The document provides information on creating the right training environment for athletes with visual impairments (VI). It discusses VI classification systems used in Paralympic sports, motor performance factors in athletics for athletes with VI, and training considerations. It notes that vision is impacted by impairment of the eye structure, optic nerves, or visual cortex. The classification system evolved from a 1970s model of legal blindness categories to a 2000s system accounting for visual acuity and visual field measurements. Sprinters, middle-distance runners, long-distance runners, jumpers, and throwers have different motor and guidance needs. Training must address low physical activity levels, cardiorespiratory endurance, balance, coordination, learning skills, and the psychological profile of

1. Creating the right environment for VI
training
Ciro Winckler
APB/CPB/UNIFESP

2. Professor of São Paulo Federal University
Athletics Technical Coordinator of Brazil
NPC
Member of IPC Athletics Coach Council
Member of Brazilian Paralympic Academy
Ciro Winckler

3. • Vision
• VI Classification
• Motor Performance in Athletics
• Training
Agenda

4. Visual Impairment
Vision is impacted by either an impairment of
the eye structure, optical nerves or optical
pathways, or visual cortex of the central brain.
IPC, 2015Visual Field
Visual Acuity

5. Visual Acuity
Distance where The
athlete can see and
define the object

6. Visual Field

7. VI Classification
• Model Started
of 1970 decade
• Legal Blindness
• B1 Blind
• B2 Low Vision
• B3 Low
Vision

9. VI Classification
• Decade of 2000
• Modification of the System
• 11
Visual acuity poorer than LogMAR 2.6.
• 12
Visual acuity ranging from LogMAR 1.5
to 2.6 (inclusive)
and/or Visual field constricted to a
diameter of less than 10 degrees.
• 13
Visual acuity ranging from LogMAR 1.4
to 1.0 (inclusive) and/or Visual field
constricted to a diameter of less than
40 degrees.

10. VI Classification
50 Faculteit der Bewegingswetenschappen
RESEARCH APPROACH 1
IMPAIRMENT-PERFORMANCE RELATIONSHIP
S13 S12 S11
S13 S12 S11NE
NE
R² = 0.687
R² = 0.373
VI Classification Research
Expert Meeting
Day II
Amsterdam
23-25th January 2015

11. Eye Mask or Opaque Glass

12. Visual Functions
Visual Acuity
• Sta.c
• Dinamic
Binocular Visuion
Visual Field
Color vision
Luminosity
Adapta.on
Visual Intelligence
Contrast

13. Visual
Inteligency

14. Limita&on
Experience

15. Time of the impairment
Time Life
Birth
C
ongenital
Brain
M
aturation
Acquired
Motor Development

16. Can you do the Description?

17. Can you do the Description?

18. Can you do the Description?

19. Can you do the Description?

20. Motor Performance
in Athletics

21. Sprinter
Midle and
Long
Distance
runners
Jumper
Thrower
11 12 13 Guide

22. Are Guides necessary
only for Track events?
Hay, J.G., Miller, J.A. and
Canterna, R.W. (1986).
The techniques of elite
male long jumpers.
Journal of Biomechanics,
19, 855-866.
athlete’s physical capabilities. (In long jumping, the optimum technique is usually to use the
fastest possible run-up and to spring upwards as much as possible at takeoff.)
0
2
4
6
8
10
0 2 4 6 8 10 12
run-up speed (m/s)jumpdistance(m)
Cross-sectional study (Hay, 1993)
Intervention study (Current study)
Figure 1. Comparison of results from a cross-sectional study and a technique intervention
study. (Cross-sectional data courtesy of Jim Hay.)
In contrast, the intervention study reported here considered only a single athlete. Although
the jumps by the athlete were always at maximum effort, the jumps with the slower run-ups
were not employing the optimum technique that would result in the maximum possible jump
distance. However, at any given run-up speed the technique used by the athlete was close to
the optimum for that run-up speed. This is a reasonable assumption because the athlete was
highly experienced and regularly performed jumps from a short run-up as part of his normal
training program. The trend line for the intervention study intersects that for the cross-
sectional study at a jump distance of about 8 m. This is expected because data points in this
region correspond to conditions identical to those for the cross-sectional study; namely,

23. Sprinter
Midle and
Long
Distance
runners
Jumper
Thrower
11 12 13 Guide
C
o
m
p
e
t
i
t
i
o
n
T
r
a
i
n
i
n
g

24. State of Art
BalanceCoordination
Speed of
Learning
Incidental
learning
VO2
Sedentarism
Psycologial
Profile

25. Low levels of Physical
Activity
Leverenz, 2009
Sedentarism caused by the
visual limitation or
absense of stimulation
STANFORD, 1975, HOPKINS, et al. 1987,
COMITÉ OLIMPICO ESPANHOL, 1992,
MOURA E CASTRO, COSTA, FREITAS, 1992,
WILLIANS, et al. 1996
Sedentarism

