This research has been conducted to develop a prevention module of collision and balance lost in electric wheelchairs. Ultrasonic sensors were used for detecting obstacles. Giro and acceleration sensors were used for measuring the tilt angle of wheel chair frame. Kalman filters were employed for filtering high-frequency noise of acceleration sensor and removing zero drift of the Giro sensor. The presence and location of obstacles were detected, and their information was sent to the user smartphone. When the tilt angle of the wheelchair frame exceeded a certain value, a warning signal was set to operate. Raspberry Pi camera module was used to transfer rear view image data to the smartphone to help the driver acknowledge obstacles in the rear side. A DSP processor with high computing performance was necessary to realize a real-time processing of the sensor and image data. Our research showed that a prevention module of collision and balance lost connected to a smartphone can be realized at a considerable low price.

Structural analyses were performed for a movable seat mechanism applied in a new type shower commode wheel chair. The wheel chair has slide rails below the wheel chair seat to help patient move to bed side. The slide rails and seat were modeled for the structural simulation. Experiments were performed to validate simulation results by using strain gage Rosettes. Student t-test was performed to the experimental data, which showed that the stresses obtained from the simulation were not significantly different from those obtained from the experiments. The slide rail structure was found to give a safety factor of 2.4 under 80Kg user weight with ten rollers used for seat support. The safety factor much increased by placing more rollers under the wheel chair seat. Our simulation revealed that rollers installed only in the central and corner regions were used as supports due to the bending deformation of the seat.