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Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
Recent advances on motion analysis  in sports
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Recent advances on motion analysis in sports

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  • 1. RECENT ADVANCES ON MOTION ANALYSIS IN SPORTS PUNITA ADAJANIA
  • 2. WHAT IS MOTION ANALYSIS? Modern human movement analysis is the interpretation of computerized data that documents an individual’s upper and lower extremities, pelvis, and trunk motion during movement. The beginning of dynamic calculations of human movement began with Giovanni Borelli during Renaissance.
  • 3. • In the past 25 years, the development and subsequent improvement of electronic technology and computer science has made it easier to analyze human movement. • Sports performance is directly linked to human motion and performance. • So, movement analysis is automatically a part of human performance assessment and analysis. • Today in many sports, sports scientists use movement analysis as a tool to enhance techniques, correct movement errors, assess metabolic costs related to a variety of movements, and aid in rehabilitation.
  • 4. • Modern computerized systems of movement analysis generally consist of placing special markers on the subject that will transmit informative data from their position in space to receiver device or force platforms. • Computer software programs are used to evaluate the collected data and process it. • Movement researchers can determine: abnormal biomechanics, measure deviations from a desired pattern, and assess a variety of biomechanical errors made by an athlete.
  • 5. TYPES OF ANALYSIS: • Temporal (repetitions, timing) • Kinematic (positions, motion) • Kinetic (forces, moments of force) • Direct • Indirect • Electromyography (muscle activation)
  • 6. Temporal Analyses • Quantifies durations of performances in whole (race time) or in part (split times, stride times, stroke rates, etc.) • Instruments include: • stop watches, electronic timers • timing gates • frame-by-frame video analysis
  • 7. Donovan Bailey sets world record (9.835) despite slowest reaction time (0.174) of finalists
  • 8. KINEMATICS • Position, velocity & acceleration • Angular position, velocity & acceleration • Distance travelled • tape measures, electronic sensors. • Linear displacement • point-to-point linear distance and direction • Angular displacement • changes in joint angular orientations from point-to-point.
  • 9. KINEMATICS • Instrumentation includes: • tape measures, electrogoniometers • speed guns, accelerometers • motion capture from video or other imaging devices (cinefilm, TV, infrared, ultrasonic, etc.) • GPS, gyroscopes, wireless sensors
  • 10. KINEMATICS • Cheap to very expensive range. • Cheap yields low information • e.g., stride length, range of motion, distance jumped or speed of object thrown or batted • Expensive yields over-abundance of data • e.g., marker trajectories and their kinematics, segment, joint, and total body linear and angular kinematics, in 1, 2, or 3 dimensions
  • 11. Walking walking Gait Characteristics - Walking a stride length b stance phase, left foot swing phase, left foot step length one gait cycle left foot right foot double-support left foot-strike right toe-off left toe-off right foot-strike single-support time
  • 12. Cheap: Gait Characteristics of Running or Sprinting running/sprinting Cheap: Gait Characteristics of Running or Sprinting a stride length b stance phase, left foot swing phase, left foot left foot right foot step length one gait cycle Notice that running foot- prints are typically on the midline unlike walking when they are on either side flight phase right foot-strike left foot-strike right toe-off left toe-off Stride velocity = stride length / stride time Stride rate = 1 / stride time time
  • 13. Cheap: video analysis of sprinting • Hip locations of last 60 meters of 100-m race • Male 10.03 s • accelerated to 60 m before maximum speed of 12 m/s 100 • Female 11.06 s 70 • accelerated to 70 m before maximum speed of 10 m/s 60 male: 12 m/s 90 80 female: 10 m/s 50 40 5 6 7 8 9 Race time (s) 10 11
  • 14. MODERATE: ACCELEROMETRY • Direct measures such as electro goniometry (for joint angles) or accelerometry are relatively inexpensive but can yield real-time information of selected parts of the body • Accelerometry is particularly useful for evaluating impacts to the body. head form with 9 linear accelero meters to quantify 3D accelerati on Inside head form is a 3D acceleromet er and 3 pairs of linear sensors for 3D angular acceleration
  • 15. Expensive: Gait and Movement Analysis Laboratory • Multiple infrared cameras or infrared markers • Motion capture system • Usually multiple force platforms Subject has 42 reflective markers for 3D tracking of all major body segments and joints
  • 16. KINETICS • Forces or moments of force (torques) • Impulse and momentum (linear and angular) • Mechanical energy (potential and kinetic) • Work (of forces and moments) • Power (of forces and moments)
  • 17. • Two ways of obtaining kinetics: • Direct dynamometry • Use of instruments to directly measure external and internal forces • Indirect dynamometry via inverse dynamics • Indirectly estimate internal forces and moments of force from directly measured kinematics, body segment parameters and externally measured forces Gait laboratory with 10 Motion Analysis cameras and walkway with five force platforms Instron compression tester for force and deformation measures of bones, muscles, ligaments, etc., under load
