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Thesis Thorup 2007 Biomechanical gait analysis in pigs

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Thesis Thorup 2007 Biomechanical gait analysis in pigs

  1. 1. Biomechanical gait analysis of pigsThe present Ph.D. thesis was part of a larger research project entitled: “Floor quality and design: Significance to the health and welfare of swine”, funded by The Danish Ministry of Food, Agriculture and Fisheries. The overall purposes of this thesis were to characterize the gait of pigs bio- mechanically and to examine the effect of floor condition on the pigs’ gait. These objectives were achieved via morphometric studies of the body segment parameters and joint rotation axes of pigs’ limbs, and not least a biomechanical analysis of walking pigs. By combining data from these studies through inverse dynamics the joint loads in the limbs of walking pigs were calculated. More specifically the present thesis aimed firstly to measure the body segment parameters and determine the joint rotation axes of pigs’ limbs (paper I). Secondly, to characterize the walk of pigs on dry solid concrete floor, evaluate whether pigs modify their gait according to floor condition, and suggest a co- efficient of friction that ensures pigs safe walking on solid concrete floors (pa- per II). Finally, to calculate the net joint forces and moments of the fore- and hindlimb joints of pigs walking on solid concrete floor and examine the effect of floor condition on the net joint reaction forces and joint moments (paper III). Ph.D. thesis by Vivi Mørkøre Thorup Ph.D.thesisBiomechanicalgaitanalysisofpigsViviMørkøreThorup ISBN: 87-91771-13-7 Department of Exercise and Sport Sciences Faculty of Science, University of Copenhagen, Denmark and Department of Animal Health, Welfare and Nutrition Faculty of Agricultural Sciences, University of Aarhus, Denmark
  2. 2. BIOMECHANICAL GAIT ANALYSIS OF PIGS © Vivi Mørkøre Thorup, M.Sc. Department of Exercise and Sport Sciences Faculty of Science, University of Copenhagen, Denmark and Department of Animal Health, Welfare and Nutrition Faculty of Agricultural Sciences, University of Aarhus, Denmark Ph.D. thesis Submitted May 31st 2007 Defended October 5th 2007 Evaluation committee: Professor John Rasmussen, Ph.D., The AnyBody Group, Department of Mechanical Engineering, Faculty of Engineering, Science and Medicine, Aalborg University, Denmark Professor Stig Drevemo, Ph.D., Department of Anatomy, Physiology and Biochemistry, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Sweden Assoc. Professor Kurt Jørgensen, Dr. scient., Department of Exercise and Sport Sciences, Faculty of Science, University of Copenhagen, Denmark (Chairman of evaluation committee) Supervisors: Assoc. Professor Bente Rona Jensen, Ph.D., Department of Exercise and Sport Sciences, Faculty of Science, University of Copenhagen, Denmark Head of Research Unit Birte Lindstrøm Nielsen, Ph.D., Department of Animal Health, Welfare and Nutrition, Faculty of Agricultural Sciences, University of Aarhus, Denmark Bente Jørgensen, Ph.D., formerly at the Danish Institute of Agricultural Sciences, Denmark Cover layout: Simon Schierbeck Layout: Vivi Mørkøre Thorup Printed by: Det Samfundvidenskabelige Fakultets ReproCenter ISBN: 87-91771-13-7
  3. 3. BIOMECHANICAL GAIT ANALYSIS OF PIGS Ph.D. thesis by Vivi Mørkøre Thorup Department of Exercise and Sport Sciences Faculty of Science, University of Copenhagen, Denmark and Department of Animal Health, Welfare and Nutrition Faculty of Agricultural Sciences, University of Aarhus, Denmark 2007
  4. 4. PREFACE PREFACE This Ph.D.-thesis is submitted to the Department of Exercise and Sport Sciences, Faculty of Science, University of Copenhagen, Denmark. The study was carried out in periods from 2002 to 2007, mainly at the Department of Animal Health, Welfare and Nutrition, Faculty of Agricultural Sciences, University of Aarhus, Denmark. The thesis is part of a larger research project (no. 3412-04-00114) entitled: “Gulvkvalitet og gulvudformning: Betydning for svins sundhed og velfærd” (Floor quality and design: Significance to the health and welfare of swine), commonly known as “Gulvprojektet”. The project was initiated by Bente Jørgensen seconded by the head of research unit, Karin Hjelholt Jensen, at the former Danish Institute of Agricultural Sciences, Research Centre Foulum. Gulvprojektet and the present thesis were funded by The Danish Ministry of Food, Agriculture and Fisheries. Being interdisciplinary this Ph.D.-project has presented many challenges to me, as the worlds of biomechanics, agriculture and biology had to meet. It has been exciting, difficult, long, but also very educating. Moreover, due to the various disciplines involved, I have tried to keep the language relatively non-specialised, so that a broad audience may understand it. I truly hope that the research presented here will be useful to other researchers in these areas and not least of benefit to pigs in future pig production. I appreciate my supervisors: Bente Rona Jensen, Department of Exercise and Sport Sciences, University of Copenhagen; Bente Jørgensen, formerly at the Danish Institute of Agricultural Sciences (supervisor Nov. 2002 to Feb. 2007); and Birte Lindstrøm Nielsen, Department of Animal Health, Welfare and Nutrition, University of Aarhus (supervisor Dec. 2006 to May 2007) for their support and guidance. Further, my sincerest thanks to my additional co-authors Frede Aa. Tøgersen, Department of Genetics and Biotechnology, University of Aarhus and Bjarne Laursen, National Institute of Public Health, University of Southern Denmark for being incredible patient and helpful. I am grateful to my colleagues at the Faculty of Agricultural Sciences, who have contributed with their technical skills, knowledge and encouragement. In particular I would like to mention: Mette Lindstrøm Bech, Anton Steen Jensen, Jens Peder Nørgaard Nielsen, Erik Decker, Hugo Christensen, Holger Thrane and Erik Jørgensen. Also I would like to thank fellow students and colleagues at the Faculty of Science for help at programming, discussions
  5. 5. PREFACE on biomechanics and other things, in particular Pia Melcher, Jesper Sandfeld, Peter K. Larsen and Tine Alkjær. I would also like to thank Perstrup Beton Industri A/S, Kolind, Denmark for supplying the floor material. Furthermore my deepest appreciation to my friends for their support, especially Bodil M. Hjarvard for among many other things sharing the struggle of writing a Ph.D.-thesis, to my family for having faith in me, and not least to Tommy for his endless love and encouragement and for being a fantastic wizard of computers and digital printing. Finally, I am grateful to all the four-legged creatures, both pets and production animals that crossed my path during this thesis and contributed to making my life funnier and more diverse. In the thesis all photos were taken by me, unless otherwise mentioned. Vivi Mørkøre Thorup Foulum, May 2007
  6. 6. TABLE OF CONTENTS TABLE OF CONTENTS Preface Table of contents Summary…………………………………………………………………………………..7 Summary in Danish……………………………………………………………………….9 Abbreviations………………………………………………………………….……...….11 List of papers………………………………………………………………….………….12 1. General introduction…………………………………………………….………….13 Background…………………………………………………………………….……..…..13 Gait analysis…………………………………………………………………….…..….…16 Friction………………………………………………………………………….………...19 Aims………………………………………………………………………………………21 Outline…………………………………………………………………….…………...….21 2. Methods……………………………………………………………….…...…………23 Animals…………………………………………………………………….…………......23 Experimental set-ups and procedures…....………………………………….……………23 Data processing…………………………………………………………….……………..28 Statistical analysis………………………………………………………….……………..30 3. Results………………………………………………………………….…………….32 Morphometrics……………………………………………………………….…………...32 Gait analysis………………………………………………………………….…………...34 Floor friction……………………………………………………………………………...40 4. General discussion…………………………………………………………………..41 Comparative morphometrics……………………………………………………………...41 Morphometric method considerations…………………………………………………....43 Gait characteristics……………………………………………………………………......44 Floor condition effects on gait…………………………………………………………....46 Friction…………………………………………………………………………………....47 Ethical considerations………………………………………………………………….....48 5. Conclusions and perspectives……………………………………………………....49 Conclusions……………………………………………………………………………......49 Perspectives……………………………………………………………………………......49 6. References…………………………………………………………………………...51
  7. 7. TABLE OF CONTENTS Appendices…………………………………………………………………………….....58 I. Paper I……………………………………………………………………………….....58 II. Paper II………………………………………………………………………………....71 III. Paper III………………………………………………………………………………..81
  8. 8. SUMMARY 7 SUMMARY Leg problems are a burden to both the pigs and the farmers in modern pig production, because leg problems decrease the welfare of the pigs, they are highly prevalent and one of the main reasons for removing the pigs prematurely from production. One of the principal causes of leg problems is the pig pen floor, or rather inappropriate floors. Especially inadequate frictional properties leading to slippery floor conditions may contribute to these leg problems. Until now the effect of floor condition on the gait of pigs has not been characterised scientifically. The overall objectives of the present thesis were to characterize the gait of pigs biomechanically and to examine the effect of floor condition on the pigs’ gait. These objectives were achieved via two types of studies, namely morphometric studies of the body segment parameters and joint rotation axes of pigs’ limbs, and a biomechanical analysis of walking pigs. By combining the data from these studies through inverse dynamics the joint loads in the limbs of walking pigs can be calculated. The thesis is based on three papers which more specifically aimed to: 1) Measure the body segment parameters and determine the joint rotation axes of pigs’ limbs; 2) Characterize the walk of pigs on dry solid concrete floor, evaluate whether pigs modify their gait according to floor condition, and suggest a coefficient of friction that ensures pigs safe walking on solid concrete floors; 3) Calculate the net joint forces and moments of the fore- and hindlimb joints of pigs walking on solid concrete floor and examine the effect of floor condition on the net joint reaction forces and joint moments. The results showed that the joint rotation axes were located mainly at or near the attachment site of the lateral collateral ligament of the joints. The body segment parameters revealed that the pigs’ forelimb was lighter and shorter than their hindlimb. Furthermore, the biomechanical analysis showed that on wet and greasy floor conditions the pigs lowered the walking speed and the peak utilized coefficient of friction compared to dry floor. Moreover, the pigs shortened the progression length, i.e. step length, and prolonged the stance phase duration on greasy floor. The inverse dynamics revealed that the forelimb peak horizontal joint reaction force and the hindlimb minimum horizontal joint reaction force were lowest on greasy floor. Also the forelimb joint moments were displaced to a lower level on greasy floor compared to dry and wet floors. In addition the gait analysis showed that during walk the forelimbs carried more body weight and received higher peak ground reaction forces than the hindlimbs. Finally the hindlimb stance phase was shorter than the stance phase of the forelimbs.
