ERC-Controller: an Education, Research and Clinical Platform for Wheeled Mobility (University of Pittsburgh)

Hongwu Wang, Candiotti Jorge Luis, Elaine Houston, Chengshiu Chung


Mobility devices are often required by older adults or people with limited lower extremity function, pain, or other clinical conditions to enable them to move about and perform their functional activities independently. Electric powered wheelchair (EPW) controllers have not seen substantial improvement since the introduction of the microprocessor. With an estimated 300,000 EPWs in use in the United States and the population of older adults increasing rapidly, the need for safer control systems for wheeled mobility is a priority. This paper presents in detail the design of an ERC (represent for Education, Research and Clinical) controller for wheeled mobility as well as the potential usage of the platform for education and clinical application. Our design comes out with a single board computer provides the computational power and storage space needed to execute normal operations, complex safety algorithms, and extensive data logging. An array of sensors connects to the computer, providing feedback on velocity, inertia, caster angle, and obstacle range and several slots for expansion if necessary. An enclosure box protects the electronics and faceplates provide connectors for all the sensors and user interfaces for easy accessing. VxWorks, Linux and Windows operating systems have been tested on the platform with all the hardware. Some examples of the usage of the platform for researches, educations and clinics have been described.


Mobility devices are often required by older adults or people with limited lower extremity function, pain, or other clinical conditions to enable them to move about and perform their functional activities independently [1]. In the United States alone there are at least 300,000 electric power wheelchairs (EPWs) in use [2]. With the rapid increase in the senior population, there will be increased demand of EPWs in the future. Given this function, mobility devices and assistive technologies can reduce dependence on personal care assistants and caregivers (Agree, Freedman, Cornman, Wolf, & Marcotte, 2005). Along with the increased demand of EPWs, it is estimated that 18-26% of manual wheelchair users could not safely and independently drive current commercially available EPWs [3]. Meanwhile, there were more than 100,000 accidents were treated in United States emergency departments and tips and falls accounted for 65-80 percent of the accidents [4]. There is a need for more intelligent controllers to allow more people with disabilities to use EPWs independently and safely. However, out of most researches had been conducted on smart control of wheeled mobility, few of them turns out to be a commercial product or clinical tool [5]. The lack of research in the area of mobility device interventions and growing practice of direct-to-consumer marketing by certain mobility device supplier of mobility devices outside of the healthcare setting could lead to a high incidence of poor matching of clients with appropriate equipment [6].

Our goal is to build a new ERC controller that would not only serve as research platform of wheeled mobility, but also serve as an education and clinical tools. The device would have the ability to be used for control research, data collection. Furthermore, the chair would have the ability to be used for undergraduate and graduate classes, as well as for clinicians to evaluate the performance of EPW users like the SmartWheel product [6].


Current EPWs control researches need a platform to implement the algorithms with computational power and sensors; there are few clinical tools to provide objective evidences for clinicians to evaluate the performance of wheeled mobility users. Thus, the goal is to design a control platform for education, research and clinical usage.


The Controller Box

The size of the controller box (8.5”x13”x5”) is made as compact as possible to fit the entire components as well as to be mounted on most EPWs either under the seat or at the back of the seat without significant dimension increase. All connectors in the box are standard and readily available commercially to allow anyone being able to connect to the box without requiring manufacture specialty connectors. Interconnect boards made from a printed circuit board are used to increase the rugged nature of all the connections and to simplify the connection process for education, research, and clinical usage. A high power trough is used to separate the high power from the lower power circuits to ensure safety and ease of using.

Controller box and inside components:

The Controller box and the components inside the box

Figure 1. The Controller box and the components inside the box


The faceplate of the controller box

Figure 2. The faceplate

To increase the ease of use and weather resistance, a faceplate is designed and made to provide a clean interface to the box.


There are some peripheral components are made up of a variety of sensors, which can be added or removed as required for a particular application. The current sensors available are two Drive Wheel Encoders, one Caster Spindle Encoder, one 3 Axis Gyro / 3 Axis Accelerometer, one Infrared Range Finder, one Sonar Range Finder, one Laser Line Striper and one 3-D Camera.


Three operating system (OS) have been installed and tested: VxWorks real time OS, Linux Ubuntu 10.4 and Windows XP. The board support package for VxWorks is installed and tested; drivers for Linux and Windows XP are installed and tested too. All the components are working without problems for all three OS too.


There are almost limitless uses for an open-source wheeled mobility controller in education, research and clinical arenas.


