A Hand Motor Skills Rehabilitation for the Injured Implemented on a Social Robot

Abstract

In this work, we introduce HaReS, a hand rehabilitation system. Our proposal integrates a series of exercises, jointly developed with a foundation for those with motor and cognitive injuries, that are aimed at improving the skills of patients and the adherence to the rehabilitation plan. Our system takes advantage of a low-cost hand-tracking device to provide a quantitative analysis of the performance of the patient. It also integrates a low-cost surface electromyography (sEMG) sensor in order to provide insight about which muscles are being activated while completing the exercises. It is also modular and can be deployed on a social robot. We tested our proposal in two different facilities for rehabilitation with high success. The therapists and patients felt more motivation while using HaReS, which improved the adherence to the rehabilitation plan. In addition, the therapists were able to provide services to more patients than when they used their traditional methodology.

Robotic Platforms for Assistance to People with Disabilities

“…In addition to the previous direct physical assistance solutions, rehabilitation applications can also benefit from sensor-based monitoring systems that have lower costs and thus can be used widely, not only in hospitals but also at home. Gomez-Donoso et al in [6] propose a new software platform that is able to analyze data coming from a low-cost hand-tracking device and a low-cost surface electromyography (sEMG) sensor, in order to verify that a set of rehabilitation exercises is carried out competently. This software is implemented in a social robot in order to improve the engagement of the patients and to improve feedback about the therapy.…”

Study on Flexible sEMG Acquisition System and Its Application in Muscle Strength Evaluation and Hand Rehabilitation

“…Among them, the conductive fillers include carbon-based conductive materials such as graphene or carbon nanotubes, and nanometal-based conductive substrates such as gold, silver, and copper. The main flexible substrates used for sEMG sensors are polydimethylsiloxane (PDMS) and polyurethane (PU) [15][16][17][18][19]. Liu et al [20] investigated flexible skin sEMG sensors using polyimide (PI) substrates and Cu serpentine interconnects in the field of oral recognition.…”