Rehabilitative training system based on a ceiling rail for detecting the intended movement direction of a user

Abstract

Background: Accurate detection of the intended movement direction of a patient plays an important role in the development of a training system for gait rehabilitation and enables to increase the effect of gait rehabilitation training.

Objective: This study investigated the detection of the intended movement of a user to operate a ceiling rail-based rehabilitative training system with accurate timing.

Methods: To detect the movement direction intention of a user, two potentiometers were used to measure the movement direction in the anterior, posterior, and left and right directions of the user when operating the driving motor of the rehabilitative training system. A simple test mock-up with two potentiometers was fabricated, and the experiments were conducted to determine the effect of the direction of movement on the measured values of potentiometers. A direction measurement algorithm was developed to control the driving motor of the rail-based gait rehabilitative training system.

Results: The intended movement direction of the user could be predicted for eight directions by combining the "positive value, 0, negative value" of each measured value of the two potentiometers. Further, the developed algorithm was effectively used to control the driving function to assist the walking, sitting-standing, and climbing up-down the step activities in daily life.

Conclusions: The movement intention detection function for users developed in this paper can be used to effectively control a rehabilitative training system for patients with hemiplegia to improve gait movement and posture balance, thereby improving their function of activities of daily living.

Keywords: Intended motion direction; gait rehabilitation; rail-based rehabilitative training system.

Figure 1.

Design concept of the gait rehabilitation system.

Figure 2.

Design of motion detection part using two potentiometers.

Figure 3.

Wire angle simulation according to the gait motion.

Figure 4.

Test mock-up using two potentiometers.

Figure 5.

LabVIEW program for data acquisition.

Figure 6.

Virtual line for accurate movement of the wire.

Figure 7.

Results of two potentiometers according to eight directions.

Figure 8.

Prediction algorithm for the movement intention of the patient using the results of two potentiometers.

Figure 9.

Apparatus of the gait and sitting motion using the motion detection function of the rehabilitation training system.