An Embedded Risk Prediction System for Wheelchair Safety Driving
Development of intelligent wheelchairs can increase mobility and independence of impaired individuals. As there exist dangerous driving risks such as improper driving postures, moving too fast or on rough road, it is useful to monitor the wheelchair user’s driving conditions and, particularly, predict potential driving risks. This paper proposes a risk prediction system for the wheelchair safety driving. A novel designed smart cushion is used to evaluate dangerous drivings risks. Our cushion is able to better combine the pressure sensors and accelerometer and it can detect sitting postures, wheelchair accelerations, and terrain conditions. In addition, we propose a prediction system to monitor the wheelchair driving status. Features are extracted and a fuzzy inference system is used to quantify the dangerous driving risks. Warnings or intervention control strategies will be trigged to increase wheelchair driving safety.
KeywordsSmart cushion Pressure sensor Accelerometer Wheelchair safety driving Risk prediction Fuzzy inference system
The research is financially supported by China-Italy S&T Cooperation project “Smart Personal Mobility Systems for Human Disabilities in Future Smart Cities” (China-side Project ID: 2015DFG12210, Italy-side Project ID: CN13MO7), and the National Natural Science Foundation of China (Grant Nos: 61571336 and 61502360). This work has been also carried out under the framework of INTER-IoT, Research and Innovation action—Horizon 2020 European Project, Grant Agreement #687283, financed by the EU.
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