26. VO2
VO2 max. associated
with the visual acuity
level
Hopkins et al. 1987, Leverenz,
2009

27. VO2
People with blindness that
are sys tematic p hysical
activity practitioners can
develop similar results of
the VO2 of people without
disabilities
KOBBERLING; JANKOWSK & Leger, 1991

28. T h e l o w v i s u a l
capacity cau se s a
r e d u c t i o n i n
mechanical efficiency
of movement, thus
demand more energy
e x p e n d i t u r e a n d
increased fatigue
STAMFORD, 1975, HOPKINS et al., 1987
Coordination

29. Balance
VIwithout
VI

30. Psychological
Profile
VI
BRAMS
Nome Means Athlete and Guide
T-Escore FATOR T-Escore
Tension Depression Anger Vigour Fatigue Confusion
80+
79
78
77
76
75
74
73
72
71
70
69
68
67
66
65
64
63
62
61
60
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58
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51
50
49
48
47
46
45
44
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
5
4
3
2
1
0
5
4
3
2
1
0
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
11
10
9
8
7
6
5
4
3
2
1
0
9
8
7
6
5
4
3
2
1
0
80+
79
78
77
76
75
74
73
72
71
70
69
68
67
66
65
64
63
62
61
60
59
58
57
56
55
54
53
52
51
50
49
48
47
46
45
44
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
Guides
Athletes
BRAMS
Nome Gold Medalist and guide
T-Escore FATOR T-Escore
Tension Depression Anger Vigour Fatigue Confusion
80+
79
78
77
76
75
74
73
72
71
70
69
68
67
66
65
64
63
62
61
60
59
58
57
56
55
54
53
52
51
50
49
48
47
46
45
44
43
42
41
40
39
38
37
36
35
34
33
32
31
30
29
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
5
4
3
2
1
0
5
4
3
2
1
0
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
11
10
9
8
7
6
5
4
3
2
1
0
9
8
7
6
5
4
3
2
1
0
80+
79
78
77
76
75
74
73
72
71
70
69
68
67
66
65
64
63
62
61
60
59
58
57
56
55
54
53
52
51
50
49
48
47
46
45
44
43
42
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40
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36
35
34
33
32
31
30
29
guide
Athlete

31. Injuries in VI athletics
ecurrent injury,
using Microsoft
0Ò
. Descriptive
ne the total and
Wilk test was
ibution. Where
ssumed, a one-
used to assess
nd field events,
sexes. Alterna-
ess differences
ptance level of
d 31 suffered a
orrespond to a
93 injuries per
incidence rate
her prevalence
male athletes
cant (P 9 0.05).
s presented a
slightly higher prevalence of sports injuries, followed by
T/F12 and T/F13 athletes. However, T/F12 athletes showed
slightly higher clinical incidence, followed by T/F11 and
T/F13 (Table 1). There were no statistically significant dif-
ferences observed between classifications or groups in these
epidemiological data (P 9 0.05). When comparing the epi-
demiological data between event types such as track (sprint,
medium, and long distance) and field (throws and jumps), no
statistically significant differences were observed.
FIGURE 1—Mechanism of sport injury in track and field paralympic
competitions.
http://www.acsm-msse.orgSports Medicine
lege of Sports Medicine. Unauthorized reproduction of this article is prohibited.
With respect to injury mechanisms (Fig. 1), overuse in-
juries were the most prevalent (82%), and traumatic injuries
constituted the remaining smaller proportion (P G 0.05).
Figure 2 represents the distribution of sport injuries by
body segment, where the lower limbs appeared to be most
affected.
The frequency of injuries by body region (Fig. 3) revealed
that the thighs were most affected.
The frequency of sport injuries varied by diagnosis (Fig. 4),
(Table
disabi
Wh
presen
clinica
(Table
higher
that w
males
ferent,
size st
very l
and w
bodied
sports
disabi
to eva
addres
quired
lation
multip
Wit
Preval
FIGURE 2—Distribution of sport injury by body segment in track and
field paralympic competitions.
Sports Injuries in Paralympic Track and Field
Athletes with Visual Impairment
MARILIA PASSOS MAGNO E SILVA1
, CIRO WINCKLER2
, ANSELMO ATHAYDE COSTA E SILVA1
,
JAMES BILZON3
, and EDISON DUARTE1
1
Department for Adapted Physical Education, University of Campinas, BRAZIL; 2
Department for Movement Science,
Federal University of Sa˜o Paulo, BRAZIL; and 3
Department for Health, University of Bath, UNITED KINGDOM
ABSTRACT
MAGNO E SILVA, M. P., C. WINCKLER, A. A. COSTA E SILVA, J. BILZON, and E. DUARTE. Sports Injuries in Paralympic Track
and Field Athletes with Visual Impairment. Med. Sci. Sports Exerc., Vol. 45, No. 5, pp. 908–913, 2013. Purpose: The aims of this study
were to determine the epidemiology, nature, and pattern of sports injuries in Brazilian Paralympic track and field athletes with visual
impairment and to assess differences between visual classes and sex. Methods: Forty visually impaired elite Paralympic athletes par-
MAGNO E SILVA, M. P., C. WINCKLER, A. A. COSTA E SILVA, J. BILZON, and E. DUARTE. Sports Injuries in Paralympic Track and
Field Athletes with Visual Impairment. Med. Sci. Sports Exerc., Vol. 45, No. 5, pp. 908–913, 2013.

