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Updated: Apr 4, 2026

Design and Analysis for Fall Detection System Simplification
Published on: April 6, 2020
[Research on the simulation of daily activities and fall risk assessment for the elderly based on a long-strip static
Zhihao Chen1, Xiang Mao1, Zhiqiang Qi1
1Department of Otorhinolaryngology Head and Neck Surgery,Tianjin First Central Hospital,Tianjin,300000,China.
Abstract:
Objective:This study evaluates risk factors influencing fall probability in the elderly based on the analysis of daily activity simulation characteristics on a Linear Static Platform. The findings aim to provide a reference for fall prevention and balance rehabilitation strategies in older adults. Methods:A total of 30 participants aged over 60years who met the inclusion and exclusion criteria were enrolled. Six gait balance tests simulating daily activities were administered using a Linear Static Platform. Subjects were divided into fall and non-fall groups, and regression analysis was used to predict fall risk intensity. Results:The walking test, the rapid turn while walking test, and the forward lunge squat test demonstrated higher accuracy in assessing fall risk. Increased step width(P=0.027, OR=1.99, 95%CI 1.08-3.66), slower walking speed(P=0.020, OR=0.82, 95%CI 0.70-0.97), increased endpoint sway velocity(P=0.031, OR=2.85, 95%CI 1.10-7.39), and higher sway velocity during left and right turns(P=0.040, OR=1.16, 95%CI 1.01-1.30; P=0.037, OR=1.35, 95%CI 1.02-1.80) elevated left and right lunge impact index(P=0.010, OR=1.07, 95%CI 1.02-1.12; P=0.015, OR=1.05, 95%CI 1.01-1.09)were significantly associated with increased fall risk.. Conclusion:Among the six gait balance parameters reflecting daily activities in the elderly, step width, step length, walking speed, and terminal sway velocity may serve as effective indicators for assessing fall risk.

