A Novel Fall Prediction System on Smartphones

The elderly person's life is almost full of hazards. Especially, the fall risk is one of the problems caused by the elderly and the people using prostheses. This paper aims to develop a fall prediction system on smartphones. The proposed App system can record users' gait data sets with which their gait statuses regarding stability and symmetry are analyzed. A high-level fuzzy Petri net model is used to identify the human's actions, including normal action, sport, and fall risk. The experimental results indicate that there are high successful predictions obtained by the proposed App system. Thus, it can easily increase the fall risk prevention.