Data Logger Development for Wheelchair Mobility Outcomes

Principal Investigator/s: Dan Ding, PhD

Co-Investigator/s: Ronald M. Boninger, MBA; David Boninger, PhD; Rory Cooper, PhD; Songfeng Guo, PhD; Chris Willems, ME

 2005-2006

Independent mobility is a key contributor to the quality of life and social participation of an individual with a physical disability. With decreased mobility, there is usually an associated increased risk of social isolation, unemployment, and other health problems such as obesity, cardiovascular disease, and pressure ulcers. Researchers at the Human Engineering Research Laboratories have developed two generations of wheelchair data loggers. These data loggers have been successfully used to investigate the activity levels of consumers and compare usage among different types of wheelchairs. We have received several requests from research institutions, rehabilitation hospitals and clinics to purchase our second-generation data loggers. The market appeal for wheelchair data loggers has also been confirmed through feedback from users, clinicians, therapists, and wheelchair manufacturers and suppliers. In this proposal, we will further improve both our manual and powered wheelchair data loggers. Improvements will encompass mechanical reliability, electronic updates and software features. It is critical that commercialization of wheelchair data loggers be accelerated so that it can become more readily available as an outcome measure for researchers, clinicians, wheelchair manufacturers and suppliers, as they all strive to understand how wheelchairs or other related interventions affect mobility levels of users, or how mobility levels relate to other medical/physiological symptoms. This enhanced objective understanding facilitated by data loggers will lead to early detection and intervention of mobility-induced problems, quantifiable intervention or prescription evaluation, and justification of wheelchairs provided.

The manual wheelchair data logger was successfully developed as proposed in the proposal. It is approximately 5 centimeters in diameter and 3.8 centimeters in depth.  It is self contained, lightweight and powered by a 1/6D lithium wafer cell battery, which enables the data logger to collect and store data for over three months.  The data logger easily attaches to the spokes of a manual wheelchair using a small aluminum strap and screws (Figure 1); therefore, no modifications are required to be made to the wheelchair.  It measures the rotation of the wheelchair wheel through the use of three reed switches mounted 120 degrees apart on the back of the printed circuit board (Figure 2) and a magnet mounted at the bottom of a pendulum.  The pendulum and magnet combination, which is mounted in the aluminum base, maintains its position due to gravity.  Therefore, whenever the wheelchair wheel exceeds 120 degrees of rotation, one of the reed switches is triggered. As each reed switch is triggered, a date and time stamp of the event to the nearest tenth of a second is recorded. Raw data stored on the flash memory chip of the data logging device were transferred to a personal computer.  The raw data files were then decompressed and analyzed using a custom designed MATLAB program.  The custom code computed the mobility characteristic variables of daily distance, average daily speed and active hours.  In addition, the activity level variables of total accumulated movement time, number of starts/stops per thousand meters, maximum period of continuous activity between consecutive stops, and maximum distance traveled between consecutive stops were also calculated using the custom MATLAB code. The manual wheelchair data loggers were successfully used to collect data from the 39 manual wheelchair users for three weeks and 16 manual wheelchair users for three months in the 25^th National Veteran Wheelchair Games in Minneapolis, Minnesota in June 2005. The data logger was proved easy to mount and take off, and can collect data up to three months.

 A prototype power wheelchair data logger in the form of a trailing wheel as proposed was constructed and tested, but it wasn’t able to meet the design criteria proposed. The major problem was to secure the trailing wheel data logger to a power wheelchair without obstructing the normal driving activities. During the initial test, the data logger fell off the power wheelchair and influence the steering capability of wheelchair to some extent. Therefore, a caster data logger design concept was proposed and prototyped. The electronics is based on the manual wheelchair datalogger. A set of three reed switches, mounted inside the caster hub revolve around a magnet, which is fixed to the stationary axle.  The reed switches are connected to the circuit board and a battery, which also revolve around the axle.  When the magnet passes over one of the reed switches the switch is closed, causing the microcontroller on the circuit board to record the date, time, and switch number. We conducted a three-hour trial and the preliminary results see satisfactory. Removal of the datalogger and replace of the original wheel took less than 15 minutes. A manuscript on the design was submitted to 2006 RESNA conference.

Garrett G. Grindle, Songfeng Guo, and Rory A. Cooper, Fabrication and Feasibility Testing of a Concept Caster Data Logger for Electric Powered, 2006 RESNA conference.

Future work will refine the design of power wheelchair data logger and conduct extensive tests of the manual and power wheelchair data loggers using the double-drum and curb-drop test machines. The focus group for manual wheelchair data logger is scheduled at March 9, 2006 when 5-8 clinician/suppliers will be recruited to test the usability of data loggers. A NIH STTR Phase II proposal on further improvement and commercialization of the data loggers is being planned with our partner Three River Holdings Ltd, and will be submitted by April 1, 2006.