  • 18. KINETICS: DYNAMOMETRY • Measurement of force, moment of force, or power • Instrumentation includes: • Force transducers • Pressure mapping sensors • Force platforms • Isokinetic • concentric, eccentric, isotonic
  • 19. ELECTROMYOGRAPHY • process of measuring the electrical discharges due to muscle recruitment • only quantifies the active component of muscle, passive component is not recorded • levels are relative to a particular muscle and a particular person therefore need a method to compare muscle/muscle or person/person • not all subjects can perform maximal voluntary contractions (MVCs) to permit normalization • effective way to identify patterns of muscle recruitment
  • 20. EMG: AMPLIFIERS • Types: • cable • cable telemetry • telemetry
  • 21. EMG: ELECTRODES • Types: • surface (safest, painless, best for sports) • fine wire (better for detecting which part of muscle is active) • needle (best for medical)
  • 22. ELECTROMYOGRAPHY • Benefits • identifies whether a particular muscle is active or inactive • can help to identify pre-fatigue and fatigue states • Drawbacks • encumbers the subject • difficult to interpret • cannot identify contribution muscle is making (concentric, eccentric, isometric) • should be recorded with kinematics
  • 23. MOTION ANALYSIS METHODOLGY • Export motion analysis positional data into a numeric computational software such as: Matlab (The Mathworks, Inc.) or  symbolic manipulation software such as Maple (MapleSoft, Inc.) or Mathematica (WolframResearch, Inc.). • An algorithm is used to automatically do the calculations.
  • 24.  software is used to calculate inverse dynamics( computes the net turning effect of all the anatomical structures across a joint) such as  Kintrak , KinTools RT (MotionAnalysis), Vicon BodyBuilder (Vicon), Mathematical Mechanical Systems Pack (Wolfram Research, Inc.), etc
  • 25. SPORTS BIOMECHANICS ANALYSIS PLANES OF MOTION • In sports, body segments are invariably forced to move in different planes of motion. • To gain an accurate assessment of global and relative planes of motion, threedimensional angular rotation and velocity vectors have to be calculated. • This is particularly important for sports such as golf, which place a coaching emphasis on shoulder, hip, arm and shaft planes.
  • 26. SEGMENTAL SEQUENCING • Angular velocity vectors are calculated to determine the segmental sequencing patterns in athletic motion. • A general adherence to the proximal to distal sequencing scheme promotes effective performance in most sports that produce high-end effector velocities, such as in the golf swing, cricket bowling and baseball pitching. • Sequencing patterns are particular to each sport, and may also differentiate between elite and amateur athletes.
  • 27. SUMMATION OF SEGMENTAL VELOCITIES • In the classic kinetic link principle, each succeeding distal segment is activated after the corresponding proximal segment has reached its maximum linear or angular velocity. • the maximum velocity of the proximal segment or joint is added to its corresponding distal segment throughout the kinematic chain.
  • 28. STRETCH-SHORTENING CYCLE ACTIVATION • pre- stretching of muscles increases the strength of the subsequent concentric contraction. • Stretch shortening cycles are activated at various times in sports. • However, there is a distinct phase known as the transition phase in which the stretch shortening cycles of the major power actuating muscles are most strongly activated during eccentric contractions. • Motion analysis techniques need to identify the various stretch shortening cycles that occur in movement patterns.
  • 29. PRACTICAL APPLICATIONS Kicking: • Activation of stretch shortening cycle in terms of thigh flexion, knee flexion, time occurrence of maximum knee flexion and knee flexion angular acceleration • Segmental sequencing in maximal velocity in step kicking. • Causal mechanisms of proximal to distal sequencing in kicking.
  • 30. Golf swing: • Identification of swing plane. • Activation of static stretch shortening cycle. • Major segment velocity contributions in the golf swing.
  • 31. Cricket bowling: • Segmental sequencing of elite fast bowlers • Forward solution model to reduce shoulder counter-rotation in bowlers • Spinal kinetics and lumbar injury in fast bowlers • Bowling legality analysis.
  • 32. Tennis serving: • Identification of violations in segmental sequencing of the tennis serve. • Major segment velocity contributions in serving.
  • 33. Automatic Detection and Analysis of Player Action in Moving Background Sports Video Sequences Haojie Li, Jinhui Tang,, Si Wu, Yongdong Zhang, and Shouxun Lin • This study presents a system for automatically detecting and analyzing complex player actions in moving back- ground sports video sequences, aiming at action-based sports videos indexing and providing kinematic measurements for coach assistance and performance improvement. • Two visual analyzing tools:  motion panorama (360 degrees view) overlay composition (help capture images for a specific layout or design). • Real diving and jump game videos are used to test the proposed system and algorithms, and to show their effectiveness.