  9. 9. SUMMARY 8 In conclusion this thesis presents the first experimental data on the joint rotation axes and body segment parameters of pigs’ limbs. The locations of the joint rotation axes were described relative to bony landmarks and may serve as skin marker positions in kinematics. Furthermore the quantification of the body segment parameters enables inverse dynamic analysis of the locomotion of pigs. Moreover, the biomechanical analysis showed that floor condition did affect the pigs’ gait in several ways. Among other things the pigs lowered their walking speed and peak utilized coefficient of friction, shortened their steps and prolonged their stance phase duration on greasy and potentially slippery floor. The inverse dynamics revealed that, as a consequence of these gait adaptations, numerous joint parameters were affected by floor condition, especially in the forelimbs. Overall, greasy floor appeared the most slippery condition to the pigs, whereas wet floor was intermediate of dry and greasy conditions. The gait analysis also revealed some biomechanical differences between the limbs, as the forelimbs carried more weight and had longer stance phases than the hindlimbs, consequently the pigs’ forelimb joints responded more markedly to floor condition than their hindlimb joints. Finally the gait analysis indicated that a high static coefficient of friction is needed to prevent pigs from slipping on dry concrete floors.
  10. 10. SAMMENDRAG (SUMMARY IN DANISH) 9 SAMMENDRAG Benproblemer er en byrde for både grisene og producenterne i moderne svineproduktion, fordi benproblemer nedsætter grisenes velfærd, forekommer meget hyppigt og er en af de vigtigste årsager til at fjerne grisene fra produktionen før tid. En af hovedårsagerne til benproblemer er gulvet i svinestien, eller rettere uhensigtsmæssige gulve. Især upassende friktionsegenskaber, der medfører glatte gulve, kan bidrage til disse benproblemer. Hidtil er gulvtilstandens effekt på grises gang ikke blevet videnskabeligt beskrevet. De overordnede formål med den foreliggende afhandling var, at karakterisere grises gang biomekanisk, samt at undersøge effekten af gulvtilstand på grisenes gang. Disse mål blev opnået gennem to typer af studier, nemlig morfometriske studiee af kropssegmentparametre og ledrotationsakser for griseben, samt en biomekanisk analyse af gående grise. Ved at kombinere data fra disse studier i invers dynamik kan ledbelastningerne i benene på gående grise beregnes. Denne afhandling er baseret på tre artikler, som mere specifikt havde til formål at: 1) Måle kropssegment-parametrene og bestemme ledrotationsakserne for griseben; 2) Karakterisere grises gang på tørt fast betongulv, undersøge om grise tilpasser deres gang efter gulvtilstand, samt foreslå en friktionskoefficient, som tillader grisene at gå sikkert på faste betongulve; 3) Beregne netto ledreaktionskræfterne og ledmomenterne i for- og bagben på grise, der går på fast betongulv, samt undersøge gulvtilstandens effekt på netto ledreaktionskræfterne og ledmomenterne. Resultaterne viste, at ledrotationsakserne var placeret ved eller nær vedhæftningspunktet for leddenes laterale colaterale ligamenter. Kropssegmentparametrene viste, at grisenes forben var kortere og lettere end deres bagben. Endvidere viste den biomekaniske ganganalyse, at på våde og fedtede gulve sænkede grisene ganghastigheden og den maksimale anvendte friktionskoefficent sammenlignet med tørt gulv. Desuden afkortede grisene den tilbagelagte afstand pr. skridt, dvs. skridtlængden, og øgede standfasevarigheden på fedtet gulv. Den inverse dynamik afslørede, at forbenets maksimale horisontale ledreaktionskraft og bagbenets minimale horisontale ledreaktionskraft var lavest på fedtet gulv, endvidere var forbenets ledmomenter forskudt til et lavere niveau på fedtet gulv i sammenligning med tørre og våde gulve. I tilgift viste ganganalysen, at under gang bar forbenene mere af kropsvægten og modtog større maksimale underlagsreaktionskræfter end bagbenene. Endelig var bagbenenes standfase kortere end forbenenes.
  11. 11. SAMMENDRAG (SUMMARY IN DANISH) 10 Det kan konkluderes, at denne afhandling præsenterer de første eksperimentelle data på ledrotationsakser og kropssegmentparametre på griseben. Ledrotationsaksernes placering blev beskrevet relativt i forhold til knoglefremspring og kan fungere som hudmarkørplaceringer i kinematiske analyser. Desuden muliggør kvantificeringen af kropssegmentparametrene en invers dynamisk analyse af grises bevægelse. Den biomekaniske ganganalyse viste, at gulvtilstanden påvirkede grisenes gang på adskillige måder. Bl.a. sænkede grisene ganghastigheden og den maksimale anvendte friktionskoefficent, samt afkortede skridtene og øgede standfasevarigheden på fedtet, og dermed potentielt glat, gulv. Den inverse dynamiske analyse viste, at som følge af disse gangtilpasninger var mange ledparametre påvirket af gulvtilstanden, især i forbenene. Generelt syntes fedtet gulvtilstand at være den glatteste, mens vådt gulv var mellemliggende i forhold til tørre og fedtede gulve. Ganganalysen afslørede også, at benene adskilte sig biomekanisk på flere måder, idet forbenene bar mere vægt og havde længere standfase end bagbenene, hvilket førte til tydeligere responser på gulvtilstand i forbensleddene end i bagbensleddene. Endelig indikerede ganganalysen, at en høj statisk friktionskoefficent er nødvendig for at sikre grisene mod udskridninger på tørre betongulve.
  12. 12. ABBREVIATIONS 11 ABBREVIATIONS a: constant acceleration α: angular acceleration BSP: body segment parameter BW: body weight COF: coefficient of friction (µ) dCOF: dynamic COF sCOF: static COF uCOF: utilized COF COM: centre of mass COMrel: relative position of the COM calculated as the dprox in percent of segment length dprox: distance from COM to proximal segment end D(YL): offspring from Duroc boars crossed with Yorkshire × Danish Landrace sows F: force Ff: frictional force Fn: normal force g: gravitational acceleration GRF: ground reaction force GRFap: ante-posterior horizontal GRF GRFml: medio-lateral horizontal GRF GRFv: vertical GRF Inertia: moment of inertia or rotational inertia ICOM: moment of inertia around the COM Iprox: moment of inertia around the proximal segment end JAR: joint axis of rotation JRF: joint reaction force JRFh: horizontal JRF JRFv: vertical JRF M: moment or torque ml: external load mass n: number of observations rt: turntable radius s.d.: standard deviation s.e.: standard error sp: distance between photocells tl: load drop time
  13. 13. LIST OF PAPERS 12 LIST OF PAPERS Paper I Vivi Mørkøre Thorup, Frede Aakman Tøgersen, Bente Jørgensen and Bente Rona Jensen (2007a). Joint axes of rotation and body segment parameters of pig limbs, Acta Veterinaria Scandinavica 49:20. 10 pp. (doi: 10.1186/1751-0147-49-20). Provisional pdf reprinted with kind permission from BioMed Central Ltd. Paper II Vivi Mørkøre Thorup, Frede Aakman Tøgersen, Bente Jørgensen and Bente Rona Jensen (2007b). Biomechanical gait analysis of pigs walking on solid concrete floor, Animal 1: 708-715. Reprinted with kind permission from The Animal Consortium. Paper III Vivi Mørkøre Thorup, Bjarne Laursen and Bente Rona Jensen. Net joint kinetics in the limbs of pigs walking on concrete floor during dry and contaminated conditions, manuscript submitted to Journal of Animal Science.
  14. 14. GENERAL INTRODUCTION 13 1. GENERAL INTRODUCTION Background In modern pig production leg problems are extremely common and constitute a major welfare problem in the slaughter pig population as well as in the breeding stock. The term ‘leg problems’ is not an exact diagnosis, as it covers: locomotor disturbances; claw disorders; and joint disorders like osteochondrosis and osteoarthrosis (Jørgensen, 2003). Locomotor difficulties range from shortened strides to severe lameness during which the animal refuses to bear weight on the affected limb and is unwilling or unable to stand (Hill, 1992). Other signs of leg weakness are e.g. buck-kneed forelimbs, upright pasterns, turned-out limbs, and standing-under-position in the hindlimbs (Jørgensen, 2003), Figure 1.1. Figure 1.1: Multiple leg disorders in a pig (left): Standing-under position in the hindlimbs. The forelimbs are standing wide apart, are turned-out and buck-kneed (photo by Bente Jørgensen). A pig without leg disorders (right) is shown for comparison. A pig claw consists of a soft skin covered heel bulb and a hard keratinous sole at the toe (Webb, 1984), Figure 1.2. Examples of leg problems related to the claws are overgrowth and lesions (cracks or erosions) in the wall, sole and/or bulb (Mouttotou et al., 1997; Jørgensen, 2000).