32. Races

33. The blind athletes (Class T11) should
be escorted by the athlete-guide.
The Low Vision athletes (Class T12)
can be escorted by the athlete-
guide.
The guide and the Athletes T11 or T12
run side by side, connected by a rope
The guide will provide verbal and
tactile information
Lieberman, Butcher & Moak, 2001

34. Athlete and Guide
Connection

35. Athlete and Guide
Connection

37. Athlete and Guide
Connection
Tether Model
• Style
• Technique
• Experience
• Strategy
• Event

38. Infringiment of the Rule 7.10
Push
Pull
Propel
kind of Tether

39. +3-4 mts

40. How much the guide
needs to be better than
the athlete?

42. 14
PALABRAS
CLAVE:
Discapacidad
visual,
Deporte
paralímpico,
Atletismo,
Carreras de
velocidad,
Cinemática
de la carrera
KEY
WORDS:
Visually
impaired,
Paralympic
Sport,
Athletics.
Sprint race,
Kinematic of
the race
Rev.Ib.CC. Act. Fís. Dep. 2014; 3(3): 14-23
LA CARRERA DE VELOCIDAD EN PERSONAS CON
DISCAPACIDAD VISUAL
THE SPRINT IN PERSONS WITH VISUALLY IMPAIRED
Miguel Ángel Torralba1
, José María Padullés2
, Marcelo Braz Vieira3
y Helena Olson4
1
Miguel Ángel Torralba. Doctor en Ciencias de la Educación. Profesor titular de la Universidad de
Barcelona. torralba@ub.edu
2
José María Padullés. Doctor por la Universidad de Barcelona. Profesor titular del INEFC-Barcelona.
jpadulles@gencat.cat
3
Marcelo Braz Vieira. Doctorando en Actividad Física, Educación Física y Deporte en la Universidad de
Barcelona. marcelobraz@ub.edu
4
Helena Olson. Licenciada en Ciencias de la Actividad Física. Profesora asociada de la Universidad de
Barcelona. helenajosefinolsson@hotmail.com
Código UNESCO: 240604 Biomecánica
Clasificación Consejo de Europa: 3 Biomecánica
FINANCIACIÓN
Este estudio conto con la financiación de la Universidad de Barcelona y el Instituto Nacional de Educación
Física de Cataluña (INEFC).
Recibido el: 1/9/2014
Aceptado el: 16/12/2014
RESUMEN
El presente estudio buscó identificar las diferencias que se observan en las carreras de
velocidad realizadas por atletas con discapacidad visual. Para ello se recogieron los
datos de 39 atletas ciegos de 24 países que participaron en los 100 metros de los
Juegos Paralímpicos en Beijing 2008. Los datos extraídos permiten valorar el tiempo de
carrera(s), velocidad media (m/s), número de pasos, frecuencia media (Hz), tiempo
medio de paso(s) y amplitud media de paso (m), realizando un estudio comparativo con
personas sin discapacidad. Se recogieron las grabaciones del Centro de audiovisuales
del Comité Paralímpico en Beijing (DVD), siendo los datos tratados con el paquete
estadístico SPSS (21.0). Entre los resultados, destacar la importancia que tienen la
longitud de paso y la frecuencia, donde los atletas ciegos muestran un resultado inferior
en el primer parámetro, resaltando como muy positivo la casi nula diferencia existente
en la reacción de la salida de tacos.
ABSTRACT
The present study aimed to identify differences observed in the sprints races performed
by visually impaired athletes. Data were collected from 39 blind athletes from 24
countries participated in the 100 meters Paralympic Games in Beijing 2008. The
extracted data allow to assess race time (s), average speed (m/s), number of steps,
average frequency (Hz), mean of step time (s) and mean of the step amplitude (m),
making a comparative study with non-disabled. Recordings of the audio-visual center of
Beijing Paralympic Committee (DVD) were collected, and data was processed with
SPSS (21.0). Among the results, highlight the importance of stride length and frequency,
where the blind athletes show lower results in the first parameter, highlighting a very
positive almost no difference in the reaction of output blocks.
Rev. Ib. CC. Act. Fís. Dep. 18
la carrera de 100 m, de los atletas
con discapacidad visual, categoría
ciegos (T11), con el objeto de
valorar las variables de tiempo de
reacción (s), tiempo de carrera (s),
velocidad media (m/s), número de
pasos, frecuencia media (Hz),
tiempo medio de paso (s) y amplitud
media de paso (m), teniendo en
cuenta la categoría y sexo de los
participantes. Se extrajo la media de
todas las variables y la desviación
estándar (DE), así como la mínima
han participado en los JJPP, debido
a que es una muestra muy
representativa del atletismo
mundial, ya que participaron 23
países, en la competición más
característica del deporte adaptado.
En las tablas 2 y 3 se puede
verificar los datos medios generales
de las series clasificatorias
masculinas y femeninas.
Tabla 2. Datos generales de la fase clasificatoria masculina
Marca
(s)
Vel.
Media
(m/s)
T.
reac.
(s)
T.
carrera
(s)
Nº
Pasos
Vel.
Media
real
(m/s)
Frec.
Media
(Hz)
T.
Medio
paso
(s)
Ampl.
Media.
paso
(m)
N 23 23 23 23 23 23 23 23 23
Mínimo 11,19 8,07 0,14 10,96 47,5 8,16 4,08 0,21 1,80
Máximo 12,39 8,94 0,23 12,26 55,5 9,12 4,76 0,25 2,11
Media 11,77 8,50 0,19 11,58 51,2 8,65 4,43 0,23 1,95
DE 0,32 0,23 0,02 0,33 1,7 0,25 0,18 0,01 0,06
La carrera de velocidad en personas con
discapacidad visual
Miguel Ángel Torralba et al.
Tabla 3. Datos generales de la fase clasificatoria femenina
Marca
(s)
Vel.
Media
(m/s)
T.
reac.
(s)
T.
carrera
(s)
Nº
Pasos
Vel.
Media
real
(m/s)
Frec.
Media
(Hz)
T.
Medio
paso
(s)
Ampl.
Media.
paso
(m)
N 10 10 4 10 8 10 8 8 8
Mínimo 12,41 7,14 0,19 12,17 53,5 7,14 4,26 0,22 1,72
Máximo 14,00 8,06 0,45 14,00 58,3 8,22 4,45 0,24 1,87
Media 13,12 7,63 0,28 13,01 55,8 7,70 4,35 0,23 1,79
DE 0,45 0,26 0,11 0,54 1,5 0,32 0,08 0,00 0,05
En la tabla 4 se indican los datos
referentes a las finales A y B de los
JJPP de Beijing en la categoría T11
masculina. El resultado de la
estudio de Ferro(29)
en el que indica
que la fase de vuelo es más corta
en los atletas ciegos que en los
atletas sin discapacidad que utilizó
Olympic
41-49 Steeps
RT 0,16
Olympic
47-51 Steeps
RT 0,17

