Abstract

This work is devoted to the presentation of a Wireless Sensor System implementation for upper limb rehabilitation to function as a complementary system for a patient’s progress supervision during rehabilitation exercises. A cost effective motion capture sensor node composed by a 9 Degrees-of-Freedom (DoF) Inertial Measurement Unit (IMU) is mounted on the patient’s upper limb segments and sends wirelessly the corresponding measured signals to a base station. The sensor orientation and the upper limb individual segments movement in 3-Dimensional (3D) space are derived by processing the sensors’ raw data. For the latter purpose, a biomechanical model which resembles that of a kinematic model of a robotic arm based on the Denavit-Hartenberg (DH) configuration is used to approximate in real time the upper limb movements. The joint angles of the upper limb model are estimated from the extracted sensor node’s orientation angles. The experimental results of a human performing common rehabilitation exercises using the proposed motion capture sensor node are compared with the ones using an off-the-shelf sensor. This comparison results to very low error rates with the root mean square error (RMSE) being about 0.02 m.

Highlights

  • In the present paper the forward kinematics were extracted for the human upper limb, which was designed as a kinematic chain consisting of three joints, namely, the shoulder, the elbow and the wrist and 7 DoFs

  • An upper limb kinematic model that resembles a robotic arm with rigid links is proposed

  • It is formed as a 7 DoF kinematic chain, while the Denavit-Hartenberg configuration is adopted to describe this model

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Summary

Introduction

The patient is expected to perform sets of physical exercises and activities under the supervision of the corresponding medical staff, in order to achieve a functioning level of body segments, which may have been impaired by an accident or a surgery, or as a consequence of pathological conditions, such as in case of a stroke. The objective in these circumstances is to decrease the recovery time for the patient by rehabilitating his physiological motor capabilities.

Types of Upper Limb Rehabilitation Systems
WSN-Based Upper Limb Rehabilitation Systems
Upper Limb Motion Reconstruction
Motivation & Objectives
Upper Limb Kinematic Model
Range of Motion for the Upper Limb Model
Dh Parameters of Upper Limb Model
DoFs Angles Estimation
Sensor Fusion and Orientation Estimation
Estimation of the Shoulder Joint Angles
Estimation of the Elbow Joint Angles
Estimation of the Wrist Joint Angles
Motion Sensors
Elbow Joint Flexion-Extension Exercise
Shoulder Joint Abduction-Adduction Exercise
Wrist Joint Flexion-Extension Exercise
Findings
Discussion
Conclusions
Full Text
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