Vol. 22, Issue 2 Mobile Stride Length Estimation with Deep Convolutional Neural Networks
Accurate estimation of spatial gait characteristics is critical to assess motor impairments resulting from neurological or musculoskeletal disease. Currently, however, methodological constraints limit clinical applicability of state-of-the-art double integration approaches to gait patterns with a clear zero-velocity phase. We describe a novel approach to stride length estimation that uses deep convolutional neural networks to map stride-specific inertial sensor data to the resulting stride length.
An Emerging Era in the Management of Parkinson’s Disease: Wearable Technologies and the Internet of Things
Wearable technologies connected through the Internet of Things (IoT) platform are revolutionizing patient care delivery. This new technology offers a bridge for the lateralization of the current healthcare system, incorporating patients as important actors in disease management, reducing costs and improving diagnostics and treatment outcomes. Characterized by large individual variability in clinical progression and treatment needs, Parkinson’s disease presents as an excellent model for this paradigm shift.