Classification of lower limb rehabilitation exercises with multiple and individual inertial measurement units

Straight leg raise rehabilitation exercises (for both lying and seated position) for lower limb injuries play a critical role in terms of stress on joints after the injury. The primary objective paper is to find how accurately efficiently single two IMU sensor-based system could classify SSLR (Seated straight raise) LSLR (Lying using machine learning. Inertial Measurement Units (IMUs) that include accelerometer gyroscope were calibrated tested, individual combined, classified seating as well exercise different demanded personalities. Individual IMUs achieved about 96 % accuracy binary classification. However, combined (two) 96.8 accuracy. merits proposed based sensor are it easy install, cost effective very useful telemedical operations pandemic situations like COVID19. On basis these results, be concluded approximately 96% able identify performing exercise.