43. Sprint Race
Maintenance
Top Speed
18%
Starting
Block
5%Acceleration
64
%
RT
1%
Lessened Degree of
desaceleration12%
Tellez, 2008

44. Hand Position
Foot Position
Posicionamento&

45. Orientation

46. Reaction Time
1 2
Guide 0,209 0,283
Ahlete 0,146 0,222

47. Anthropometric

48. Anthropometric
Differences
Saída&de&Bloco&

51. In review: POWER AND SPEED
DIFFERENCES BETWEEN BRAZILIAN
PARALYMPIC SPRINTERS WITH
VISUAL IMPAIRMENT AND GUIDES: A
PILOT STUDY
Figure 1. Comparisons of the velocities in 10 m between
AVI and guide athletes.
ES = 2.1 (Large), P < 0.05.
Figure 2. Comparisons of the velocities in 50 m
between AVI and guide athletes.
ES = 1.7 (Large), P < 0.05.
Panel A individual comparisons.
Panel B means of the groups and the
magnitude of the difference (%), between
parentheses are presented the 95%
confidence interval of difference

52. Isokinetics
and Speed
192,2
98,9
251,3*
130,0* 142,7
90,4
181,6*
118,0* 119,1
91,2
148,5*
112,6*
R Extensor R Flexor R Extensor R Flexor
ATHLETES GUIDES
Peak Torque
60°/s 180°/s 300°/s
6,09
7,99 8,54
6,39
8,93* 9,69*
0
2
4
6
8
10
12
10m 30m 50m
Speed
Distance
SPEED
VI G
Athletes with Visual Impairment
R. Extensor
60°/s
R. Extensor
180°/s
R. Extensor
300°/s
0-10 m 0,423 0,386 0,374
10-30 m 0,786* 0,752* 0,721*
30-50 m 0,792* 0,776* 0,731*
BARROS, R.A. ; Winckler, C. ; LOTURCO, I. . Analysis of Relationship between Strength and Speed in
Athletes with Visual Impairment and Guides Participants of Athletics Brazil Paralympic Team. In:
VISTA 2013 'Equipment and Technology in Paralympic Sports', 2013, Bonn. VISTA2013 Scientific
Conference Booklet. Bonn, 2013. v. 1. p. 81-83.

55. The stride length and
arm swing of blind
athletes and their
guides change in the
side connected
Torralba et al, 2007

58. SILVA, M. P. M. E. ; BARROS, R.A. ; Winckler, C. ; Miranda, A.J. . Evaluation of Muscle
Imbalances and the Relationship with Sport Injuries in Athletes with Visual
Impairment and their Guides. In: VISTA 2013 'Equipment and Technology in
Paralympic Sports', 2013, Bonn. VISTA2013 Scientific Conference Booklet. Bonn, 2013.
v. 1. p. 99-101.

