RESNA 27th International Annual Confence
Application of a Commercial Datalogger to Electric Powered and Manual Wheelchairs of Children
Previous studies of the driving characteristics of manual and power wheelchair users have included only subjects over the age of 17. This study aims to investigate the usage patterns of children wheelchair users ages 6-17 years old. The early data shows that children travel a distance of 990.95 ± 403.29 meters per day. Also, children wheelchair users travel at an average speed of 0.222 ± 0.073 meters per second. Study results appear to reveal that children wheelchair users are less active than adult wheelchair users. More data is needed to solidify these results.
Wheelchair, assistive technology, datalogger, children
When designing wheelchairs, it is important to consider the usage the wheelchair will see over its lifetime. Specifications of batteries, motors, drive components, and frame components could be better quantified based on usage patterns. Until recently, wheelchair user's driving characteristics have not been comprehensively studied. The Human Engineering Research Laboratories (HERL) has successfully developed a datalogging device that is able to record distance traveled, speed, and time of wheelchair usage (1). This device is weather-proof and portable and can be unobtrusively attachable to a power or manual wheelchair.
In initial studies by Cooper (2), analysis of datalogger data has shown that power wheelchair users at the National Veterans Wheelchair Games (NVWG) traveled farther and at greater speeds than community based power wheelchair users in the community setting in Pittsburgh, PA. Analysis also reveals that users of power wheelchairs travel at higher speeds than users of manual wheelchairs, but overall users of both types of wheelchairs travel about the same distance per day (3).
However, these two previous datalogger studies have included only subjects over the age of 17 years old. Including children ages 6-17 years old in the datalogger study would create a well-rounded sample of wheelchair users across the life span. This is necessary to accurately describe the driving characteristics of individuals who use wheelchairs as a means for mobility. There have been no other studies conducted to accurately document the wheelchair usage patterns of children. An early study by Butler (4) reports wheelchair usage, during training to learn to use a power wheelchair, as logged by the parents.
The objective of this study was to use the dataloggers to collect speed, distance, and movement time data from children power and manual wheelchair users. The information collected could then lead to better wheelchair designs by developing specifications for batteries, motors, frames, and drive components. The hypothesis in this study is that younger wheelchair users will drive further and use their wheelchairs more when compared to older people.
The targeted population for subjects in this study is children age 6-17 years old who utilize a powered wheelchair or independently propel a manual wheelchair as their primary source of mobility. Potential subjects are not limited on the basis of diagnosis so that the study will represent a broad wheelchair user population. Data is anticipated from 10 children using power wheelchairs and 10 children using manual wheelchairs. Informed consent documents are to be signed by the child's parent or guardian for permission to have their child participate in the research study.
After informed consent had been obtained, the child's wheelchair was instrumented with the datalogger. A magnet was attached to the tire or wheel hub of the wheelchair and a reed switch was then attached to the frame of the chair opposite to the magnet. While the wheelchair is in motion, a time stamp is recorded by the datalogger each time the magnet passes the reed switch. The datalogger remains on the wheelchair for five to seven days. The participants are reminded to go about their daily activities and disregard the datalogger since it is unobtrusive to the operation of the wheelchair. Data recorded is then analyzed using a custom program written in MATLAB to obtain the distance traveled by the subject and the average speed of travel per one hour increments.
Two children using power wheelchairs have participated in this study to date. The average distance traveled per hour over the study period is shown in Figure 1. The average speed per hour over the study period is shown in Figure 2.
The average child wheelchair user travels 990.95 ± 403.29 meters per day. Children wheelchair users also travel at an average speed of 0.222 ± 0.073 meters per second. The plots show a low amount of activity between the hours of midnight and 8:00 am.
Hoover et al. (3) shows that the average adult power wheelchair user travels 3792 ± 2174 meters per day and travels at an average speed of 0.399 meters per second. Results from this study suggest that children power wheelchair users travel less distance and at slower speeds during the day. In comparing the plots of average distance per hour in adults and children, the children appear to travel shorter distances in the afternoon hours between 2pm and 5pm where adults are fairly constant in traveling distance throughout the afternoon hours. There also appears to be a spike in the distance and speed traveled between 7-8 pm, possibly where the children are getting ready for bedtime. Unlike the adults, the children did not travel any distances between 2-7 am.
Data from the first two children subjects in this study shows that children may be less active than adults, but more data is required. In the future, we hope to enlist up to 18 more children to participate in this study. This early data also does not include children manual wheelchair users.
This study was funded by Rehabilitation Services Administration Training Grant.(DOE H129E990004)
Beth Ann Kaminski,
Human Engineering Research Laboratories,
VA Pittsburgh Healthcare System
7180 Highland Drive Building 4,
2 nd Floor, East Wing, 151R-1
Pittsburgh, PA 15206