  15. 15. GENERAL INTRODUCTION 14 Figure 1.2: The volar surface of a pig’s foot showing the two main claws and partly one of the accessory claws. The dark area indicated by the white ring is an example of heel erosion (photo by Bente Jørgensen). Table 1.1: Frequencies of pigs affected by leg problems as reported in literature. No. of studied pigs Affected (%) Diagnosis Study Breeding animals culled prematurely 172 Danish sows from herds with mortality>10% 72 Locomotor disorders (Kirk et al., 2005) 1372 Danish sows from 37 herds 59 Leg problems (Vestergaard et al., 2004) 272 North American sows from herds with mortality>12% 44 Locomotor problems (Irwin et al., 2000) 263 Danish sows randomly selected at slaughterhouse 29 Leg weakness (Christensen et al., 1995) 67 boars from random Norwegian breeding stations 24 Leg weakness (Grøndalen, 1974) Pigs slaughtered at normal time 246 Danish boars and gilts from housing experiment 13; 19; 9 Leg weakness; osteochondral changes; claw disorders (Jørgensen, 2003) 3988 boars from Danish breeding stations (examined in vivo at 93 kg) 21 Leg weakness (Jørgensen and Andersen, 2000) 3974 English pigs from convenience selected herds 94 Foot lesions (Mouttotou et al., 1997) 2000 Hungarian pigs 85 Claw disorders (Kovacs and Beer, 1979) 373 Norwegian boars and gilts from feeding experiments 48 Leg weakness (Grøndalen, 1974) 3195 English pigs randomly selected at slaughterhouse 65 Foot lesions (Penny et al., 1963) The prevalence of leg problems is high and has been for years (Table 1.1). More than 22 million slaughter pigs were produced in 2005 in Denmark (Anonymous, 2006). Even a low soleheel bulb
  16. 16. GENERAL INTRODUCTION 15 estimate of 13% affected animals would mean that at least 2.86 million slaughter pigs suffered from leg weakness in 2005. In addition to reduced welfare of the affected animal leg problems cause economic losses to farmers due to reduced growth performance, decreased carcass quality, and lost breeding potential as both replacement animals as well as breeding animals are slaughtered prematurely (Kroes and van Male, 1979; Hill, 1992). Moreover, lame sheep (Ley et al., 1989) and lame cows (Whay et al., 1997) displayed an increased sensitivity to a mechanical noxious stimuli, indicating that these animals were in a hyperalgesic state. Furthermore administering an anti-inflammatory drug to lame cows improved their gait (Weary and Flower, 2006). These findings strongly indicate that lameness is associated with pain in the affected animals, and it is reasonable to speculate that the association is similar in swine. Figure 1.3: Schematic presentation of the multiple causes of leg problems. The causes of leg problems are multi factorial, possible causal agents are: inappropriate floors (Jørgensen, 2003); genetics (Jørgensen and Andersen, 2000); infections (Hill, 1992); nutrition; and lack of exercise caused by small pens and/or high stocking densities (Jørgensen, 2003), Figure 1.3. The pig pen floor has several properties affecting the animals housed on them, e.g. friction; abrasiveness; surface profile, i.e. edges or grooves; hardness; dimension, i.e. slat to gap ratio or percentage drainage; and durability, i.e. resistance to wear (Webb and Nilsson, 1983; Baxter, 1984; McKee and Dumelow, 1995). Floors with too low friction may cause slips damaging the joints due to overexertion and falls which may cause burns, impact Leg problems Genetics Infections Lack of exercise Inappropriate nutrition Floor properties
  17. 17. GENERAL INTRODUCTION 16 injuries and ultimately can result in fractured legs. Hard floors, as opposed to yielding floors, do not reduce mechanical pressure on claws or other contacting surfaces by redistributing the load over a wider area and can cause bruising and swollen joints from lying on the floor. Too abrasive floors cause excessive wear of the claws and skin lesions whereas too little abrasiveness leads to overgrown claws (McKee and Dumelow, 1995). Moreover, slippery floors can potentially make animals adopt abnormal movement patterns, which may have adverse effects on the limbs. Already decades ago knowledge of what constitutes a good floor and measurements of foot/floor interactions to quantify the biological consequences of the physical floor properties was called for (Webb and Clark, 1981a). In addition, Danish legislation (Anonymous, 2000) states that in new pig houses for slaughter pigs one third of the floor must be solid or drained, but in spite of the legislation the effect of floor type on the locomotion of pigs is unknown. However, to consider all the physical floor properties is beyond the scope of this project, which focused on the frictional property of the floor in relation to pig gait. Pigs are mainly housed on slatted or partly slatted floors but normal gait on solid floor has to be characterized, before the effect of different slatted floors on the gait of pigs can be established. Gait analysis Biomechanics Traditionally, the assessment of pig locomotion, or more precisely gait, has been done subjectively by judging the pigs clinically and scoring them on a scale from normal to severe changes (Jørgensen and Vestergaard, 1990). However, technological advances in the field of biomechanics have made it possible to undertake objective and more advanced, yet non- invasive studies of gait. The most commonly applied methods of biomechanical gait analysis are kinematics and kinetics. Kinematics analyses the displacement of body segments, or joint axes of rotations (JARs), over time usually by video recordings. Kinetics analyses the forces causing the displacement or movement, for instance by measuring ground reaction forces (GRFs) with a force plate. Both kinetics and kinematics have been widely applied in the study of humans (Simonsen et al., 1997; Alkjær et al., 2001) and domestic animals. Especially horses have been subjected to
  18. 18. GENERAL INTRODUCTION 17 gait analysis (Drevemo et al., 1980; Merkens and Schamhardt, 1988; Martinez-del Campo et al., 1991; Gustås et al., 2007), but also the gaits of dogs (Budsberg et al., 1987; Hottinger et al., 1996), cows (Herlin and Drevemo, 1997; van der Tol et al., 2003; Flower et al., 2007) and chickens (Corr et al., 2003) have been studied biomechanically. In pigs however, biomechanical gait analysis is sparse and not very detailed. Thus Webb and Clark were, to my knowledge, the first to show examples of GRF and pressure measurements of a walking pig, but their study did not quantify any variables (Webb and Clark, 1981a; Webb and Clark, 1981b). Furthermore, in a kinematic study eight pigs weighing 32 to 41kg were filmed as they walked across wet concrete floors of differing friction (Applegate et al., 1988). In that study the stance phase duration of the hindlimbs was 9% shorter compared to the forelimbs. Further the pigs’ forelimbs slipped more and longer and showed more angular changes compared to the hindlimbs. The floor friction affected the displacement (slip) variables significantly, but not variables like e.g. the stride (step) length and stride velocity (walking speed). The floors were however exposed to the pigs for 22 hours prior to testing, which increased the initial friction considerably in five cases and decreased it in one case, and since the mean of the friction before and after testing was used for the statistics, this may have confounded the results. A few kinematic studies of treadmill walking pigs also exist (Calabotta et al., 1982; Barczewski et al., 1990), however these studies did not focus much on gait related measurements, but rather on measurements related to structural soundness (i.e. conformation), such as the torso length, distance between the hocks, and the angle of the pastern segments relative to horizontal. Inverse dynamic modeling Kinematics and kinetics do not describe the internal forces in the limbs. Nevertheless internal forces can be calculated using a linked segment model, which consists of rigid segments linked to each other at the joints. The input for the linked segment model consists of kinematic and kinetic data from moving animals along with measurements of their body segment parameters (BSPs). In Figure 1.4 the tree types of input are shown with thick lines. Together with knowledge of the BSPs, i.e. the segment masses, moments of inertia and centers of mass, usually obtained from cadaver studies, an inverse dynamic solution is used to calculate the net joint forces and moments. Net joint forces describe the resultant of all the forces acting across a joint, i.e. bone, ligament and muscular forces (Vaughan et al., 1999). Correspondingly net joint moments, which are produced by forces acting through a moment
  19. 19. GENERAL INTRODUCTION 18 arm resulting in rotary motion of a segment, describe the resultant moment of force or torque produced by the muscles, tendons and ligaments, thus giving information about the amount of muscle activity and whether the joints are dominated by a flexor or extensor moment. Figure 1.4: Schematic presentation of applied inverse dynamics. Modified after Vaughan and colleagues (Vaughan et al., 1999). BSPs for inverse dynamic modeling have been reported for various species, such as horses (van den Bogert, 1989; Buchner et al., 1997) and dogs (Nielsen et al., 2003). Also the JAR locations of horses (Colahan et al., 1988) and dogs (Arnoczky et al., 1977) have been examined. To my knowledge, neither the BSPs nor the JAR locations have been studied in pigs. Over the last decade inverse dynamic solutions have been used to describe the joint moments in the limbs of walking horses (Colborne et al., 1998; Clayton et al., 2000; Clayton et al., 2001) and dogs (Nielsen et al., 2003; Colborne et al., 2005). The tibio-femoral joint contact Body segment parameters: mass, length & moment of inertia Inverse dynamics model (equations of motion) Body segment displacements (kinematics) Ground reaction forces (kinetics) Net joint forces & moments Measurements of body segments Angular velocities, accelerations & angles
  20. 20. GENERAL INTRODUCTION 19 forces in surgically operated sheep have also been described using inverse dynamics (Taylor et al., 2006), but neither the joint reaction forces nor the joint moments have been analysed in pigs. Friction As mentioned earlier pigs reared under intensive production systems may have limited exercise possibilities caused by the generally small pens and/or high stocking densities. Lack of exercise reduces muscle weight and bone strength in sows (Marchant and Broom, 1996) and it reduces bone development in growing pigs (Weiler et al., 2006). Thus the floor in the part of the pig pen, which is meant for feeding, drinking, dunging and moving around (i.e. not the resting area) should not, by being slippery, further restrain the pigs from exercising or restrict their normal behavioural repertoire, such as play behaviour or settling of dominance relationship. In relation to slipperiness the main factor involved is the coefficient of friction (COF) of the floor, which is a measurement of the force generated between the contacting surfaces of two materials or objects, e.g. the floor and the foot. The COF, represented by the symbol µ, is a constant, which is measured as the ratio between the frictional force (Ff), meaning the force parallel to the sliding surface, and the normal force (Fn), which is always perpendicular to the normal force (Young and Freedman, 2004). This relationship is shown in Equation 1.1: µ = Ff / Fn (1.1) Two frictional measurements are used, depending on whether the contacting surfaces are motionless, i.e. static, in which case the static COF (sCOF) is used. If one or both of the surfaces are in motion, the dynamic COF (dCOF) is used. By measuring the ratio between the Ff and Fn just before sliding starts, the sCOF is obtained, whereas the dCOF is measured once sliding has started. The dCOF is usually lower than the sCOF (Young and Freedman, 2004). It is the actual contact area on a microscopic level between the two surfaces, not the total area that determines the COF, therefore the roughness and hardness of the two contacting surfaces influence the COF. Furthermore the COF can be influenced by the presence of contaminant fluids on the floor surface (Redfern and Bidanda, 1994) and by contact pressure, velocity, type of test equipment and test conditions (Baxter, 1984; Redfern et al., 2001).