59. ORIGINAL RESEARCH
published: 06 November 2015
doi: 10.3389/fphys.2015.00323
Edited by:
Thomas Janssen,
VU University Amsterdam,
Netherlands
Reviewed by:
Naoto Fujii,
University of Ottawa, Canada
Alvaro N. Gurovich,
Indiana State University, USA
*Correspondence:
Irineu Loturco
irineu.loturco@terra.com.br
Specialty section:
This article was submitted to
Exercise Physiology,
a section of the journal
Frontiers in Physiology
Received: 28 August 2015
Accepted: 26 October 2015
Published: 06 November 2015
Citation:
Loturco I, Winckler C, Kobal R, Cal
Abad CC, Kitamura K, Veríssimo AW,
Pereira LA and Nakamura FY (2015)
Performance changes and relationship
between vertical jump measures and
actual sprint performance in elite
sprinters with visual impairment
throughout a Parapan American
games training season.
Front. Physiol. 6:323.
doi: 10.3389/fphys.2015.00323
Performance changes and
relationship between vertical jump
measures and actual sprint
performance in elite sprinters with
visual impairment throughout a
Parapan American games training
season
Irineu Loturco1
*, Ciro Winckler2
, Ronaldo Kobal1
, Cesar C. Cal Abad1
, Katia Kitamura1
,
Amaury W. Veríssimo2
, Lucas A. Pereira1
and Fábio Y. Nakamura1, 3
1
Nucleus of High Performance in Sport, São Paulo, Brazil, 2
Brazilian Paralympic Committee, Brasília, Brazil, 3
Department of
Physical Education, State University of Londrina, Londrina, Brazil
The aims of this study were to estimate the magnitude of variability and progression in
actual competitive and field vertical jump test performances in elite Paralympic sprinters
with visual impairment in the year leading up to the 2015 Parapan American Games,
and to investigate the relationships between loaded and unloaded vertical jumping
test results and actual competitive sprinting performance. Fifteen Brazilian Paralympic
sprinters with visual impairment attended seven official competitions (four national, two
international and the Parapan American Games 2015) between April 2014 and August
2015, in the 100- and 200-m dash. In addition, they were tested in five different periods
using loaded (mean propulsive power [MPP] in jump squat [JS] exercise) and unloaded
(squat jump [SJ] height) vertical jumps within the 3 weeks immediately prior to the main
competitions. The smallest important effect on performances was calculated as half
of the within-athlete race-to-race (or test-to-test) variability and a multiple regression
analysis was performed to predict the 100- and 200-m dash performances using the
vertical jump test results. Competitive performance was enhanced during the Parapan
American Games in comparison to the previous competition averages, overcoming the
smallest worthwhile enhancement in both the 100- (0.9%) and 200-m dash (1.43%). In
addition, The SJ and JS explained 66% of the performance variance in the competitive
results. This study showed that vertical jump tests, in loaded and unloaded conditions,
could be good predictors of the athletes’ sprinting performance, and that during the
Parapan American Games the Brazilian team reached its peak competitive performance.
Keywords: Paralympics, track and field, muscle power, physical disability, blind athletes

60. Table 1. Predictions of 100- and 200-m dash performances using multiple regression analysis.451
452
453
TABLE 1454
455
Table 1. Predictions of 100- and 200-m dash performances using multiple regression analysis.456
457
R2 Equation
100-m 0.66* y = 15.558 - (0.063 x SJ) - (0.061 x JS)
200-m 0.66* y = 32.918 - (0.167 x SJ) - (0.098 x JS)
458
Note: SJ = squat jump; JS = jump squat; P < 0.01.459
Loturco et al. Performance of Paralympic sprinters
FIGURE 3 | Linear regression between 100 (A,C) and 200-m (B,D) dash performances and the squat jump (SJ) height and relative mean propulsive
power (MPP REL) in the jump squat (JS) exercise; *P < 0.01.
regression models have increased only (on average) ∼1.2% of
the explained variance between dependent (actual sprint times)
and independent variables (SJ and JS), we considered relevant
TABLE 2 | Predictions of 100- and 200-m dash performances using
multiple regression analysis.
R2 Equation

61. Practical Impact
• Athletes with similar anthropometric
• Modification of the side of the race
• Training Rotine for the guide and for
the athlete