  • 34. Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey Akin Avci, Stephan Bosch, Mihai Marin-Perianu, Raluca Marin-Perianu, Paul Havinga • Traditionally, researchers used vision sensors for activity recognition. • With the advancements in micro sensor technology, low-powerwire- less communication and wireless sensor networks(WSNs), inertial sensor systems provide a low-cost, effective and privacy-aware alternative for activity recognition. • The most widely used inertial sensors are accelerometers and gyroscopes. • A gyroscope sensor measures the angular velocity by using the tendency of vibration in the same plane as an object vibrates.
  • 35. • SPORTS AND LEISURE APPLICATIONS: • Body-worn WSNs can also be used for recognition of sportive and leisure activities in order increase the lifestyle quality of people. • Used in cycling, playing football, exercising with a rowing machine, and running both for supervised and unsupervised data. • Besides, Long et al. present a system for computing daily energy expenditure for daily activities and sportive activities such as soccer, volley- ball, badminton, table tennis, etc.
  • 36. Martial Arts • Detection of motion sequences in martial arts is also another application field for WSNs. • Heinz et al. used body-worn accelerometers and gyroscopes for motion sequences in order to increase interaction in videogames of martialarts.
  • 37. CONCLUSION • They surveyed the different approaches for activity recognition using inertial sensors, with a focus on applications from health care, well-being and sports. • As a general observation, they noted that in almost all cases results reported in the literature are obtained by first gathering the sensory information on a central computer and then processing the data offline. • Performing activity recognition online and in a distributed manner (i.e. with each sensor having just a partial view of the overall situation) remains therefore an open research question.
  • 38. Video analysis of trunk and knee motion during non- contact anterior cruciate ligament injury in female athletes: lateral trunk and knee abduction motion are combined components of the injury mechanism • T E Hewett, J S Torg, B P Boden • Background: The combined positioning of the trunk and knee in the coronal and sagittal planes during non-contact anterior cruciate ligament (ACL) injury has not been previously reported. • Hypothesis: During ACL injury female athletes demonstrate greater lateral trunk and knee abduction angles than ACL-injured male athletes and uninjured female athletes. • Design: Cross-section control-cohort design. • Methods: Analyses of still captures from 23 coronal (10 female and 7 male ACL-injured players and 6 female controls) or 28 sagittal plane videos performing similar landing and cutting tasks.
  • 39. • Conclusion: Female athletes landed with greater lateral trunk motion and knee abduction during ACL injury than did male athletes or control females during similar landing and cutting tasks. • Clinical relevance: Lateral trunk and knee abduction motion are important components of the ACL injury mechanism in female athletes as observed from video evidence of ACL injury.
  • 40. Visual Analysis of Time-Motion in Basketball Games Roberto Thero´n and Laura Casares • One of the main features of a basketball coach is the visual memory. • The study aims to facilitate the work of coaches and advance the study of basketball, offering a chance to see and analyze the movements that the players have previously made in the field of play, and their implications. • Other aim was to provide both statistical and kinematic analysis of the data collected for each of players to facilitate monitoring over several physical exercises. • The main data sources are individual wearable Global Positioning System (GPS) devices, that enable the collection of real time data related to the position of each player in the court during the whole match or training exercise.
  • 41. • Time-motion analysis (TMA) is a standard analytical procedure to determine the time and energy invested in an activity for a period of time. • Through this process the various patterns of movement involved in sport situations, such as speeds, durations or distances are collected and tallied. • They obtained valuable information on the use of energy systems, and on specific movement patterns of each sport. • In particular, TMA has been used in rugby, football, hockey and basketball
  • 42. Methods for Time-Motion Analysis There are basically two ways to get data from TMA: • Video systems and GPS devices. • GPS technology has been adapted in recent years to serve as a training tool, improving portability and generating useful data for the athlete (distance travelled, speed, etc.). • Generally it has been used in sports’ training covering long distances, such as walking or cycling. • Athlete’s heart rate can also be monitored.
  • 43. • There are some basic applications of data visualization that are supplied with TMA technologies for different sports. • Example: RealTrack (www.realtrackfootball.com) offers four modules covering 1) the basic plot of heart rate, 2) kinematic data monitoring, 3) calculation of positional relationships between players and their graphic representation and 4) video module that allows browsing the data collected over time.
  • 44. • Especially in football, many similar systems to RealTrack have been developed in the last three or four years. • An approach based on visual analysis would improve the cognitive ability of the athlete or coach to make decisions.
