ABSTRACT

Manual wheelchair users are at high risk of developing pressure ulcers. To try to prevent the development of PU, clinicians recommend regular weight shifts, but MWU don’t always follow this advice. In order to develop a useful smartphone application to coach MWU to do effective pressure reliefs, it is necessary to accurately identify seating postures.

This paper briefly describes a sensor system for tracking MWU seated center of pressure, and presents representative data obtained from the sensor system while study subjects did forward, leftward, and rightward leans , as well as lifting off the chair. With appropriate filtering, this data can be combined with clinical expertise to produce an artificial intelligence algorithm that identifies types of PR maneuvers, and provides a logical way to quantify their degree. Incorporating the algorithm into a coaching app can continue the education for MWU on how to do effective PR beyond the acute rehab phase, and lead to positive pressure relief behaviors that will reduce the incidence of sitting related pressure ulcers.