Date of Award

Spring 2012

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Biomedical Engineering - (Ph.D.)

Department

Biomedical Engineering

First Advisor

Sergei Adamovich

Second Advisor

Richard A. Foulds

Third Advisor

Alma S. Merians

Fourth Advisor

Eugene Tunik

Fifth Advisor

William Corson Hunter

Abstract

Stroke affects more than 700,000 people annually in the U.S. It is the leading cause of major disability. Recovery of upper extremity function remains particularly resistant to intervention, with 80% to 95% of persons demonstrating residual upper extremity impairments lasting beyond six months after the stroke. The NJIT Robot Assistive Virtual Rehabilitation (NJIT-RAVR) system has been developed to study optimal strategies for rehabilitation of arm and hand function. Several commercial available devices, such as HapticMaster™, Cyberglove™, trakSTAR™ and Cybergrasp™, have been integrated and 11 simulations were developed to allow users to interact with virtual environments. Visual interfaces used in these simulations were programmed either in Virtools or in C++ using the Open GL library. Stereoscopic glasses were used to enhance depth perception and to present movement targets to the subjects in a 3-dimensional stereo working space. Adaptive online and offline algorithms were developed that provided appropriate task difficulty to optimize the outcomes.

A pilot study was done on four stroke patients and two children with cerebral palsy to demonstrate the usability of this robot-assisted VR system. The RAVR system performed well without unexpected glitches during two weeks of training. No subjects experienced side effects such as dizziness, nausea or disorientation while interacting with the virtual environment. Each subject was able to finish the training, either with or without robotic adaptive assistance.

To investigate optimal therapeutic approaches, forty stroke subjects were randomly assigned to two groups: Hand and Arm training Together (HAT) and Hand and Arm training Separately (HAS). Each group was trained in similar virtual reality training environments for three hours a day, four days a week for two weeks. In addition, twelve stroke subjects participated as a control group. They received conventional rehabilitation training of similar intensity and duration as the HAS and HAT groups. Clinical outcome measurements included the Jebsen Test of Hand Function, the Wolf Motor Function Test, and the ReachGrasp test. Secondary outcome measurements were calculated from kinematic and kinetic data collected during training in real time at 100 Hz. Both HAS and HAT groups showed significant improvement in clinical and kinematic outcome measurements. Clinical improvement compared favorably to the randomized clinical trials reported in the literature. However, there was no significant improvement difference between the two groups. Subjects from the control group improved in clinical measurements and in the ReachGrasp test. Compared to the control group, the ReachGrasp test showed a larger increase in movement speed during reaching and in the efficiency of lifting an object from the table in the combined HAS and HAT group.

The NJIT-RAVR system was further modified to address the needs of children with hemiplegia due to Cerebral Palsy. Thirteen children with cerebral palsy participated in the total of nine sessions of one hour training that lasted for three weeks. Nine of the children were trained using the RAVR system alone, and another four had training with the combined Constraint-Induced Movement therapy and RAVR therapy. As a group, the children demonstrated improved performance across measurements of the Arm Range of Motion (AROM), motor function, kinematics and motor control. While subjects' responses to the games varied, they performed each simulation while maintaining attention sufficient to improve in both robotic task performance and in measures of motor function.

Share

COinS