(1) Segmenting exercise from intermittent non-exercise periods
(2) Recognizing which exercise is being performed
(3) Counting repetitions
We present cross-validation results on our training data and results from a study assessing the final system, totaling 114 participants over 146 sessions. We achieve precision and recall greater than 95% in identifying exercise periods, recognition of 99%, 98%, and 96% on circuits of 4, 7, and 13 exercises respectively, and counting that is accurate to ±1 repetition 93% of the time. These results suggest that our approach enables a new category of fitness tracking devices.
The automatic counting portion of this work shipped as part of the Microsoft Band.
Data from this project is available at the Microsoft Research Open Data Repository.
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