Assistive locomotion strategies for active lower limb devices

Rehabilitation interventions that assist the patient according to his/her needs are still missing in the literature. This M.Sc. thesis addressed some contributions related to this issue to recover the locomotion of individuals suffering from neurological injuries through the active assistance provided by an Exoskeleton-H2 (Exo-H2). Two locomotion strategies for gait events detection and locomotion mode recognition were designed, implemented and validated. Since the Exo-H2 was still in the developing phase during this thesis, the locomotion strategies implemented for gait events detection and locomotion mode recognition were validated in a humanoid robot and in Exoskeleton-H1. Results showed that the proposed strategies are accurate, robust, and versatile tools. When combined and integrated into the control architecture of Exo-H2, these strategies will assist the impaired locomotion function according to the user's needs, i.e., gait event and movement that is being performed by the patient. These insights comprise the future challenges.