  21. 21. GENERAL INTRODUCTION 20 Walking safely depends on a proper COF between a subject’s foot and the floor. When determining the slip propensity of a subject walking on a particular floor, the COF required by the walking subject is typically compared with the sCOF or dCOF available at the foot/floor interface. The required or utilized coefficient of friction (uCOF) is defined as the ratio between the resultant horizontal and vertical ground reaction forces at the subject-floor interface. In theory, a slip occurs when the uCOF produced during foot-floor contact exceeds the available COF (Redfern et al., 2001). In this way the relationship between the utilized and the available COF expresses the risk of slipping. In walking humans anticipating a slippery floor postural and temporal gait adaptations reduced the peak uCOF (Cham and Redfern, 2002). Furthermore, the peak uCOF has been shown to increase with increased walking speed (Powers et al., 2002). In cows the locomotion has been investigated during dry, wet and slurry-covered floor conditions (Phillips and Morris, 2000). Moreover the slips of cows on dry and slurry-covered solid floors have been studied (Albutt et al., 1990), and the uCOFs produced by cows performing three different locomotor behaviours have also been examined (van der Tol et al., 2005). Additionally, in cows increasing the sCOF showed a rapid decrease in slipping according to results rearranged by Webb and Nilsson (Webb and Nilsson, 1983). In pigs, however, biomechanical analyses studying the effects of floor condition on locomotion are few despite the high prevalence of leg problems. As mentioned, one study kinematically analysed the gait of pigs on floors with different friction coefficients (Applegate et al., 1988), however no GRFs were measured. Another study measured the GRFs of young pigs walking on sailcloth, for which the authors only estimated the COF (Webb and Clark, 1981a). Slips occur considerably more often in sows manoeuvring on a smooth metal floor compared to a ridged plastic floor (Leonard et al., 1997) and a rubber mat (Boyle et al., 2000). In these studies the slipperiness of the floors, unfortunately, was not measured. Hence, it has so far not been studied kinetically whether pigs adapt their gait according to the floor condition. In addition the floor of a pig pen is often wet, dirty or greasy from water, urine and faeces, consequently it is important to examine the floors under similar, so-called contaminated, yet standardized conditions.
  22. 22. GENERAL INTRODUCTION 21 Aims The purposes of this project were to: • Characterize the walk of healthy pigs on concrete solid floor • Examine if pigs modify their gait according to floor condition • Suggest a safe COF, i.e. a minimum threshold, for solid concrete floors • Measure the body segment parameters (i.e. mass, COM and moment of inertia) of pigs’ limbs • Determine the rotation axes of the joints of pigs’ limbs • Calculate the net reaction forces and moments of the fore- and hindlimb joints of pigs walking on solid concrete floor • Examine the effect of floor condition on the net joint reaction forces and joint moments Outline In chapter 2 the materials and methods are summarised, followed by the results in chapter 3. Chapter 4 is a general discussion of the results presented in this thesis. Conclusions and perspectives are given in chapter 5. Chapter 6 is a list of the references used through chapters 1 to 5. The thesis is based on three papers referred to by Roman numerals. An overview of the measured variables and where they are reported is given in Table 1.2.
  23. 23. GENERAL INTRODUCTION 22 Table 1.2: An overview of the variables analysed in the present thesis and where they are discussed. Paper I Paper II Paper III Thesis Morphometrics Body weight (BW) X X X X Limb length X X Joint axes of rotation (JAR) X X Segment mass X X Segment length X X Segment centre of mass (COM) X X Segment moment of inertia X X Kinematics Walking speed X X Stance phase duration X X Swing/stance duration ratio X X Progression length X X Kinetics Peak vertical GRF X X Time to peak vertical GRF X Mean vertical GRF X X Peak horizontal GRFap X X Min horizontal GRFap X X Peak horizontal GRFml X X Min horizontal GRFml X X Peak uCOF X X Time to peak uCOF X Peak vertical JRF X X Peak horizontal JRF X X Min horizontal JRF X X Peak joint moment X X Min joint moment X X Floor properties Static COF X X Dynamic COF X X
  24. 24. METHODS 23 2. METHODS Animals Two groups of pigs without visual abnormalities on the limbs were used for the morphometric studies described in Paper I. To locate the JARs six castrates and six gilts were used. Their average body weight (BW) immediately after slaughtering, thus corresponding to live BW was 77+7kg (range 64 to 85kg). To establish the BSPs one castrate and four gilts with an average BW of 69+5kg (range 63 to 73kg) were used. The pigs used for the gait analysis described in Paper II and III were 30 gilts or castrates from 17 different sows. The pigs’ average BW was 75+6kg (range 64 to 86kg). They showed no signs of lameness, i.e. they walked without limping when allowed to walk freely on solid floor outside their home pen. All of the 42 pigs studied in the present thesis were Duroc × Yorkshire × Landrace, i.e. D(YL) crossbreeds. They were fed ad libitum and housed on partly slatted concrete at the Faculty of Agricultural Sciences (the former Research Centre Foulum), University of Aarhus. Experimental set-ups and procedures Morphometrics To establish the JARs the right fore- and hindlimbs were removed from the slaughtered pigs, and the skin and muscles were removed from the limbs without disarticulating the joints. The eight joints examined were the shoulder (scapulohumeral), elbow (humeroradial), carpal (carpal complex), forefetlock (metacarpophalangeal), hip (coxofemoral), stifle (femorotibial), hock (tarsal) and hindfetlock (metatarsophalangeal), Figure 3.1. With the bones lying on the medial side digital photos were taken of each joint in extended, neutral and flexed position around the mediolateral axis, see Figure 2.1 for an example of the shoulder joint. The JARs were calculated from the photos by drawing bisecting lines parallel to the proximal-to-distal axis of the bone at fixed landmarks and locating the intersection (Leach and Dyson, 1988). For alignment of the photos two reference points were placed at distinct landmarks on one bone of the joint, and on the other bone two reference points defined a bisecting line parallel
  25. 25. METHODS 24 to the proximal-to-distal axis of that bone. The intersection of the three lines marked the JAR. The results are described qualitatively in relation to bony landmarks palpable on the skin. Figure 2.1 Locating the shoulder joint (lateral view). Photos of extended (bottom layer), relaxed (middle) and flexed (top) positions are overlaid. Layers are aligned after two large dots on the humerus. Two small dots on the scapula define the bisecting lines parallel to the proximal-to-distal bone axis. The average of the intersection points is the JAR. Figure 2.2 Schematic representation of the experimental set-up for measurement of the segmental moment of inertia. The turntable is shown unloaded, i.e. without a segment. Unloaded turntable Photocell Photocell External load
  26. 26. METHODS 25 For the study of the BSPs the right fore- and hind limbs were separated from the trunks of the slaughtered and exsanguinated pigs and cooled. The chilled limbs were dissected into segments along craniocaudal lines as close as possible to the identified JARs, after which the segments were frozen in horizontal position with the lateral side up. The ten segments investigated were the: humerus, radius/ulna, metacarpus, forepastern (proximal and middle phalanges), foretoe (distal phalanges), femur, tibia, metatarsus, hindpastern (proximal and middle phalanges), and hindtoe (distal phalanges). The mass; the length; the distance between the center of mass (COM) and the proximal segment end (dprox); and the moment of inertia were measured on the frozen segments. The sagittal plane COM was located by balancing the segments transversely and longitudinally with the lateral side up. The moment of inertia was measured by strapping the segments onto a custom made low-friction horizontal turntable. An external load connected to the turntable was dropped, made the turntable turn and passed between two photocells measuring the drop time of the load. The experimental set-up for measuring the moment of inertia is shown in Figure 2.2. The equations used for calculating the moment of inertia are given later in the section regarding data processing. Gait analysis For the gait analysis the pigs walked individually on the test floor along a 0.5m wide and 6m long aisle. The test floor was solid concrete (flagstone, Perstrup Concrete Industry A/S, Kolind, Denmark) with a rough and absorbing surface (Figure 2.6 left). Three floor conditions: Dry, wet (tap water) and greasy (rape seed oil) conditions were tested with 10 pigs each. Bony landmarks were palpated and seven markers placed on the right limbs of the pigs (Figure 2.3). The marker set-up can be found on page 2 showing a pig during gait analysis. Furthermore, the marker set-up is described and shown schematically in Paper III, Figure 1. Kinematic and kinetic data were collected simultaneously from the pigs, as they walked at a self-selected, steady speed. Three to four successful trials for both the fore- and hindlimbs were obtained.
  27. 27. METHODS 26 Figure 2.3: Marker placement. The bony landmark of the hip is palpated (left) and the marker is placed (right) using acrylic painting (photos by Anton S. Jensen). The GRFs and moments were recorded at 1KHz from a 0.20×0.30m2 force plate (MU2030, Bertec Corporation, Columbus, OH) embedded in the central part of the aisle. The force plate was mounted with the test floor on it, invisible to the pigs. A digital video camera (NV- DS30EG, Panasonic Denmark, Glostrup, Denmark) recorded the central 1.4m of the aisle from the right side in the sagittal plane at 50Hz. The camera shutter speed was set to 1/500s and 150W lamp ensured sufficient illumination of the pigs’ markers. As a pig stepped on the force plate a light emitting diode (LED) within the camera field, but above the view of the pigs, went on to synchronize kinetic and kinematic data. The force data collection, turning on and off the LED, and turning off the camera was done by custom-made software (SideStepper version 1.3b, TA, Aalborg, Denmark). The experimental gait analysis set-up is shown in Figure 2.4. The object field of the aisle was calibrated using a rectangular frame with four points that encompassed the field of analysis. The force plate coordinate system (schematically shown in Figure 2.5) was defined so that the vertical GRFs (GRFv) were positive during the stance phase. The anteposterior horizontal GRFs (GRFap) were defined as positive in the direction of movement. The horizontal mediolateral forces (GRFml) were positive when directed laterally (outwards).
