목적 : 본 연구는 상지운동장애를 가진 아동에게 상지재활로봇치료가 기능회복에 미치는 영향에 대하여 문 헌을 고찰하고 그 효과를 메타분석을 통해 알아보고자 한다. 연구방법 : 국외 검색엔진을 이용하여 자료를 수집하였다. 주요 검색용어는 ‘Upper extremity’, ‘Robotic’, ‘Rehabilitation’, ‘Child’ 등이 사용되었다. 2010년 1월부터 2020년 12월까지 게재된 연구 중 선정기준에 적합한 논문 22편을 선정하여 분석하였다. 결과 : 연구의 질적 분석 및 계량적 메타분석, 상지 재활로봇의 종류와 로봇 치료 전·후로 사용된 측정도 구를 분석하였다. 상지운동장애를 가진 아동에게 상지재활로봇치료의 효과는 큰 효과크기로 나타났으며, 통계적으로 유의하였다(p < .05). 결론 : 상지운동장애를 가진 아동에게 상지재활로봇의 치료는 로봇의 종류와 상관없이 기능회복에 효과적 임을 알 수 있었다. 이것은 임상에서 아동에게 상지 재활치료를 위한 치료방법으로 객관적인 근거가 될 수 있을 것이다.

NREX, an upper limb exoskeleton robot, was developed at the National Rehabilitation Center to assist in the upper limb movements of subjects with weak muscular strength and control ability of the upper limbs, such as those with hemiplegia. For the free movement of the shoulder of the existing NREX, three passive joints were added, which improved its wearability. For the flexion/extension movement and internal/external rotation movement of the shoulder of the robot, the ball lock pin is used to fix or rotate the passive joint. The force and torque between a human and a robot were measured and analyzed in a reaching movement for four targets using a six-axis force/torque sensor for 20 able-bodied subjects. The addition of two passive joints to allow the user to rotate the shoulder can confirm that the average force of the upper limb must be 31.6% less and the torque must be 48.9% less to perform the movement related to the axis of rotation.

This paper presents a force control based on the observer without taking any force or torque measurement from the robot which allows realizing more stable and robust human robot interaction for the developed multi-functional upper limb rehabilitation robot. The robot has four functional training modes which can be classified by the human robot interaction types: passive, active, assistive, and resistive mode. The proposed observer consists of internal disturbance observer and external force observer for distinctive performance evaluation. Since four training modes can be quantitatively identified as impedance variation, position-based impedance control with feedback and feedforward controller was applied to the assistive training mode. The results showed that the proposed sensorless observer estimated cleaner and more accurate force compared to the force sensor and the impedance controller embedded with the proposed observer completed the assistive training mode safely and properly.