Strength and conditioning (S&C) coaches offer expert guidance to help those they work with achieve their personal fitness goals. However, due to cost and availability issues, individuals are often left training without expert supervision. Recent developments in inertial measurement units (IMUs) and mobile computing platforms have allowed for the possibility of unobtrusive motion tracking systems and the provision of real time individualised feedback regarding exercise performance. These systems could enable S&C coaches to remotely monitor sessions and help gym users record workouts. One component of these IMU systems is the ability to identify the exercises completed. In this study, IMUs were positioned on the lumbar spine, thighs and shanks on 82 healthy participants. Participants completed 10 repetitions of the squat, lunge, single leg squat, deadlift and tuck jump with acceptable form. Descriptive features were extracted from the IMU signals for each repetition of each exercise and these were used to train an exercise classifier. The exercises were detected with 99% accuracy when using signals from all five IMUs, 98% when using signals from the thigh and lumbar IMUs and 98% with just a single IMU on the shank. These results indicate that a single IMU can accurately distinguish between five common multi-joint exercises.
National University of Ireland Maynooth ->