Technology in Strength and Conditioning Tracking Lower-Limb Exercises With Wearable Sensors.

Strength and conditioning (S&C) coaches offer expert guidance to help those they work with achieve their personal fitness goals. However, because of 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 individualized 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 5 IMUs, 99% 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 5 common multijoint exercises.

Technology in Strength and Conditioning: Assessing Bodyweight Squat Technique With Wearable Sensors.

O'Reilly, MA, Whelan, DF, Ward, TE, Delahunt, E, and Caulfield, BM. Technology in strength and conditioning: assessing bodyweight squat technique with wearable sensors. J Strength Cond Res 31(8): 2303-2312, 2017-Strength and conditioning (S&C) coaches offer expert guidance to help those they work with achieve their personal fitness goals. However, it is not always practical to operate under the direct supervision of an S&C coach and consequently individuals are often left training without expert oversight. 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 individualized feedback regarding exercise performance. These systems could enable S&C coaches to remotely monitor sessions and help individuals record their workout performance. One aspect of such technologies is the ability to assess exercise technique and detect common deviations from acceptable exercise form. In this study, we investigate this ability in the context of a bodyweight (BW) squat exercise. Inertial measurement units were positioned on the lumbar spine, thighs, and shanks of 77 healthy participants. Participants completed repetitions of BW squats with acceptable form and 5 common deviations from acceptable BW squatting technique. Descriptive features were extracted from the IMU signals for each BW squat repetition, and these were used to train a technique classifier. Acceptable or aberrant BW squat technique can be detected with 98% accuracy, 96% sensitivity, and 99% specificity when using features derived from all 5 IMUs. A single IMU system can also distinguish between acceptable and aberrant BW squat biomechanics with excellent accuracy, sensitivity, and specificity. Detecting exact deviations from acceptable BW squatting technique can be achieved with 80% accuracy using a 5 IMU system and 72% accuracy when using a single IMU positioned on the right shank. These results suggest that IMU-based systems can distinguish between acceptable and aberrant BW squat technique with excellent accuracy with a single IMU system. Identification of exact deviations is also possible but multi-IMU systems outperform single IMU systems.