<i>MGait</i> : Model-Based Gait Analysis Using Wearable Bend and Inertial Sensors

Movement disorders, such as Parkinson’s disease, affect more than 10 million people worldwide. Gait analysis is a critical step in the diagnosis and rehabilitation of these disorders. Specifically, stride lengths provide valuable insights into gait quality process. However, traditional approaches for estimating length are not suitable continuous daily monitoring since they rely on special mats clinical environments. To address this limitation, article presents novel practical step-length estimation technique using low-power wearable bend inertial sensors. Experimental results show that proposed model estimates with 5.49% mean absolute percentage error provides accurate real-time feedback to user.