In the evolving landscape of assistive technology, soft wearable exosuits have emerged as a pivotal innovation, distinguishing themselves from their rigid counterparts, the exoskeletons. Yet, mastering soft structures is not an easy task. Seamlessly coordinating robotic assistance with human motion requires compensating not only for the non-linear behaviors of the device but also correctly interpreting the physiological signals that are part of the main control loop. My presentation will focus on my group’s latest progress over the past five years. I will describe the approaches we have developed to obtain compact, robust, reliable, and efficient exosuits. Emphasis will be placed on illustrating a completely novel approach named “context aware control,” which merges classic control strategies and machine learning, including artificial vision, to optimize the modulation of assistance.
Methods for semi-automated hypothesis generation from scientific literature: an open science approach
The rapid growth of scientific publications makes it difficult to manually review and keep up to date with new research findings. Literature-based discovery (LBD) is a field of artificial intelligence at the intersection of natural language processing and machine...