62. Guide's Support

63. The influence of collective behaviour on pacing in
endurance competitions
Andrew Renfree1*
, Everton Crivoi do Carmo2
, Louise Martin1
, Derek M. Peters1, 3
1
Institute of Sport and Exercise Science, University of Worcester, United Kingdom,
2
Department of Physical Education, Senac University Centre, Brazil, 3
Faculty of Health
and Sport Sciences, University of Agder, Norway
Submitted to Journal:
Frontiers in Physiology
Specialty Section:
Exercise Physiology
ISSN:
1664-042X
Article type:
Perspective Article
Received on:
19 Oct 2015
Accepted on:
23 Nov 2015
Provisional PDF published on:
23 Nov 2015
Frontiers website link:
www.frontiersin.org
Citation:
Renfree A, Crivoi_do_carmo E, Martin L and Peters DM(2015) The influence of collective behaviour on
pacing in endurance competitions. Front. Physiol. 6:373. doi:10.3389/fphys.2015.00373
Copyright statement:
© 2015 Renfree, Crivoi_do_carmo, Martin and Peters. This is an open-access article distributed
under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and
reproduction in other forums is permitted, provided the original author(s) or licensor are credited
and that the original publication in this journal is cited, in accordance with accepted academic
practice. No use, distribution or reproduction is permitted which does not comply with these terms.
This Provisional PDF corresponds to the article as it appeared upon acceptance, after peer-review. Fully formatted PDF
and full text (HTML) versions will be made available soon.
Frontiers in Physiology | www.frontiersin.org
Provisional
The influence of collective behaviour on pacing in endurance1
competitions2
Andrew Renfree1*
, Everton Crivoi do Carmo2
, Louise Martin1
, Derek M Peters1&3
3
1
Institute of Sport & Exercise Science, University of Worcester, United Kingdom4
2
Department of Physical education, Senac University Centre, Brazil5
3
Faculty of Health & Sport Sciences, University of Agder, Kristiansand, Norway6
7
Correspondence: Andrew Renfree, Institute of Sport & Exercise Science, University of8
Worcester, Henwick Grove, Worcester, United Kingdom WR2 6AJ.9
10
a.renfree@worc.ac.uk11
12
Keywords: decision-making, endurance performance, complex systems, sport13
14
Abstract15
A number of theoretical models have been proposed in recent years to explain pacing16
strategies observed in individual competitive endurance events. These have typically related17
to the internal regulatory processes that inform the making of decisions relating to muscular18
work rate. Despite a substantial body of research which has investigated the influence of19
collective group dynamics on individual behaviours in various animal species, this issue has20
not been comprehensively studied in individual athletic events. This is somewhat surprising21
given that athletes often directly compete in close proximity to one another, and that22
collective behaviour has also been observed in other human environments including23
pedestrian interactions and financial market trading. Whilst the reasons for adopting24
collective behaviour are not fully understood, collective behaviour is thought to result from25
individual agents following simple local rules that result in seemingly complex large systems26
that act to confer some biological advantage to the collective as a whole. Although such27
collective behaviours may generally be beneficial, competitive endurance events are28
complicated by the fact that increasing levels of physiological disruption as activity29
progresses may compromise the ability of some individuals to continue to interact with other30
group members. This could result in early fatigue and relative underperformance due to31
suboptimal utilisation of physiological resources by some athletes. Alternatively, engagement32
with a collective behaviour may benefit all due to a reduction in the complexity of decisions33
to be made and a subsequent reduction in cognitive loading and mental fatigue. This paper34
seeks evidence for collective behaviour in previously published analyses of pacing behaviour35
and proposes mechanisms through which it could potentially be either beneficial, or36
detrimental to individual performance. It concludes with suggestions for future research to37
enhance understanding of this phenomenon.38
39
40
41
42
Provisional
1
Institute of Sport & Exercise Science, University of Worcester, United Kingdom4
2
Department of Physical education, Senac University Centre, Brazil5
3
Faculty of Health & Sport Sciences, University of Agder, Kristiansand, Norway6
7
Correspondence: Andrew Renfree, Institute of Sport & Exercise Science, University of8
Worcester, Henwick Grove, Worcester, United Kingdom WR2 6AJ.9
10
a.renfree@worc.ac.uk11
12
Keywords: decision-making, endurance performance, complex systems, sport13
14
Abstract15
A number of theoretical models have been proposed in recent years to explain pacing16
strategies observed in individual competitive endurance events. These have typically related17
to the internal regulatory processes that inform the making of decisions relating to muscular18
work rate. Despite a substantial body of research which has investigated the influence of19
collective group dynamics on individual behaviours in various animal species, this issue has20
not been comprehensively studied in individual athletic events. This is somewhat surprising21
given that athletes often directly compete in close proximity to one another, and that22
collective behaviour has also been observed in other human environments including23
pedestrian interactions and financial market trading. Whilst the reasons for adopting24
collective behaviour are not fully understood, collective behaviour is thought to result from25
individual agents following simple local rules that result in seemingly complex large systems26
that act to confer some biological advantage to the collective as a whole. Although such27
collective behaviours may generally be beneficial, competitive endurance events are28
complicated by the fact that increasing levels of physiological disruption as activity29
progresses may compromise the ability of some individuals to continue to interact with other30
group members. This could result in early fatigue and relative underperformance due to31
suboptimal utilisation of physiological resources by some athletes. Alternatively, engagement32
with a collective behaviour may benefit all due to a reduction in the complexity of decisions33
to be made and a subsequent reduction in cognitive loading and mental fatigue. This paper34
seeks evidence for collective behaviour in previously published analyses of pacing behaviour35
and proposes mechanisms through which it could potentially be either beneficial, or36
detrimental to individual performance. It concludes with suggestions for future research to37
enhance understanding of this phenomenon.38
39
Provisional

