Ubiquitous Fall Hazard Identification with Smart Insole
Journal
IEEE Journal of Biomedical and Health Informatics
Journal Volume
25
Journal Issue
7
Pages
2768-2776
Date Issued
2021
Author(s)
Abstract
Falls are leading causes of nonfatal injuries in workplaces which lead to substantial injury and economic consequences. To help avoid fall injuries, safety managers usually need to inspect working areas routinely. However, it is difficult for a limited number of safety managers to inspect fall hazards instantly especially in large workplaces. To address this problem, a novel fall hazard identification method is proposed in this paper which makes it possible for all workers to report the potential hazards automatically. This method is based on the fact that people use different gaits to get across different floor surfaces. Through analyzing gait patterns, potential fall hazards could be identified automatically. In this research, Smart Insole, an insole shaped wearable system for gait analysis, was applied to measure gait patterns for fall hazard identification. Slips and trips are the focus of this study since they are two main causes of falls in workplaces. Five effective gait features were extracted to train a Support Vector Machine (SVM) model for recognizing slip hazard, trip hazard, and safe floor surfaces. Experiment results showed that fall hazards could be recognized with high accuracy (98.1%). ? 2013 IEEE.
Subjects
Activity recognition
gait analysis
slips trips and falls (STF)
smart insole
wearable healthcare
Floors
Gait analysis
Hazardous materials
Managers
Occupational risks
Support vector machines
Different floors
Economic consequences
Hazard identification
Non-fatal injuries
Potential hazards
Safety managers
Slips and trips
Wearable systems
Hazards
article
building
controlled study
gait
human
support vector machine
worker
workplace
falling
prevention and control
shoe
Accidental Falls
Gait
Gait Analysis
Humans
Shoes
Workplace
SDGs
Type
journal article