  • 45. Measurement of Normal Lumbar Spine Range of Motion in the College-Aged Turkish Population Using a 3D Ultrasound-Based Motion Analysis System • Christopher Carling , Jonathan Bloomfield, Lee Nelson ,Thomas Reilly • Objectives: The aim of this study was to determine range of motion values of lumbar spine in Turkish people by using 3D motion analysis method. • Patients and Methods: The study included 100 subjects (50 males, 50 females; range 18 to 22 years). • The Zebris® 3D Motion Analysis System was used for the measurement. Lateral bending, flexion, extension, pelvic tilt were evaluated in the measurements.
  • 46. • Conclusion: The normal values of movements of lumbar spine in Turkish people have been determined with 3D motion analysis system. Key words: Range of motion; pelvic tilt; lumbar spine; Turkey.
  • 47. MARKERLESS VISUAL TRACKING AND MOTION ANALYSIS FOR SPORTS MONITORING Julien Pansiot • In the past decade, detailed biomechanical motion analysis has become an important part of athletic training and performance evaluation. • However, most commercially available systems are obtrusive and require complicated experimental setup and dedicated laboratory settings. • This thesis presents a robust real-time vision-based tracking system based on a miniaturized, low-power, autonomous Visual Sensor Network (VSN). • The system is able to provide real-time motion monitoring with on-node processing. • The proposed method is applied to motion tracking of indoor tennis training and performance evaluation.
  • 48. Recent Developments in Human Motion Analysis Liang Wang, Weiming Hu, Tieniu Tan • Visual analysis of human motion is currently one of the most active research topics in computer vision. • Human motion analysis concerns the detection, tracking and recognition of people, and more generally, the understanding of human behaviors, from image sequences involving humans. • This study provides a comprehensive survey of research on computer vision based human motion analysis. • The emphasis is on three major issues involved in a general human motion analysis system, namely human detection, tracking and activity understanding. • Keywords: Human motion analysis; Detection; Tracking; Behavior understanding; Semantic description
  • 49. AN ANALYSIS OF BASKETBALL PLAYERS' MOVEMENTS IN THE SLOVENIAN BASKETBALL LEAGUE PLAY-OFFS USING THE SAGIT TRACKING SYSTEM • Frane Erčulj, Brane Dežman, Goran Vučković, Janez Perš, Matej Perše, Matej Kristan • The main aim of the study was to present the SAGIT measuring system and to establish the covered distance and the average velocity of basketball players' movements by using the aforementioned system. • The SAGIT system is a relatively new technology which is based on computer-vision methods and enables an automated acquisition of data from the video recordings of games.
  • 50. • The system was used to track the movements of 23 basketball players from two teams during three games of the play- offs of the Slovenian National Championship for men. • It was established that during the 40 minutes of the active phase of the game the players covered a distance of 4,404 m on average and that during the passive phase, they covered an additional 1,831 meters. • The players' average velocity of movement during the active phase of the game was 1.86 m/s. • Although the players from one of the teams moved slightly faster and covered a greater distance, the differences between the teams in terms of the average velocity and covered distance were not statistically significant. • Key words: basketball player tracking, computer vision
  • 51. REFERENCES • ADVANCED APPLICATIONS OF MOTION ANALYSIS IN SPORTS BIOMECHANICS René E.D. Ferdinands • Automatic Detection and Analysis of Player Action in Moving Background Sports Video Sequences, Haojie Li, Jinhui Tang, Si Wu, Yongdong Zhang, and Shouxun Lin 2010. • Activity Recognition Using Inertial Sensing for Healthcare, Wellbeing and Sports Applications: A Survey Akin Avci, Stephan Bosch, Mihai Marin-Perianu, Raluca Marin-Perianu, Paul Havinga University of Twente, The Netherlands • MOVEMENT ANALYSIS IN SPORTS AND BASKETBALL, Ilker Yücesir
  • 52. • Video analysis of trunk and knee motion during non- contact anterior cruciate ligament injury in female athletes: lateral trunk and knee abduction motion are combined components of the injury mechanism T E Hewett,J S Torg, B P Boden • Visual Analysis of Time-Motion in Basketball Games, Roberto Thero´n and Laura Casares • Measurement of Normal Lumbar Spine Range of Motion in the CollegeAged Turkish Population Using a 3D Ultrasound-Based Motion Analysis System • Markerless Visual Tracking and Motion Analysis for Sports Monitoring, Julien Pansiot • Recent Developments in Human Motion Analysis ,Liang Wang, Weiming Hu, Tieniu Tan
  • 53. • AN ANALYSIS OF BASKETBALL PLAYERS' MOVEMENTS IN THE SLOVENIAN BASKETBALL LEAGUE PLAY-OFFS USING THE SAGIT TRACKING SYSTEM.
  • 54. THANK YOU

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