  28. 28. METHODS 27 Figure 2.4: The experimental set-up for the gait analysis. From this angle the solid test floor in the aisle is hardly visible. Figure 2.5: The force plate coordinate system with the positive GRFv, GRFap and GRFml directions indicated. The ground reaction forces are shown as reaction-oriented. Floor friction The COFs of the dry, greasy and wet floor conditions were measured1 using an Instron 5569 drag device (Figure 2.6). The drag device had a polyether urethane material (Elastollan 1185A, Elastogran GmbH, Lemförde, Germany) on the measuring surface (area: 0.064×0.064m2 ; weight: 5kg), which was dragged across the test surface at a speed of 0.002m/s. The sCOF was defined as the peak occurring at the onset of movement, and the dCOF as the mean of measurements made over a distance of approximately 0.1m. The average sCOFs and dCOFs were calculated from 10 measurements. 1 At The Danish Technological Institute, Gregersensvej 1, DK-2630 Taastrup, Denmark video camera force plate filmed section of aislecupboard with pc LED walking directon GRFv (Fz) GRFap GRFml (Fx) + + +
  29. 29. METHODS 28 Figure 2.6: Left: The experimental set-up for the floor friction measurements. Right: A close-up of the concrete floor with the dragging device (Photos by Søren Pedersen, Danish Technological Institute). Data processing In the morphometric studies regarding the JARs, minor uncertainty in placing the reference points at landmarks usually generated three points of intersection in the photos, therefore an arithmetic average of the three points was calculated (Figure 2.1). To obtain the BSPs, the relative position of the COM was calculated as the dprox in percent of the total segment length. The calculation of the moment of inertia was based on well-known laws of physics and will be explained in the following. A load dropped vertically over a distance s will fall or move with a constant linear acceleration a for the time t (equation 2.1): s = ½ a • t2 a = 2 s/t2 (2.1) Further, the angular acceleration α can be calculated from the a and from the radius of the turntable rt according to equation 2.2:
  30. 30. METHODS 29 α = a/rt (2.2) Substituting equation 2.1 into equation 2.2 yields equation 2.3: α = (2s/t2 )/rt = 2s/(t2 • rt) (2.3) Then the moment M of the load affecting the turntable was calculated from the radius rt and the force F (equation 2.4). Here F was calculated from the mass of the load ml and the gravitational acceleration g according to Newton’s second law, the law of acceleration. M = F • rt = ml • g • rt (2.4) By applying Newton’s second law to rotational motion, i.e. the relationship between M and α, the moment of inertia of the system Isys could be calculated according to equation 2.5: M = Isys • α Isys = M/α (2.5) By substituting equations 2.3 and 2.4 into 2.5, thus yielding equation 2.6, the Isys could be calculated from the mass of the external load ml (0.203kg); the gravitational acceleration g (9.82m/s2 ); the radius of the turntable rt (0.15m); the distance between the two photocells sp (1.317m); and the load drop time tl: Isys = ((ml • g • rt) • (tl 2 • rt))/2s = (ml • g • rt 2 • tl 2 )/2sp (2.6) Finally, the segment moment of inertia was calculated by subtracting the moment of inertia of the unloaded turntable from the moment of inertia of the turntable loaded with the segment. The metacarpal, metatarsal, pastern and toe segments were too light to have their moment of inertia measured with the described set-up, thus their moment of inertia was estimated from their mass, length and circumference according to equation 2.7, assuming that the segments were cylindrical (Vaughan et al., 1999). Furthermore the toe segments could not be balanced, therefore their COM and moment of inertia were approximated.
  31. 31. METHODS 30 moment of inertia = mass/12 • (length2 + 0.076 • circumference2 ) (2.7) The video sequences from the gait analysis were digitized using Pinnacle Studio (version 8, Pinnacle Systems, Inc., Mountain View, CA), 2-dimensional coordinates were constructed and digitally low-pass filtered by a fourth order Butterworth filter with a cut-off frequency of 8Hz using APAS (Ariel Dynamics Inc, Trabuco Canyon, CA). The kinetic data were downsampled to 50Hz to fit the sampling frequency of the kinematic data. Furthermore the kinetic data were normalized in magnitude by body mass to enable comparisons between individuals of different body mass. To compensate for differences in stance phase durations all data were normalized in time by interpolating data points to form 100 samples for each stance phase. The kinematic data, kinetic data and the BSPs were combined in an inverse dynamic solution using a linked segment model (Quanbury et al., 1975). Assumptions to the model were that segments were rigid, that the joints were ideal hinge joints, and that movement was pure rotation around a fixed axis (Winter, 2004). Positive joint moments were defined such that counterclockwise moments acting on a segment distal to the joint were positive, whereas clockwise moments were negative (Winter, 2004). The extensor side was the cranial (anterior) side for the elbow, hip, and tarsal joints, and the caudal (posterior) side for the other joints (Paper III Figure 1). All calculations made for the project were programmed in MATLAB (2002, The MathWorks Inc, Natick, MA, USA). Statistical analysis In Paper I the locations of JARs were described anatomically and the BSPs were measured. The results were presented as means + standard deviations (s.d.). For Paper II statistical comparisons of floor conditions and of the limbs were made using a two-way ANOVA test. The kinematic and kinetic variables were tested separately in a repeated measurement model. Floor condition and limb were the systematic effects. The random effects were the sow (i.e. kinship); the residual error term; and the repeated effect of
  32. 32. METHODS 31 trials (within pig limb), which was incorporated into the model under the assumption that neighbouring trials were more correlated than those farther apart. With three floor conditions, ten pigs per condition, two limbs per pig and four trials per limb, this yielded a maximum number of observations of 240 for each variable. However, some trials were discarded upon close inspection, mainly due to incomplete force data at the beginning or end of the stance phase. Differences in body parameters, meaning the BW and limb length between pigs from the three floor conditions were tested in a SAS GLM procedure (2001, SAS Institute Inc, Cary, NC). The sCOF and dCOF of the floor conditions were tested using a paired t-test. In Paper III comparisons of the floor conditions and of the joints were performed using a two- way ANOVA test. All the kinematic and kinetic variables were tested separately in a repeated measurement model. Floor condition and joint were the systematic effects. The random effect was the residual error term and the repeated effect of joint (within pig limb), which was incorporated in the model under the assumption that adjacent joints were more correlated than those farther apart. The trials were averaged per limb, furthermore differences between joints were compared within limbs only. The three floor conditions, ten pigs per condition and five joints per pig yielded a maximum number of observations of 150 for each variable. The SAS MIXED procedure (2001, SAS Institute Inc, Cary, NC) was used for the ANOVA tests. A level of significance of 5% was used throughout unless otherwise mentioned.
  33. 33. RESULTS 32 3. RESULTS Morphometrics The average and the individual JAR locations are shown in Figure 3.1 in which they are scaled to the fore- and hindlimbs of one pig. The JARs were primarily located at or near the attachment sites of the lateral collateral joint ligaments. Figure 3.1: The average (crosses) and individual (dots) JAR locations of 12 pigs related to one animal. Lateral view. Top: Forelimb with the shoulder (1F), elbow (2F), carpal (3F) and fetlock (4F) JARs. Bottom: Hindlimb with the hip (1H), stifle (2H), tarsal (3H) and fetlock (4H) JARs. For scaling purposes a measuring stick with black and white fields of 1cm was placed next to the bones.
  34. 34. RESULTS 33 The average weight decrease due to blood loss and water evaporation from the whole carcasses was 5.2% BW. The relative BSPs reported in Table 3.1 were the values used for the biomechanical model described in Paper III. In Paper I, Table 1 the absolute BSPs were reported in addition to the relative values. The COM ranged from 31 to 50% of the segment length measured from the proximal segment end, meaning that the COM was located proximally in all segments. The segment mass as well as the moment of inertia decreased with increasing distance from the trunk, thus the proximal segments were the heaviest and had the largest moments of inertia. Table 3.1: The relative BSPs: the segment mass (% BW); the COM (distance from the proximal segment end to the COM in % of segment length); and the moment of inertia around the proximal segment end (Iprox, % BW×segment length2 ) for the right fore- and hindlimb segments from slaughtered animals. Values are means (s.d.) of five pigs. Mass COM Iprox % % % Forelimb Humerus 1.94 (0.12) 46 (2) 0.00813 (0.00094) Radius/ulna 1.05 (0.04) 31 (3) 0.00264 (0.00040) Metacarpus 0.18 (0.03) 49 (2) 0.00061 (0.00011)T Pastern 0.15 (0.01) 45 (2) 0.00050 (0.00002)T Toe 0.04 (0.00) 50A 0.0001A Hindlimb Femur 6.50 (0.22) 50 (5) 0.01376 (0.00147) Tibia 1.44 (0.07) 40 (4) 0.00385 (0.00040) Metatarsus 0.42 (0.03) 32 (6) 0.00092 (0.00015)T Pastern 0.16 (0.01) 40 (6) 0.00044 (0.00007)T Toe 0.04 (0.01) 50A 0.0001A A Approximated; T Three pigs.
  35. 35. RESULTS 34 Gait analysis Kinematics The pigs walked with a four-beat gait characterized by alternating two and three limb support phases. The fore- and hindlimbs differed kinematically (Table 3.2.), thus the stance phase duration of the forelimbs was longer compared to the hindlimbs, and the swing to stance phase ratio was lower on the forelimbs than on the hindlimbs. Floor condition affected the kinematics (Table 3.2), as the pigs’ walking speed was faster on dry condition compared to contaminated conditions. In addition the progression length was longer on dry condition compared to greasy condition, whereas wet condition was intermediate. Furthermore the stance phase lasted longer on greasy condition compared to dry and wet conditions. Table 3.2: The kinematic gait variables for the floor conditions and/or limbs reported as least square means (s.e.). Floor condition Limb n Dry Wet Greasy Fore Hind Walking speed (m/s) 192 0.88 (0.03)a 0.79 (0.03)b 0.74 (0.03)b Progression length (m) 192 0.75 (0.01)a 0.73 (0.01)ab 0.70 (0.01)b Swing/stance phase ratio 192 0.62 (0.02)A 0.70 (0.02)B Stance phase duration (s) 226 0.60 (0.02)a 0.63 (0.02)a 0.69 (0.02)b 0.69 (0.02)A 0.59 (0.02)B Different superscripts denote significant differences at the levels: a,b 0.001<P<0.01; A,B P<0.001. Table 3.3: The vertical ground reaction force (GRFv) and utilized coefficient of friction (uCOF) variables reported as least square means (s.e.). n Condition Forelimb Hindlimb Mean GRFv (N/Kg) 226 3.76 (0.04)a 3.22 (0.04)b Peak GRFv (N/Kg) 233 5.63 (0.06)a 4.43 (0.06)b PeakTime GRFv (%) 226 59 (2)a 34 (2)b Peak uCOF 224 Dry 0.48 (0.02)a Wet 0.42 (0.02)b Greasy 0.32 (0.02)c PeakTime uCOF (%) 224 6 (4)a 23 (4)b a, b Different superscripts denote significant differences at P<0.001.
