Data Acquisition and Control Architecture for Intelligent Robotic Exoskeletons in Rehabilitation

Abstract

Neuromotor function rehabilitation is a process that implies a considerable recovery period, which can be slow, costly, and ineffective. This paper presents an architecture proposal for the development of intelligent robotic exoskeletons to support upper limb rehabilitation, especially in clinical conditions such as hemiparesis, as well as to address the problems described above. A review of the literature is presented, exploring the intelligent systems of control and signal processing in medical robotics, biosignal acquisition and the integration of technologies into this type of exoskeleton. The niches of scientific research are highlighted which allow for the planning of this architecture, such as the design of control strategies focused on the patient’s clinical condition, the proper data acquisition and the establishment of methodologies that lead to the adoption of technology in the health area. It is emphasized that this proposal focuses on the use of new engineering methods and tools, where mechanical, electronic and computational systems are involved, providing advantages in areas such as medicine, health sciences and physiotherapy. Also, this proposal has a high social impact, since it allows the development of tools that help in the rehabilitation processes carried out in developing countries such as Colombia.