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Automated Assessment of Kinesthetic PerformanceSimon Fothergill
Ph.D. student
Digital Technology Group, Computer Laboratory, University of Cambridge
SeSAME Plenary Meeting, 11th February 2010
Automated Assessment of Kinesthetic Performance
• Sense and Optimise.
• Feedback is fundamental pedagogical mechanism.
• Automate to supplement.
• What are they doing? What should they be doing? How?
• Rowing simulators.
Important areas of work
• Capturing Kinetics
• Performance similarity
• Natural expression
• Useful feedback
Capturing Kinetics : Requirements
Dataset
• Real and uncontrived
• Large
• Representative of the performance
• High fidelity
• Synchronised
• Segmented
Data capture system
• Compatible
• Equipment augmentation
• Annotation
• Security
• Portable
• Cheap
• Physically robust
• Extensible platform
Capturing Kinetics : Overview
Capturing Kinetics : Hardware (1)
Sensors
• 3D position of handle
• 3D position of seat
• force applied though handle
• force applied though toes of each foot
Capturing Kinetics : Hardware (2)
Capturing Kinetics : Hardware (2)
Capturing Kinetics : Software
Capturing Kinetics : Operation (1)
ECS (Erg Coordinate System)
• EMCS needs to track handle (1), seat (1) and erg position + orientation (4)
• WMCS currently limited to 4 LEDs
• Use 1 LED as a stationary point on the erg & 2 LEDs on the seat at different points in time
• Use PCA to extract ECS axes
Erg clamped to camera rig to minimise errorTwo LEDS attached to seat
Capturing Kinetics : Operation (2)
Data from one Wii controller IR camera, used in computing correspondance of LEDs between cameras
End LED
Handle LED
Seat LEDs
Server
Triangulation
Stereo calibration
Client
4 x 2D coordinates
4 x 3D coordinates
Erg calibration
Label markers
Transform to ECS
Update ECS if necessary
ECS
Calibrate labeller
Calibrate WMCS(openCV)
Storage
Cal
ibra
tion
Live
ope
ratio
n
Capturing Kinetics : Operation (3)
Server (boathouse) Client
Detect strokes
Log data :Motion + force data, images
Split data into strokes
Update database
Turn on/off camera
Live
ope
ratio
nP
ost s
essi
on
File server (CL)
Create directories
Transmit data
Handle + seat coordinates, handle force, stroke boundaries
Create user videos
Augment and select
Encode videos
Record user code
Data, videos, video metadata
Display on GUI
Create metadata
Capturing Kinetics : Deployment & Evaluation
Technical
• At limit of WMCS range (accuracy and precision)
• WMCS won’t work in bright sunlight
• Hand covering LED on handle
• Correspondence: Unnecessary vigorous rowing upsets algorithms which could be improved (domain specific e.g. scan; generic e.g. epipolar constraints)
• ECS updated infrequently
• More force sensors on heal of feet
• openCV is buggy
General
• Developed a novel and functional system and gained experience of deploying it and what is possible to achieve.
• It enables further useful and convincing work to be done
• Useful dataset, sets a benchmark
Users
• Some people are very frightened about using it, especially as video is taken
• The system has a steep but short learning curve
• Athletes require a very simple interface. They won’t even see half the screen and definitely not read anything.
Supplementary Assistance for Rowing Coaching – SpARC (1)
Application for real-time visual feedback
SpARC : Evaluation Method
Method
• Coach athlete
• Record target performance
• Row with different feedback:
• none,
• real-time kinetics,
• target performance
• under various conditions:
• After 30 minutes
• After 5 weeks
• Race pace
• Fatigued
Participants
• 5 rowers
• 2 professional GB rowing coaches
Performance metrics
• Energy supplied to ergometer
• Approximate efficiency
• Approximate similarity to target
• Approximate consistency
SpARC : Evaluation Results
The mean and standard deviation for the metrics over all the strokes of a session are given. Values are rounded to 3 significant figures. Some data was lost due to a sensor system fault.
Example of how the force performance metrics changes though a session from Expt. 1 for rower 3.
SpARC : Evaluation Results : Does feedback help?
• Statistical significance
• Little/detrimental effect on performance immediately after rowing, (1 case where feedback helps)
• Quite strong correlation after prolonged solo training and during race-pace
• Significant correlation during fatigued rowing
SpARC : Conclusions and Limitations
• Functional application providing real-time feedback on kinetics of a rowers performance when using an ergometer
• System is of some use in helping rowers to maintain a consistently good technique as described by a coach, especially when the athletes are extended absence of their own coach or become fatigued.
• Evaluation dataset is currently small.
• Order of experiments is not varied.
• Performance metrics are only justifiable approximations, although could be included in a biomechanical model of a rowing boat.
Acknowledgements
Andy Hopper,
Rob Harle,
George Colouris,
Brian Jones,
Sean Holden,
Marcelo Pias,
Salman Taherian,
Andy Rice,
Joe Newman,
DTG,
Rainbow group,
Andrew Lewis,
SeSAME,
Computer Laboratory,
Jesus College,
Jesus College Boatclub,
Jesus College BoatClub Trust,
Cantabs boatclub Cambridge,
Peter Lee & James Harris GB rowing
Further information
HCI09 demonstration
MUM09 demonstration
Videolectures.net (MUM09)
ISEA10 paper (submiting)
S+SSPR08 paper
Sourceforge StrideSense
Cambridge University i-Teams
Questions
Thank you for your attention.
Comments and Questions, please!