  36. 36. RESULTS 35 GRFs and utilized friction The vertical GRF time course followed a two-humped pattern with the second maximum typically being higher than the first maximum in the forelimb. In the hindlimb the vertical GRF time course was also two-humped, but the first maximum was typically the highest (Figure 3.2). The time course of the GRFap was approximately sinusoidal, and the GRFml was mostly negative during the stance phase (Figure 3.2). The mean and peak GRFv were higher in the forelimbs than in the hindlimbs (Table 3.3). Figure 3.2: A typical example of the vertical (GRFv), anteposterior horizontal (GRFap) and mediolateral horizontal (GRFml) ground reaction forces exerted by the forelimb (left curves) followed by the hindlimb (right curves) of a pig walking on dry floor. For both limbs the uCOF was highest at the beginning and towards the end of the stance phase with a minimum around mid stance (Paper II, Figure 2). The peak uCOF was lower on greasy floor compared to wet floor, which again was lower compared to dry floor (Table 3.3). The timing variables of the peak vertical GRF (PeakTime GRFv) and of the peak uCOF (PeakTime uCOF) were not normally distributed, thus their corresponding P-values should be interpreted with caution, nevertheless the time to peak GRFv was longer in the forelimbs compared to the -1 0 1 2 3 4 5 6 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Time (s) Force(N/Kg) Forelimb Hindlimb GRFv GRFap GRFap GRFml GRFml
  37. 37. RESULTS 36 hindlimbs, whereas the time to peak uCOF was shorter in the forelimbs than in the hindlimbs (Table 3.3). Regarding the horizontal GRFs there were differences between the limbs and between the floor conditions (Paper II, Table 2). The floor effects are evident from Figure 3.3. Thus the forelimb peak GRFap was lower on greasy floor compared to the other conditions. In the hindlimbs the peak GRFap was higher on wet floor compared to dry and greasy conditions and the minimum GRFap was more negative on dry floor than on contaminated floors. Further the peak GRFml in the hindlimbs was higher on dry floor compared to the contaminated conditions. The limbs differed (Paper II, Table 2) in the following ways: The peak GRFaps on the contaminated conditions were lowest in the forelimbs. On dry floor the hindlimb minimum GRFap was more negative than on the contaminated conditions. The hindlimbs exerted higher peak GRFml than the forelimbs, whereas the minimum GRFml was most negative in the forelimbs. Figure 3.3: The peak and minimum horizontal GRFs (N/kg) for both limbs. White bars: dry condition; Black bars: wet condition; Grey bars: greasy condition. Top row: Anteposterior (ap) forces. Bottom row: Mediolateral (ml) forces. Values are least square means, n=227. Error bars are s.e. A star indicates that the condition concerned differs significantly from the two others. -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 GRFap(N/kg) -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 GRFap(N/kg) -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 GRFml(N/kg) -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 GRFml(N/kg) Hindlimb Forelimb D W G GWD
  38. 38. RESULTS 37 Joint kinetics The time courses of the vertical and horizontal JRFs (Paper III, Figure 3) were similar to those of their respective GRFs (Figure 3.2), further the peak vertical JRF was approximately 8 times higher than the peak horizontal JRF (Table 3.4). Greasy floor condition decreased the peak horizontal forelimb JRF compared to dry condition, whereas wet condition was intermediate (Table 3.4a). Moreover the minimum horizontal hindlimb JRF was smaller (i.e. less negative) on contaminated conditions compared to dry condition (Figure 3.4). The peak vertical JRF was not affected by floor condition in any of the limbs (Table 3.4a). Table 3.4a: The peak and minimum JRFs (N/kg×10-2 ) and joint moments (Nm/kg×10-2 ) of the fore- and hindlimbs for the three floor conditions. Values are least square means (s.e.) across all joints, n=150. Condition Dry Wet Greasy P Forelimb Peak JRFv (N/kg×10-2 ) 549 (10) 557 (10) 562 (10) Peak JRFh (N/kg×10-2 ) 77 (4)a 67 (4)ab 60 (4)b * Min JRFh (N/kg×10-2 ) -77 (5) -75 (5) -80 (5) Peak M (Nm/kg×10-2 ) 23.2 (1.2)a 23.0 (1.2)a 18.4 (1.2)b ** Min M (Nm/kg×10-2 ) -9.1 (0.9)a -9.1 (0.9)a -11.9 (0.9)b * Hindlimb Peak JRFv (N/kg×10-2 ) 427 (8) 433 (8) 424 (8) Peak JRFh (N/kg×10-2 ) 77 (3)ab 83 (3)a 75 (3)b <0.1 Min JRFh (N/kg×10-2 ) -89 (3)a -76 (3)b -74 (3)b *** Peak M (Nm/kg×10-2 ) 20.9 (1.2) 22.0 (1.2) 20.5 (1.2) Min M (Nm/kg×10-2 ) -5.9 (0.5) -5.4 (0.5) -5.8 (0.5) a, b Within a row condition means that do not have a common superscript differ significantly (* P < 0.05; ** P < 0.01; *** P < 0.001). The peak vertical JRFs were highest in the distal joints and lessened with decreased distance from the trunk (Table 3.4b). The elbow and shoulder joints differed from each other, moreover they exerted both higher peak horizontal JRFs and more negative minimum horizontal JRFs than
  39. 39. RESULTS 38 the other forelimb joints. The hip exerted higher peak horizontal JRFs as well as more negative minimum horizontal JRFs compared to the other hindlimb joints (Table 3.4b). Figure 3.4: The peak and minimum horizontal JRFs (N/kg) for the three floor conditions. White bars: dry condition; Black bars: wet condition; Grey bars: greasy condition. Values are least square means, n=150. Error bars are s.e. Stars indicate that min JRFh hindlimb dry condition is significantly most negative, and that peak JRFh forelimb dry and greasy conditions differ. Table 3.4b: The peak and minimum JRFs (N/kg×10-2 ) and joint moments (Nm/kg×10-2 ) of the fore- and hindlimb joints. Values are least square means (s.e.) across all floor conditions, n=150. Joint Coffin Fetlock Carpal/Tarsal Elbow/stifle Shoulder/hip Forelimb Peak JRFv (N/kg×10-2 ) 566 (6)a 565 (6)b 563 (6)c 552 (6)d 534 (6)e Peak JRFh (N/kg×10-2 ) 70 (2)a 70 (2)a 70 (2)a 66 (2)b 64 (2)c Min JRFh (N/kg×10-2 ) -75 (3)a -75 (3)a -76 (3)a -77 (3)b -83 (3)c Peak M (Nm/kg×10-2 ) 15.8 (0.9)a 21.6 (0.9)b 22.8 (0.9)b 34.5 (0.9)c 12.8 (0.9)d Min M (Nm/kg×10-2 ) -1.0 (0.7)a -0.9 (0.7)a -2.3 (0.7)a -8.4 (0.7)b -37.6 (0.7)c Hindlimb Peak JRFv (N/kg×10-2 ) 447 (4)a 446 (4)a 441 (4)b 429 (4)c 377 (4)d Peak JRFh (N/kg×10-2 ) 78 (2)a 77 (2)a 76 (2)a 76 (2)a 85 (2)b Min JRFh (N/kg×10-2 ) -77 (2)a -77 (2)a -78 (2)a -79 (2)a -88 (2)b Peak M (Nm/kg×10-2 ) 14.3 (0.9)a 22.2 (0.9)b 32.9 (0.9)c 11.0 (0.9)d 25.2 (0.9)e Min M (Nm/kg×10-2 ) -0.9 (0.5)a -0.5 (0.5)a -1.4 (0.5)a -15.4 (0.5)b -10.3 (0.5)c a, b Within a row joint means with differing superscripts differ significantly at P<0.001. -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 Horizontaljointforce(N/kg) -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 Horizontaljointforce(N/kg) Hindlimb Forelimb D DW G W G
  40. 40. RESULTS 39 The joint moment time courses were similar across all floor conditions, but differed between joints (Paper III, Figure 2). The shoulder moment had a small flexor dominated peak around 16% stance phase, then shifted to extensor domination with a large negative minimum around 76% stance. The elbow moment increased quickly towards an extensor dominated peak around 26% stance, then declined to flexor domination having a negative minimum at 95% stance. The carpal joint was entirely flexor dominated. The flexor dominated fore- and hindfetlock joint moments had similar patterns rising moderately towards the peaks around 73% and 62%, respectively. The flexor dominated fore- and hindcoffin joint moment patterns were also alike, with slow increases until peaking at approximately 78% stance. The mainly extensor dominated hip moment peaked around 38% stance with only a short flexor dominated period with a minimum at 90% stance. The stifle moment was initially small with a flexor dominated peak around 18% stance, it then shifted to extensor domination with a negative minimum around 80% stance. The entirely extensor dominated tarsal joint moment peaked around 37% stance. A timing pattern was present, as the peak moment occurred early in proximal joints and later the more distal the joint. Floor condition caused different forelimb joint moment magnitudes. Thus in the forelimb greasy condition lowered the peak moment by 21% compared to dry and wet conditions, moreover the minimum moment was 24% more negative on greasy than on dry and wet conditions (Table 3.4a and Figure 3.5). Figure 3.5: The peak and minimum joint moments (Nm/kg). White bars: dry condition; Black bars: wet condition; Grey bars: greasy condition. Values are least square means, n=150. Error bars are s.e. Stars indicate that in the forelimb greasy condition differs significantly from the other conditions with respect to both peak and min joint moments. -0.2 -0.1 0 0.1 0.2 0.3 Jointmoment(Nm/kg) -0.2 -0.1 0 0.1 0.2 0.3 Jointmoment(Nm/kg) Hindlimb Forelimb D DW G W G
  41. 41. RESULTS 40 The majority of the joints differed with regard to both peak and minimum moments (Table 3.4b). Thus the highest moment amplitudes (i.e. the range between the peak and minimum moments) in the forelimb were in the shoulder and elbow joints. In the shoulder the large range was caused by a highly negative moment, whereas in the elbow the range was due to a very high positive moment. In the hindlimbs the highest joint moment amplitudes were in the hip and tarsal joints, which both showed considerable peak and minimum moments. Floor friction In general the dynamic COFs tended to be lower than the static COFs (Figure 3.6), although the only significant difference between the sCOF and dCOF was on greasy floor. As expected the dCOF was lowest on greasy floor, surprisingly however the sCOF was unaffected by floor condition. Figure 3.6: The static (S) and dynamic (D) COFs (dimensionless) for the three floor conditions. Values are means of 10 measurements. Error bars are s.d. The star indicates that greasy condition dCOF is significantly lower than the other measurements. 0.00 0.20 0.40 0.60 0.80 COF(dimensionless) Dry S Dry D Wet S Wet D Greasy S Greasy D
  42. 42. GENERAL DISCUSSION 41 4. GENERAL DISCUSSION Comparative morphometrics The location of the JARs around the attachment sites of the lateral collateral ligament of the joints (Paper I) were consistent with findings in which the rotation axes of the shoulder, elbow, carpal, forefetlock, stifle, hock, and hindfetlock joints of anaesthetized horses were radiographed (Leach and Dyson, 1988) and with findings for the forefetlock JAR, where dead horses had Steinman pins inserted and were radiographed (Colahan et al., 1988). It was also coherent with marker placement in large-breed dogs (Hottinger et al., 1996), where the greater trochanter was used for representation of the hip JAR in a kinematic gait analysis, and by radiography which located the stifle JAR on the condyle of the femur in dead dogs (Arnoczky et al., 1977). When comparing the pigs’ BSPs (Paper I, Table 1) to those of dogs, ponies and horses reported in the literature (Table 4.1) a general pattern was found. Here the pigs’ pastern and toe segments together correspond to the digit segment in the other species. Thus the segment mass and ICOM both decreased with increasing distance from the trunk in all species. The relatively heavy trunk and light limbs has previously been stated to be a global design in quadrupeds that facilitates fast limb movements without large inertial forces (Schamhardt, 1998), and is caused by the majority of the hindlimb muscle mass being located proximal to the ankle joint (van Ingen Schenau and Bobbert, 1993), meaning the tarsal joint in the pigs. In further detail the pigs, with an average BW of 69kg, had a weight distribution in the limb segments more similar to ponies of 203kg (van den Bogert, 1989) than to mixed-breed dogs of 25kg (Nielsen et al., 2003) or to horses of approximately 500kg (Sprigings and Leach, 1986; Buchner et al., 1997). Furthermore the relative segment masses of the pigs’ distal segments, i.e. the radius/ulna, metacarpus, foredigit, metatarsus and hinddigit were the lowest among the species compared, whereas the pigs’ proximal segments, i.e. the humerus, femur and tibia segments of the hindlimb were the second heaviest. Thus the global design with light distal segments relative to the heavy proximal segments seems to be very pronounced in pigs, and may be due to extensive breeding for more meat on the trunk and proximal limb parts.
