Quantitative Assessment of Motor Function for Patients with a Stroke by an End-Effector Upper Limb Rehabilitation Robot.

Yali Liu,Chong Li,Xinyu Guan,Linhong Ji,Qiuzhi Song

doi:10.1155/2020/5425741

Abstract

With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke. To make the assessment equipment easier to use in clinics and combine the assessment methods with the rehabilitation training process, this paper proposes an anthropomorphic rehabilitation robot based on the basic movement patterns of the upper limb, point-to-point reaching and circle drawing movement. This paper analyzes patients' movement characteristics in aspects of movement range, movement accuracy, and movement smoothness and the output force characteristics by involving 8 patients. Besides, a quantitative assessment method is also proposed based on multivariate fitting methods. It can be concluded that the area of the real trajectory and movement accuracy during circle drawing movement as well as the ratio of force along the sagittal axis in backward point-to-point movement are the unique parameters that are different remarkably between stroke patients and healthy subjects. The fitting function has a high goodness of fit with the Fugl-Meyer scores for the upper limb (R2 = 0.91, p = 0.015), which demonstrates that the fitting function can be used to assess patients' upper limb movement function. The indicators are recorded during training movement, and the fitting function can calculate the scores immediately, which makes the functional assessment quantitative and timely. Combining the training process and assessment, the quantitative assessment method will farther expand the application of rehabilitation robots.

Highlights

Stroke is one common disease caused by abnormal blood supply, about 15% hemorrhagic and 85% ischemic blood [1]
The accuracy of movement was described by the movement average distance during forward point-to-point dispaverage forward movement (FWM), backward point-to-point dispaverage backward movement (BWM), and circle drawing movement dispaverage AC and Rdispc
The black solid line was the average value among the subjects, and the gray-shaded area was one positive and negative standard deviation

Summary

Introduction

Stroke is one common disease caused by abnormal blood supply, about 15% hemorrhagic and 85% ischemic blood [1]. Once a stroke patient has been in steady state after drug therapy, he/she will receive many rehabilitation trainings to promote recovery and prevent complications [3]. To be clear about the motor function state of patients and make customized training schedules for patients, therapies should make function assessment. Researchers focused on muscle strength assessment [4]. With the increasing cases of stroke patients, therapists and researchers had developed many function assessment scales such as Brunnstrom Scales and Fugl-Meyer Scales [5,6,7]. With rehabilitation training methods changed by intelligent equipment such as rehabilitation robots, the assessment methods are needed to be improved. To make the assessment methods impersonal and combined with intelligent equipment, it is necessary to develop quantitative methods for motor function assessment

Methods

Results

Conclusion