Innovation

Electric wheelchairs can be a huge improvement on someone’s life and independence. Wheelchairs can reduce caregiver necessity to maybe only a few hours a day. Caregivers are often an expensive but important investment. However, with my project, I can hopefully restore the wheelchair user’s freedom of movement. I am working on putting a simple camera and a powerful processor on the wheelchair to help navigate the user through unfamiliar public areas.

There have been a myriad of ideas like mine, but of the professionals and users I have talked to, none have been implemented. The thought is that most systems are expensive and not covered by insurance, or only used in an academic setting. A survey has indicated that 40% of patients using wheelchairs found it “difficult or impossible” to steer an electric wheelchair and up to half of patients would find it beneficial to have an added navigation system (Fehr et al., 2000). This demonstrates the demand for such a system. Fehr indicated that the focus of research should be technology that focuses on actually being implemented rather than just studied. A literature review in 2012 highlighted the research done on “smart wheelchairs” to date.  Technologies such as infrared, sonar, laser, radar, and physical sensors are combined to help the wheelchair gain awareness of its surroundings (Horn, 2012). These systems are often expensive and must be tied together by a laptop or large computer. In other cases, the user would be constrained to only their home, indoor, or recorded areas. Of course, with the integration of all of these technologies into one package, they could cancel out the others disadvantages. However, the more components in a system, the more complex and expensive it becomes, making it harder to use.

In particular, my research aims at helping people with disabilities navigate down a sidewalk. For some with decreased cognition or motor skills, this may be difficult. The featured image shows an ideal situation in which my idea will work. This can be compared to lane keeping systems used in modern cars. In general, they use normal cameras and processors that analyze lane markings (Yu et al., 2008). These systems are normally limited to highway use because of the consistent lane markings. The output of these systems rarely control the car for the user, this would introduce a control system that may have false readings and steer the car off course. Rather, they have passive alerts and haptic feedback.

My research could be contributed to future wheelchairs in the way individual technologies are now (radar, laser, etc.), and bundled to form a more responsive chair. In addition, any sort of navigation technology that relies on a route, but is not defined by position alone could incorporate this technology. I imagine the future of robots roaming the streets picking up garbage and fixing sidewalks using cameras and other sensors.

References

Fehr L., Langbein, W. E., & Skaar, S. (2000). Adequecy of power wheelchair control interfacees for persons with severe disabilities: A clinical survey. Journal of Rehabilitation Research and Development. 

Horn, O. (2012). Smart Wheelchairs: past and current trends. Systems and Computer Science. http://dx.doi.org/10.1109/IConSCS.2012.6502470

Yu, B., Zhang, W.,  & Cai, Y. (2008). A Lane Departure Warning System based on Machine Vision. IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application. http://dx.doi.org/10.1109/PACIIA.2008.142

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