  43. 43. GENERALDISCUSSION 42 Table4.1:Thebodysegmentparametersandbodyweightofdogsandhorsesfromotherstudies.Thesegmentmass(%BW;COMrel(the distancefromtheproximalsegmentendtotheCOMin%ofsegmentlength;ICOM(kg*m2 *10-3 )andaverageBW+s.d.(kg)ofsixdogs,five ponies,threeThoroughbredhorsesandsixDutchWarmbloodhorses,respectively.Thedigitscomprisethepasternandtoesegments. SpeciesMixed-breeddogs1 Ponies2 Thoroughbreds3 DutchWarmbloods4 AverageBW+s.d.25.3+2.5kg203+30kg473+67kg538kg MassCOMrelICOMMassCOMrelICOMMassCOMrelMassCOMrelICOM %BW%kg•m2 •10-3 %BW%kg•m2 •10-3 %BW%%BW%kg•m2 •10-3 Forelimb Humerus2.9946.95.51.844.727--1.6051.0110 Radius/ulna1.2641.01.41.135.0221.4043.01.2535.0129 Metacarpus0.3847.10.140.2947.13.40.4350.30.3044.014.6 Foredigit0.3250.00.080.30--0.4558.10.3492.09.1 Hindlimb Femur---6.050.91606.747.53.4659.0340 Tibia---1.248.018.31.439.51.5437.9145 Metatarsus---0.4935.611.40.638.00.5332.050 Hinddigit---0.28--0.451.90.3592.010.1 1 Nielsenetal.,2003;2 vandenBogert,1989;3 SprigingsandLeach,1986;4 Buchneretal.,1997.
  44. 44. GENERAL DISCUSSION 43 Morphometric method considerations The JAR locating method assumed that all movement was in the sagittal plane, however the spread locations of the hip and elbow JARs suggested that slight movement occurred in other planes as well (Paper I), as argued for the elbow joint of horses (Leach and Dyson, 1988). Besides, muscle and skin was removed from the bones to expose the bony landmarks and avoid errors introduced by skin movement (van Weeren et al., 1992). This removal may, however, have allowed the joints to deviate slightly from their anatomical sagittal plane. Although performed by one experienced technician the dissection procedure may have contributed to the inter-individual variation of the BSPs, which was somewhat larger than the variation of the BW (Paper I). Another likely explanation for the BSP variation in pigs of similar BW could be conformational differences between the pigs. The COM and the moment of inertia of the pigs' toe segments were approximated, as these segments could not be balanced and were too light to have their moment of inertia measured (Paper I). However, considering the small mass of the toe segments, the moment of inertia would be negligible therefore it was approximated as the lowest possible input value for the biomechanical model. The moments of inertia are used for calculating the net joint moments only, and during the stance phase the contributions from the inertial parameters to the net joint moments are very small because the velocity and acceleration of the limb segments are low (Vaughan et al., 1999). In horses’ forelimb the sensitivity of inverse dynamics to segmental inertial parameter errors has been studied during the swing phase of trot (Lanovaz and Clayton, 2001). That study concluded that mass errors produced larger net moment errors than segmental COM location errors, while moment of inertia errors had the least effect. Further inertial parameter errors affected the distal segments more than the proximal segments. Thus using estimated moments of inertia rather than measured ones in the present thesis is likely not to have introduced serious errors. The BSPs were measured on segments from exsanguinated and frozen carcasses, which meant lower segment weights due to an average blood loss and water evaporation of 5.2% of live BW (Paper I). Others have reported a blood loss of 7.3 to 13.7% for ponies (van den Bogert, 1989) and a blood, water and saw loss of 2.4% on Dutch Warmbloods (Buchner et al., 1997). However, the distribution of blood and water cannot be assumed to be uniform across segments, because the distal segments have a higher ratio of bone to muscle and thus less blood than the proximal segments,
  45. 45. GENERAL DISCUSSION 44 therefore the segment masses were not corrected. For the inverse dynamic analysis (Paper III) this may have caused a small underestimation of the proximal segment masses and an even larger underestimation of the moment of inertia due to the second power proportionality between the mass and the moment of inertia. Gait characteristics At low speeds the typical gait chosen by most mammals is the walk, during which the animal moves its feet with an alternating two and three limb support phases (Schamhardt, 1998), which has been confirmed for dogs, sheep, cows and horses (Jayes and Alexander, 1978; Nunamaker and Blauner, 1985; Hottinger et al., 1996; Hodson et al., 2001; Flower et al., 2005). This thesis showed that at the walk the pig, too, has alternating two and three limb stance phases, and that the swing phases are shorter than the stance phases with the difference being largest in the forelimbs (Paper II). Furthermore, pigs that are allowed to walk unrestrictedly on dry floor walk at a self-selected speed of 0.88m/s during which they progress 0.75m per step and the stance phases last 0.69s and 0.59s for the fore- and hindlimbs, respectively (Paper II). The speed reported for the pigs in this thesis agrees very well another study of pigs using a treadmill speed of 0.9m/s at which the pigs were reported to be walking comfortably (Calabotta et al., 1982). In a quietly standing quadruped a gravitational force corresponding to approximately one quarter of the body mass will be acting on each limb (Schamhardt, 1998). Furthermore, as the pig is an even- toed ungulate, each limb carries the weight on the tips of only two digits of a foot, namely the third and fourth digits (Figure 1.2). During walk the time course of the GRFv showed two peaks with a dip in between (Paper II). In the forelimbs the second peak was higher than the first, while in the hindlimbs the opposite was true. The time course of the horizontal GRFap was approximately sinusoidal reflecting the braking action of the pigs’ feet during the first part of the stance phase, whereas during the second part of the stance phase the positive force reflected the pigs’ propulsive action. The pigs’ GRF time courses were very similar to those of walking horses (Hodson et al., 2000; Hodson et al., 2001), but also to a biped like humans (Simonsen et al., 1997). Moreover the range or amplitude of the pigs’ GRFv standardized to BW reached 4-6N/kg, depending on which limb was measured. The pigs’ range was less than that of humans, which typically reaches 10 N/kg at normal walk. This is a consequence of the number of limbs supporting the weight, as walking humans have alternating one and two stance phases, as opposed to the two and three limb stance phases in walking quadrupeds mentioned earlier. The horizontal GRFs were much smaller, as the
  46. 46. GENERAL DISCUSSION 45 range of the GRFap was only about a third of the range of the GRFv, and the even smaller GRFml range was less than a tenth compared to that of the GRFv. The GRF ranges of the pigs were very similar to other those of other quadrupeds, such as horses (Merkens et al., 1985) and dogs (Nielsen et al., 2003). Several kinetic and kinematic variables are highly influenced by speed because the limbs are accelerated more at higher walking speeds, which should be considered when comparing variables both within and across studies. For instance faster walking speed is associated with longer stride and shorter stance time duration in horses (Khumsap et al., 2002). Further, the vertical GRFs increase significantly with faster walking speeds in both dogs and horses (Riggs et al., 1993; Khumsap et al., 2001). The time courses and ranges of the JRFs (Paper III) were similar those of their respective GRFs (Paper II). The peak vertical JRFs lessened with decreased distance from the trunk, as a consequence of lower accelerations and less weight above the joint in the more proximal joints. During stance phase the joint moments serve mainly to resist the GRFs, as the moments needed to act against gravity and to accelerate the limb can be considered negligible (Lanovaz and Clayton, 2001). Further a joint moment is associated directly with the combination of forces acting across the joint, and being a quadruped with four multijointed limbs the pigs can redistribute its joint moments in several ways without visual changes (van den Bogert, 1998). Therefore the time courses of the pigs’ joint moments were much more complicated than their corresponding JRFs and differed considerably between the joints. However, compared to other quadrupeds the joint moment patterns of the pigs (Paper III) were more or less similar to those of dogs and horses (Colborne et al., 1998; Clayton et al., 2000; Clayton et al., 2001; Nielsen et al., 2003). The differences between the species in joint moment magnitudes may be caused by different body size, limb anatomy, walking speed and/or modeling approaches (Paper III). From the results it became evident that the fore- and hindlimbs differed with respect to numerous variables. Pigs carried most weight by their forelimbs (Paper II), which, taken together with the finding that, the forelimbs were lightest (Paper I), may explain why leg problems occur more frequently in the forelimbs than in the hindlimbs (Jørgensen et al., 1995). It may also explain why the forelimbs kinetically responded more pronounced to floor condition than did the hindlimbs (Paper III).