65. Tether for the long Distance

66. Running
Economy
Association of the
athlete and guide
performance

67. Running
Economy
Evaluation on the Track
VI SD Guide SD p
HR max 169,78 10,80 169,69 13,10 0,60
VO2 max mL/kg/
min
42,31 7,56 43,30 4,22 0,91
VO2 max L/min 2,85 0,64 3,33 0,37 0,02

68. Running Economy
Running economy is
typically defined as
the energy demanded
for a given velocity of
submaximal running,
and is determined by
measuring the steady-
state consumption of
oxygen (VO2)
Saunders, et al 2004

69. The results show RE is higher
than those found by long
distance athletes using similar
speed (Guglielmo, Coelho, &
Sergio, 2005, Saunders et al.,
2004) and those found using
the higher speeds used in this
study (Guglielmo , Greco,
& Denadai, 2009; Nummela,
Keränen, & Mikkelsson,
2007).

70. Impact in RE
•A d j u s t m e n t s o f
stride length
• Guide needs to
p a s s v e r b a l
information
•Increased demand
of attention to race
with the blind on
treadmill

71. Guide's Demand
The higher O2
consumption
of the guides indicates the
need of more attention to
training with these athletes
as there is higher energy
expenditure during the
training and competition
when performing guidance
of the blind athlete.

72. What about Shorter
Events?

73. Jump Events

74. Rules
Orientation - Caller (11- 2/ 12 - 1)
Real Jump - 11 and 12

75. 3.5m
Linha de Medição
1m.
Talco
Talco
Jump Area

76. Number of Steps
Men Female Men Female
F11/36/37/38/42
/45/46
F11/36/37/38
/42/45/46
F12/13/20/44/47 F12/13/20/44/47
Long Jump 10-16 8-16 12-20 10-16
Triple 6-16 4-12 8-16 6-14
High Jump 2-8 2-6 4-10 2-8

77. • Spacial Orientation
• Running
• Intermediary Jump
• Learning Process
• Motor Strategy

