Principal component analysis to guide the reduce the risk of fall

Abstract

The elderly have poor rehabilitation ability, and are prone to complications after falling, which seriously endangers the physical condition of the elderly. Therefore, it is very important to study the balance ability of the elderly and its influencing factors. We constructed a mathematical model to analyze the data related to the walking of the elderly and proposed suggestions for improving stability. Considering the three aspects of gait, center of gravity and motion, 25 eigenvalues were extracted to evaluate the body balance of the elderly. Then, we constructed a balanced risk assessment system for the elderly. The entropy method is used to calculate the information content of eigenvalues as the basis of weighting. We added the elderly BMI and disease history to the risk assessment system for simulation calculation. Borrowing economic thoughts, constructing a random frontier model based on whether the elderly fall as a dependent variable, comparatively analyzing by gender, and studying the influence of gait and exercise on the balance ability of the elderly. We found that gait and center of gravity have a greater impact on the balance of the elderly, BMI has less influence, and the balance between male and female is quite different. Finally, the model is tested. We analyze the sensitivity of each index of the risk assessment system. The results are in line with expectations and the model has certain applicability.