(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.
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