80. VOLUME 8 | Proc3 | 2013 | S671
Performance Analysis Workshop, 2 - 5 April 2013, Alicante, Spain
Biomechanical analysis of the final strides of the
approach and the take-off by visually impaired
class F12 and F13 long jumpers
VASSILIOS PANOUTSAKOPOULOS1, APOSTOLOS THEODOROU1 , MARIANA C.
KOTZAMANIDOU3, EMMANOUIL SKORDILIS2, IRAKLIS A. KOLLIAS1
1 Biomechanics Laboratory, Department of Physical Education & Sports Science, Aristotle University of Thessaloniki,
Thessaloniki, Greece
2 Department of Physical Education & Sports Science, Kapodistrian University of Athens, Athens, Greece
3 Faculty of Health and Human Sciences, Akmi Metropolitan College Thessaloniki, Thessaloniki, Greece
ABSTRACT
Panoutsakopoulos V, Theodorou A, Kotzamanidou MC, Skordilis E, Kollias IA. Biomechanical analysis of
the final strides of the approach and the take-off by visually impaired class F12 and F13 long jumpers. J.
Hum. Sport Exerc. Vol. 8, No. Proc3, pp. S671-S680, 2013. Despite of the level of visual aquity, European
Records in long jumping are greater in class F12 (visual acuity 2/60) than class F13 (visual acuity 6/60)
both in males and females. The aim of the present study was to compare the biomechanical parameters of
the final strides of the approach and the take-off in class F12 and F13 long jumpers. 19 class F12 (males:
13, females: 6) and 12 class F13 (males: 4, females: 8) long jumpers participating in the 2009 International
Blind Sports Association European Championships were recorded using a stationary digital video camera
(sampling frequency: 300 fps). Key biomechanical parameters were extracted with a typical 2D-DLT
kinematical analysis. Differences between groups were investigated using Independent samples t-test.
Results indicated that the official distance was 6.07 m ± 0.55 and 5.52 m ± 0.91 for F12 and F13
respectively (p<.05). Significant differences were also observed concerning the vertical take-off velocity
(F12: 2.8 m/sec, F13: 2.4 m/sec), the support leg's knee flexion (F12: 18.2 deg, F13: 25.2 deg) and the
knee joint flexion velocity (F12: 7.4 rad/sec, F13: 10.2 rad/sec) at the take-off board and the knee maximum
flexion angle at the last stride (F12: 116.8 deg, F13: 125.4 deg). In conclusion, F12 performed better than
F13 because of the more advantageus utilization of the factors defining the vertical component in the long-
jump take-off. Additionally, the different last stride maximum knee flexion angle might imply differences
concerning the mechanics of the placement of the take-off leg. It is possible that factors such as the size
and surface properties of the 1.22 m x 1.00 m chalked take-off area used in F12 competition may contribute
to the differences observed in the study. Key words: 2D-DLT ANALYSIS, STRIDE LENGTH, JOINT
ANGULAR KINEMATICS, VISUAL ACUITY, TECHNIQUE
2 Corresponding author. Department of Physical Education and Sport Science. Kapodistrian University of Athens 41 Ethnikis
E-mail: aptheod@phed.uoa.gr
Performance Analysis Workshop, 2 - 5 April 2013, Alicante, Spain
JOURNAL OF HUMAN SPORT & EXERCISE ISSN 1988-5202
© Faculty of Education. University of Alicante
doi:10.4100/jhse.2013.8.Proc3.13
Proceeding
Panoutsakopoulos et al. / Visually impaired long jump JOURNAL OF HUMAN SPORT & EXERCISE
VOLUME8 | Proc3 | 2013 | S675
Table 1. Comparison of the biomechanical parameters of the approach between the examined class F12
and F13 long jumpers (see text for the abbreviations used)
parameter F12 F13 t p
S3L (m) 1.95 ± 0.16 1.89 ± 0.15 1.015 .318
S2L (m) 2.12 ± 0.22 2.00 ± 0.17 1.688 .102
S1L (m) 1.88 ± 0.09 1.82 ± 0.21 0.892 .388
SF3L (Hz) 4.72 ± 0.34 4.81 ± 0.49 0.635 .531
SF2L (Hz) 4.18 ± 0.44 4.07 ± 0.41 0.727 .474
SF1L (Hz) 4.23 ± 0.30 4.17 ± 0.31 0.601 .553
Vx3L (m/sec) 8.45 ± 0.50 8.15 ± 0.62 1.268 .215
Vx2L (m/sec) 8.82 ± 0.60 8.37 ± 0.90 1.695 .101
Vx1L (m/sec) 8.41 ± 0.49 8.06 ± 0.70 1.677 .104
VxMAX (m/sec) 8.96 ± 0.61 8.49 ± 0.79 1.883 .070
At the examined part of the jump, F12 and F13 athletes were not significantly different (p > .05) concerning
the alterations of HBCM at the instances examined (Figure 1). An average HBCM lowering of 0.05 m ± 0.02
was recorded during the flight phase of 2L. In general, the knee angular kinematics were not different
between groups. However, a detailed look at the support phase of 1L revealed a significant difference (t1,29
= 2.577, p < .05) concerning θkMF (116.8 deg ± 9.0 and 125.4 deg ± 9.1 for F12 and F13, respectively) but
not for θkTD or θkTO (Figure 2). VATD was not different between groups and it progressively increased
during the last two landings of the foot and the final touchdown for the take-off.
Figure 1. Height alteration (ΔH) of the Body Center of Mass between touchdowns (td) and take-offs (to) for
the penultimate stride (2L), last stride (1L) and contact on the take-off board (BO). The lines linking the data
points are not intended to represent the actual BCM trajectory
Panoutsakopoulos et al. / Visually impaired long jump JOURNAL OF HUMAN SPORT & EXERCISE
Figure 2. Mean ensemble curves for the support leg’s knee angle (ϑk) during the support phase of the last
stride. Time is normalized for the comparison. The asterisk indicated statistical significant difference (p <
.05) for the joint angle at its maximum flexion
Table 2 presents the parameters of the take-off phase. F12 had an almost three fold STΤB. With the
exception of VyTO, θkFLEX, and ωkFLEX, no statistical significant differences were noted.
Table 2. Comparison of the biomechanical parameters of the take-off phase between the examined class
F12 and F13 long jumpers (see text for the abbreviations used).
parameter F12 F13 t p
STTB (m) 0.28 ± 0.19 0.10 ± 0.09 3.665 .001**
STD (m) -0.60 ± 0.1 -0.62 ± 0.06 0.908 .371
UATD (m/sec) 2.68 ± 0.59 2.68 ± 0.95 0.011 .991
VxTD (m/sec) 8.20 ± 0.51 7.85 ± 0.71 1.604 .120
VxTO (m/sec) 6.90 ± 0.53 6.54 ± 0.68 1.649 .110
ΔVxBO (m/sec) -1.30 ± 0.46 -1.31 ± 0.44 0.031 .976
VyTD (m/sec) -0.05 ± 0.23 -0.20 ± 0.26 1.734 .094
VyTO (m/sec) 2.81 ± 0.42 2.41 ± 0.46 2.532 .017*
ΔVyBO (m/sec) 2.86 ± 0.42 2.61 ± 0.46 1.568 .128
STO (m) 0.35 ± 0.06 0.35 ± 0.06 0.227 .822

81. Throwing Events

82. • Spacial Orientation
• Running
• Rotation
• Learning Process
• Motor Strategy
• Balance

84. Low Vision can
create a inaccuracies
perceptions with impact in
adjusted of speed

85. Tools
http://paraatletismobrasil.blogspot.com.br

86. You are all welcome
to Santos in ICSEMIS 2016!!!

87. http://www.icsemis2016.org

88. Ciro.winckler@unifesp.br
ciro@cpb.org.br
Thank you!