Engineering Science and Materials Commons^™

Stationary Exercise Classification Using Imus And Deep Learning, Andrew M. Heroy, Zackary Gill, Samantha Sprague, David Stroud, John Santerre

SMU Data Science Review

In the current market, successful fitness tracking devices utilize heart rate and GPS to determine performance. These devices are useful, but don't extensively classify stationary exercise. This paper proposes a modern approach for tuning and investigating optimal neural network types on stationary exercises using Inertial Measurement Units (IMUs). Using three IMUs located on the ankle, waist, and wrist, data is collected to map the body as it moves during the stationary physical activity. A novel five-stage deep learning tuning system was written and deployed to classify user movement as one of three classes: air squats, jumping jacks, and kettlebell swings. …