Workout: Using a Wearable Sensor to Find, Recognize, and Count Repetitive Exercises

Established: November 22, 2016

Although numerous devices exist to track and share exercise routines based on running and walking, these devices offer limited functionality for strength-training exercises. We introduce a system for automatically tracking repetitive exercises – such as weight training and calisthenics – via an arm-worn inertial sensor. Our goal is to provide real-time and post-workout feedback, with no user-specific training and no intervention during a workout. Toward this end, we address three challenges:

(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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