LAUSR

With the current sedentary lifestyle we are living, along with an aging population, there is a noticeable rise in the number of impaired and physically debilitated citizens. Such debilitations require new solutions to aid in the rehabilitation process and lift the burden on healthcare systems, which are already overwhelmed in many developed countries. In this article, we target this problem by introducing the design and implementation of a non-invasive wearable architecture for full gait analysis, enabled by optical fiber Bragg grating sensors. The proposed sensing network provides the necessary tools to simultaneously monitor parameters, including foot plantar pressure, peak muscle activity, and the ankle and knee sagittal range of motion, with high precision, without the need for any synchronization or delay adjustments, between multiple sensors. The integration of the sensor network within an edge-cloud networking architecture is also discussed, which enables remote live monitoring of patients during exercise, in addition to secured storing and further analysis of data, with efficient scheduling of different tasks between the edge and the cloud, based on different levels of privacy and required latency.