一種預測失能者日常生活功能之方法

A method for predicting the daily life function of disabled people includes inputting the measurement results of a plurality of rehabilitation assessment indicator sets of a plurality of disabled persons and their corresponding daily life function states into a mechanical learning machine; selecting the variable values of several rehabilitation assessment indicator sets with the best classification performance through the mechanical learning machine; using a supervised mechanical learning algorithm to establish a daily life function state prediction model in cooperation with the corresponding daily life function states. Finally, inputting a test result of the plurality of rehabilitation assessment indicator sets of a new examinee into the daily life function state prediction model, and using the internal calculations of the daily life function state prediction model to obtain a prediction result of the daily life function state.