Sport Coach: Online activity matching using wireless sensor network.
Master's thesis, University of Twente.
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In this thesis we explore the use of Wireless Sensor Networks to perform
online activity matching for sport coaching applications. The goal
is to find one or more suitable algorithm to match the movement of a
trainer and a trainer and to find spatial and temporal differences. Such
a system can aid the trainer in group lessons where it is difficult for the
trainer to keep track of all the trainees.
In this work we consider fitness like movements such as encountered
in aerobic lessons. We limit ourselves to only one one sensor node on
the trainer and one sensor node on the trainee, but this well extends to
more sensors per trainer and trainee. It also scales well to more trainees
per trainer. We use Sun SPOT as wireless sensor nodes, and extend
the set of sensors to obtain more inertial measurement capabilities. The
accelerometer and gyroscope sensor are used to capture the movements.
The gravity vector is extracted and improved with a Kalman filter using
the accelerometer and gyroscope data. An automatic segmentation
technique is used that examines the movement data for rest and activity
periods and changes in movement direction. The segmentation and
the movement information is communicated with the node of the trainee
where the movements are compared. We choose to use Dynamic Time
Warping (DTW) to perform the spatial and temporal matching of the
movement. Because DTW is computationally intensive, we developed
an optimized technique which we call Fast Incremental Dynamic Time
Warping (FIDTW). From the result of the FIDTW algorithm, feedback
is then generated and provided to the trainee.
We test all the design choices extensively using experiments, and
perform a total system test using different test methods to validate the
taken approach. The single person test methods show that the system
can reliably discriminate spatial and temporal differences, and provide
usefull feedback. The two person test results show that improvements
are possible and that more research is needed to make the system give
|Item Type:||Master's Thesis|
|Research Group:||EWI-PS: Pervasive Systems|
|Deposited On:||16 August 2010|
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