Access Type

Open Access Dissertation

Date of Award

January 2014

Degree Type

Dissertation

Degree Name

Ph.D.

Department

Electrical and Computer Engineering

First Advisor

Abhilash K. Pandya

Abstract

This research was conducted to assist with functional tasks for a targeted group of individuals with spinal cord injury (SCI); with C5 to C7 level of injury relating to upper extremity movement. The specific population was selected as the existing technology was either too expensive, too bulky or was unable to address their needs in regards to upper extremity mobility. In addition, no platforms allowed multimodal control options for customization or provided a methodology for this crucial evaluation. The motivation of this research was to provide a methodology for selecting the appropriate control of an assistive device based on the range of basic human movements that were possible by the population under consideration (button pushing, lever sliding, and speech). The main idea was to create an evaluation methodology based on a user platform with multiple modes of control. The controls were developed such that they would allow operation of the device with respect to the capabilities of SCI participants.

Engineering advancements have taken assistive robotics to new dimensions. Technologies such as wheelchair robotics and myo-electronically controlled systems have opened up a wide range of new applications to assist people with physical disabilities. Similarly exo-skeletal limbs and body suits have provided new foundations from which technologies can aid function. Unfortunately, these devices have issues of usability, weight, and discomfort with donning. The Smart Assistive Reacher Arm (SARA) system, developed in this research, is a voice-activated, lightweight, mobile device that can be used when needed. SARA was built to help overcome daily reach challenges faced by individuals with limited arm and hand movement capability, such as people with cervical level 5-6 (C5-6) SCI. The functional reacher arm with voice control can be beneficial for this population. Comparison study with healthy participants and an SCI participant shows that, when using SARA, a person with SCI can perform simple reach and grasp tasks independently, without someone else's help. This suggests that the interface is intuitive and can be easily used to a high-level of proficiency by a SCI individual.

Using SARA, an Exo-Skeletal Assistive Robotic Arm (eSARA) was designed and built. eSARA platform had multiple modes of control namely, voice (ballistic mode with no extremity movement), button (ballistic mode with minor extremity movement) and slider (continuous mode with major extremity movement). eSARA was able to extend a total of 7 inches from its original position. The platform also provided lift assist for users that can potentially enable them to lift up to 20lbs.The purpose of eSARA was to build a platform that could help design a methodology to select the modality for a specific level of SCI injury or capability.

The eSARA platform's Human Machine Interface (HMI) was based on two experiments `Fine movement experiment' and `Gross movement experiment'. These experiments tested the reaching, grasping and lifting ability of the platform. Two groups of healthy young adults were selected to perform the experiment. The first group, 12 healthy participants, had no movement restrictions. The second group, 6 Occupational Therapy students, that could mimic restrictions similar to those of a level 5-6 SCI individual. The experiment was also conducted by an SCI individual. The results of the 2 groups from both the experiments were compared with the results of the SCI participant. It was found that the SCI participant's time performance to finish the tasks was comparable to the average of the healthy participants.

It was concluded that the developed methodology and platforms could be used to evaluate the control modes needed in order to customize the system to the capabilities of SCI individual. . These platforms can be tested for a broader range of participants including participants with arthritis, recovering from paralysis and seniors with movement issues.

Included in

Robotics Commons

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