  47. 47. GENERAL DISCUSSION 46 In pigs joint disorders occur in several joints (Nakano et al., 1987), however the most frequent site of osteochondrotic lesions in the forelimbs is the elbow (Grøndalen, 1974; Jørgensen, 2000; Jørgensen and Andersen, 2000). In the hindlimbs the stifle, and to a lesser extent the hip, are frequent sites of osteocondrotic lesions (Grøndalen, 1974; Jørgensen et al., 1995). In the present thesis high joint moment amplitudes were found in the shoulder, elbow, hip and tarsal joints (Paper III), which may help explain why joint diseases occur more frequently in the proximal than the distal joints. Humans suffering from moderate osteoarthritis in the knee have a reduced net joint flexion moment at the knee during early stance phase compared to a control group without osteoarthritis (Landry et al., 2007). Thus it could be hypothesized that net joint moments in pigs suffering from joint disorders are lowered as well. Moreover biomechanical gait analysis could be applied as a diagnostic tool in pigs, parallel to what increasingly is being done in horses, dogs and cows (Khumsap et al., 2003; Trumble et al., 2005; Rajkondawar et al., 2006). Analyzing lame pigs was, however, outside the scope of this thesis. Floor condition effects on gait Floor condition influenced the pigs’ gait in numerous ways, as especially the greasy condition seemed to affect the gait biomechanics. Regarding the kinematic variables (Paper II) the pigs reduced their walking speed and progression length; the pigs also prolonged their stance phase on greasy floor. The effect of greasy floor on the pigs’ walking speed and progression length agreed well with a study on cows, which were found to walk more slowly on a floor contaminated by slurry compared to a dry floor (Phillips and Morris, 2000), and with humans, who shortened their step length when anticipating a slippery floor (Cham and Redfern, 2002; Lockhart et al., 2007). Floor condition had no effect on the vertical GRF, but it did affect the magnitude of the horizontal GRFs (Paper II). Thus hindlimb braking forces (Min GRFap) decreased on contaminated floors to the same level as the braking force in the forelimbs, and on contaminated floors the forelimb propulsive forces (Peak GRFap) decreased. Furthermore contaminated floors lowered the medially directed movements (Peak GRFml) in the hindlimbs. Because the uCOF is calculated from the GRFs, floor condition also affected the peak uCOF (Paper II), most markedly the greasy condition. The size of the reduction in the pigs’ Peak uCOF on contaminated floors was very alike the reduction observed in humans anticipating slippery floors (Cham and Redfern, 2002; Lockhart et
  48. 48. GENERAL DISCUSSION 47 al., 2007). Seeing that the uCOF is positively correlated with walking speed (Powers et al., 2002), the reduced Peak uCOF was partly explained by the pigs’ lowered speed when walking on contaminated floors. Floor condition did not affect the time courses of the joint kinetics, but the greasy and potentially more slippery floor did, however, affect several variables compared to dry floor. The magnitude of decrease in the pigs’ joint moments as a response to greasy floor concurred well with findings in humans in whom the anticipation of slippery floors lowered the peak ankle, knee and hip moments by 24-30% (Cham and Redfern, 2002). Also in walking humans a more powerful muscular knee and ankle activity when expecting a slippery surface has been shown (Chambers and Cham, 2007). Thus it is reasonable to speculate that the muscle co-contraction in the pigs walking on greasy floor was high despite the lowered peak and minimum net joint moments observed (Paper III). As the BW and limb length of the pigs were similar across floor conditions (Paper II), the effects of floor condition were not caused by different body sizes. Rather the effects of the contaminated floors on the gait biomechanics of the pigs were consequences of gait adaptations, as the pigs reacted to contaminated conditions in a way that minimized their risk of slipping on a potentially slippery surface. It could be argued that the pigs should have walked on all three floor conditions in a randomized study design, thus using each pig as its’ own control for the effect of floor condition. Nevertheless, we decided against this design, as this would have required changing between floor conditions in one day or testing the same pigs over several days. However, changing from greasy or wet conditions to either of the other conditions could not be done within one day. Testing the pigs over several days would have introduced errors from the repeatability of repositioning the markers (Kadaba et al., 1989) and from the development of the animal. Slaughter pigs gain about 1 kg/day, the onset of leg problems starts around 75 kg, and healthy animals were required for the establishment of the normative dataset presented here. Friction From a safety point of view the two most critical phases for level walking humans are the initial heel contact and the toe off (Grönqvist et al., 2001). Of these phases the heel contact is the most challenging (Redfern et al., 2001). The pattern of the uCOF presented in this thesis (Paper II)
  49. 49. GENERAL DISCUSSION 48 confirmed this to be true in pigs as well. Furthermore the results indicated that the pigs’ forelimbs were at the risk of slipping earlier than their hindlimbs (Table 3.4). In the present thesis (Paper II) a minimum COF threshold of 0.63 was suggested to ensure safe walking on a dry concrete surface. This threshold is considerably higher than the recommendations found in literature for animal housing (Bähr and Türpitz, 1976; Kovacs and Beer, 1979; Nilsson, 1988; Phillips and Morris, 2001). These recommendations were, however, given for the entire pen floor, which comprises areas for locomotion, resting and feeding, whereas this thesis focused on floor areas meant for locomotion only. The dual composition of the pig’s foot (Figure 1.2) makes it difficult to simulate with artificial materials. However, in terms of frictional property pigs’ claws are best considered as elastomers (McKee and Dumelow, 1995). Polyethylene material has previously been used to substitute a pig foot during measurements of floor COF (Kovacs and Beer, 1979; Nilsson, 1988). In the present thesis an infrared spectroscope (FTIR) test1 showed great similarity between polyether urethane and polyethylene, as a consequence we chose polyether urethane to simulate a pig claw in the COF measurements. Furthermore a load of 5kg was chosen for the COF measurements, as this load was close to the load measured during the initial stance phase of walking pigs (Paper II, Figure 1). The sCOF and dCOFs were measured at a speed of 0.002m/s, which may have been too low to mimic the walk of a pig. A speed 5 times higher (with a load of 0.2kg) was tried, but produced vibrations. Certainly, measuring the COF is not a trivial matter. Ethical considerations Healthy pigs with no signs of lameness were used throughout the experiments of this thesis. The pigs used for the morphometric studies were slaughtered according to a method commonly applied in Danish commercial slaughterhouses according to which the pigs were CO2 stunned followed by exsanguination. Furthermore, the pigs walking on contaminated floors were not subjected to a floor condition more extreme than what animals in normal intensive pig production may experience. Finally, the results of this thesis will potentially benefit the welfare of many pigs in intensive production systems by emphasizing how important the physical floor properties in pig pens are. 1 At The Danish Technological Institute, Gregersensvej 1, DK-2630 Taastrup, Denmark
  50. 50. CONCLUSIONS AND PERSPECTIVES 49 5. CONCLUSIONS AND PERSPECTIVES Conclusions Firstly, the morphometric studies offered the first experimental data on the JARs and BSPs of pigs’ limbs. The JAR locations were described relative to bony landmarks and may serve as skin marker positions in kinematics. The results of the BSPs revealed that the pigs’ forelimb was lighter and shorter than the hindlimb, and in comparison to dogs, ponies and horses the pigs’ limbs were very light relative to the trunk. Furthermore the quantification of the BSPs enabled inverse dynamic analysis of the locomotion of pigs. Secondly, the biomechanical analysis showed that floor condition did affect the pigs’ gait. Hence the pigs adapted to contaminated floor conditions by lowering the walking speed and the peak uCOF. Moreover, the pigs shortened the progression length and prolonged the stance phase duration on greasy floor. The inverse dynamics revealed that, as a consequence of the gait adaptations, the forelimb peak horizontal JRFs and the hindlimb minimum horizontal JRFs were lowest on greasy floor. Further, the forelimb joint moments were displaced to a lower level on greasy floor compared to dry and wet floors. Overall, greasy floor appeared the most slippery condition to the pigs, whereas wet floor was intermediate of dry and greasy conditions. Thirdly the gait analysis revealed several biomechanical differences between the fore- and hindlimbs, as the forelimbs carried most weight and received highest peak ground reaction forces. As a consequence of this weight distribution the pigs’ forelimb joints responded more obviously to floor condition than their hindlimb joints. Furthermore the hindlimb stance phase was shorter than the stance phase of the forelimbs. Finally the gait analysis indicated that even on a dry concrete floor a high sCOF is needed to prevent pigs from slipping. Perspectives The basic biomechanical characterization of the gait of healthy pigs from a homogenous population provided in this thesis presents a normative benchmark to compare with data from lame pigs or pigs that have had operation or surgical implants. Additionally this thesis
  51. 51. CONCLUSIONS AND PERSPECTIVES 50 quantifies the biomechanical effects of floor condition on the gait of pigs walking on wet and greasy floor conditions relative to dry floor. Future studies should further elucidate the effect of floor condition by quantifying the slip distances on different floor conditions and by investigating further biomechanical measures like foot velocities, which may play important roles in joint loading. Furthermore, as the level of muscle activity may be high on greasy floor despite of the lowered peak joint forces and moments observed, future studies should seek to quantify the level of muscle activity. Using EMG in combination with an experimental set-up described for the gait analysis in this thesis would enable a quantification of the intensity of muscle activity across a joint, which is a more precise expression of the joint load. Much more data were collected during the course of this thesis than presented here. Ten floors; one solid and 9 slatted floors of different materials (Pedersen and Levring, 2005) were examined during dry, wet and greasy conditions using 10 pigs per condition. Moreover a second camera filmed the pigs from behind in the mediolateral plane. Thus kinematic data in two planes were obtained from a total of 300 pigs. However, due to the very time consuming data processing only 10% of the pigs were analyzed for this thesis, focusing at the stance phase biomechanics. Much more work is needed before general guidelines for pig pen floors can be suggested.
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