Rehabilitation Exercises Recognition Based on Acceleration Signals
Date Issued
2007
Date
2007
Author(s)
Pan, Chao-Wei
DOI
en-US
Abstract
Rehabilitation exercises after breast cancer surgery can help
prevent post-operation complications. This thesis adopts activity recognition technique to identify and record patients' rehabilitative exercises. This information helps doctors monitor the patients' conditions in follow-up visits.
This thesis presents a activity recognition system based on
continuous hidden Markov models. Accelerometers are used to capture the upper body movements when patients do rehabilitation. Four different representative features, mean, energy, entropy, and correlation, are extracted from signals. The recognition rate of exercises is about 98%. The performance of the recognizer is also evaluated in both user dependent and user independent cases.
Subjects
加速度
動作辨識
復健
Acceleration
Activity Recognition
Rehabilitation
SDGs
Type
thesis
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