Designing A Rehabilitation-Purposed No-Direct-Contact Collaborative Robotic System For Stroke Patients

Abstract

Different from the traditional rehabilitation methods, rehabilitation robots can provide repetitive and meaningful tasks that make the rehabilitation process smarter and more efficient during upper extremity rehabilitation for stroke patients. Therefore, rehabilitation robots are often used to assist patients during their rehabilitation training. From a robotic system perspective, it needs to sense the user's various needs to provide real-time assistance and allow the user to trust the robot. This means that the system must be able to monitor and process the user's level of fatigue. The analysis of EMG signals is used as a criterion to determine the level of muscle fatigue. At the same time, the degree of intervention that stroke patients receive during the rehabilitation process is also a challenge(Fang et al. 2017). For instance, the current rehabilitation robots often help the user to complete the rehabilitation training by means of end traction, the robot is attached to the user's arm, pulling the arm to complete the training. This approach could reduce muscle fatigue and increase the efficiency of rehabilitation.Even though direct contact and traction have been proven in studies to help patients perform better in rehabilitation, from a general HSI perspective, the degree of direct traction assistance may reduce the patient's sense of independence which affects their cognitive and motor function. This paper proposes a No-Direct-Contact Collaborative (NDCC) robotic-arm system that assists patients with physical game tasks. The NDCC system means that the robotic arm doesn't directly touch and hold the patient's upper limb as traditional robots would, but rather works in a cooperative way to complete the task, picking up and moving objects together with patients when they need. The purpose of the NDCC system is to avoid excessive interference to the patient during rehabilitation training, which is beneficial to the patient's cognitive and motor function recovery. In recent years, there has been a gradual increase in the use of robotic systems to assist in rehabilitation exercises for stroke patients and different kinds of interaction have been proposed. (Janssen et al. 2017) suggested that “interactive, engaging game-based rehabilitation tools, which match the abilities of the participant, could provide variation and attractiveness, thereby facilitating recovery of residual motor and cognitive function.” For instance, HarmonySHR system provides end-traction assistance at different recovery stages to complete rehabilitation exercises. With game elements embedded in rehabilitation systems, older patients are not only more attached to the training process but also can train their cognitive controls that “allow them to interact with our complex environment in a goal-directed manner (Anguera et al.2013)”. Therefore, the robotic arm is a “guide” rather than a “teammate.” In our research, it has been possible to collect and process the user's EMG signal during the task in real-time and convert it to RMS (Root Mean Square), and use Huskylens sensors to enable the robotic arm to track the position of the user's upper limb in real-time. The proposed study will be verified through two types of experiments, including Expert Participation and User Experience Experiments, giving designers a new direction to think about the degree of interaction and intervention between robots and stroke patients. In future studies, feedback from the user's EMG signal data and Patient's Rehabilitation Questionnaire (Fang et al. 2017) will be collected and analyzed. The physiological state of the upper limb will be determined by examining the EMG signal. The Patient's Rehabilitation Questionnaire will also be given to the user, aiming to assess the user's cognitive status and sense of independence under the two different assistance methods.