The first generation of the design had been used for the National Science Foundation (NSF) Quality of Life Technology (QoLT) Engineering Research Center (ERC) Research Experiences for Undergraduate (REU) program. Two undergraduate students had been educated and trained to use the control platform. One student was working on the caster encoder mechanical design, reading data from the encoders. Another student was working on using different type of joysticks to control an EPW. The students could easily using the platform to learn how to communicate different devices with computer via serial, analog to digital and digital to analog interfaces. At the same time, by doing research related with wheelchairs, they were more awareness with disabilities issues and importance of communications among users, clinicians, technicians and engineers.


Several researches had been conducted based on the control platform such as model based EPW control; control interface comparison and evaluation; slip detection and traction control; terrain dependent EPW driver assistance system, and personal mobility and manipulation appliance (PerMMA).


A focus group study had been conducted with both wheelchair users and clinicians to explore the problems with current controllers and potential improvement with the ERC controller. Both users and clinicians provided positive feedback to the ERC controller. Eventually this system could become priceless in the clinical arena allowing custom programming of wheelchairs to allow those with severe or complex disabilities to be able to independently control their electric powered wheelchairs more effectively. At the same time, the system could help the clinicians to evaluate the driving performances of wheelchair users and could be used for training purpose.


In conclusion, the ERC controller met all of the project goals outlined at the beginning of the project. The advantages of the ERC controller design over conventional controllers are threefold. Firstly, the feedback to the computer provided by the various sensors will allow the EPW to react to its environment dynamically by modifying the output signal sent to the drive wheel motors. This will make the EPW much safer by allowing the wheelchair to sense and react to its environment with minimal user input. Features such as anti-slip, anti-tip, obstacle detection and avoidance are reactions the EPW can take based on the sensors input. Secondly, the programmability of the controller computer will allow a high degree of customization possibilities for the joystick such as different axis, a larger center dead zone, and damping of user hand tremors. Lastly, the memory storage capability of the computer will allow for extensive data logging of a wide variety of parameters which would allow researchers and clinicians to learn more about how people use their EPW.

Thus, this controller could be used for education aim such as design classes since its rich interface, its readily sensor package as well as available expansions, its flexible software choices. The controller had been successfully demoed to be research platform for EPW related researches and could be extended to other wheeled mobility devices as well as mobile robots. In addition, the controller has been noticed by clinicians with its potential and is being worked on with clinicians to be tested.

For the safety, a wireless kill switch designed for ATVs was purchased. The switch controlled a large power relay which provided power to the entire controller. The wireless kill switch itself was powered by its own dedicated DC/DC converter. This allowed the main controller on/off switch to simply control the power to the DC/DC converter which would then turn on the wireless kill switch, turning on the power relay which would provide power to the rest of the controller.


We’d like to thank our Human Engineering Research Laboratories (HERL) for all the facilities and components support. We’d like to thank the clinicians working at Center of Assistive Technology, University of Pittsburgh for their recommendations and assistances. Special thanks go out to Corey Blauch, the design technician working at HERL to make the box out of SLS machine for us. In addition, Ben Salatin, Garrett Grindle and Juan Vazquez Lopez for their previous work on the controller design and testing. Finally, this would not have been possible without Dr. Rory A Cooper, who gave us this unique opportunity and proved to be dedicated, positive, and wise instructors during the overall design process. Funding for this project was provided by the National Science Foundation, Project EEC 0755184.


1. Agree EM, Freedman VA, Cornman JC, Wolf DA, Marcotte JE, Reconsidering Substitution in Long-Term Care: When Does Assistive Technology Take the Place of Personal Care? Journal of Gerontology: Social Sciences, 60B (5), 272–228.

2. Cooper RA, Cooper R, Boninger ML, Trends and Issues in Wheelchair Technologies, pp. 61-72, Assistive Technology, Vol. 20, No. 2, 2008.

3. Fehr L, Langbein WE, Skaar SB, Adequacy of Power Wheelchair Control Interfaces for Persons with Severe Disabilities: A Clinical Survey, Journal of Rehabilitation Research and Development, 37(3):353-60, 2000.

4. Xiang H, Chany AM, Smith GA, Wheelchair related injuries treated in US emergency departments, Injury Prevention,12, 2006, 8-11.

5. Simpson RC, LoPresti E, Cooper RA, How Many People Would Benefit From a Smart Wheelchair? Journal of Rehabilitation Research and Development, pp. 53-72, Vol. 45, No. 1, 2008.

6. Goodwin J, Oghalai T, Kuo Y, Ottenbacher K, Epidemiology of Medicare Abuse: The Example of Power Wheelchairs R2. J Am Geriatric Soc, 55(2), 221–226, 2007.

7. Cooper RA, SMARTWheel: From Concept to Clinical Practice, Prosthetics and Orthotics International, pp. 198-209, Vol. 33, No. 3, September 2009.

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