SoftAct

Funded by: Ministry of Affari Esteri e della Cooperazione Internazionale
NUMBER-PGR00807

Prevention of falls: a synergic soft exoskeleton with integrated muscle and brain biosignals to minimize gait instability in the elderly
PI: Alessandra Del Felice

Gait performance and posture can be affected by aging. Falls due to lack of stability is one of the most common causes of injury and disability in the elderly. Multiple causative factors concur; older people are usually not aware of these risks and they do not report them to physicians. As a consequence, prevention of falling is often overlooked and technological solutions are proposed to detect the fall itself. The aim of this 3-y project is to develop a novel neuromuscular controller for a soft lower-limb exoskeleton to detect the loss of stability during walking or standing and apply the proper torques to restore stability. The project is structured on two consecutive phases: an offline acquisition of kinematic, cerebral activity and muscular signal during over-ground gait and during postural adjustments induced by an instrumented balance platform, and an online implementation of the closed-loop controller for detecting and preventing falls. At the end of the project, we expect to deliver a robust and efficient system, that should increase the stability and the safety of elderlies, with possible commercial exploitation.
Poster presented at The Hamlyn Symposium on Medical Robotics 2019 (London, UK).