The purpose of this study is to evaluate the feasibility and efficacy of a smart airbag system that detects and mitigates fall-related impact in individuals with high fall risk.
The purpose of this study is to evaluate the feasibility and efficacy of a smart airbag system that detects and mitigates fall-related impact in individuals with high fall risk. The specific aims of this study are: 1. To evaluate and optimize pre-fall detection algorithms and the usability of the smart airbag system for fall mitigation in individuals with high fall risk. 2. To evaluate the efficacy of the smart airbag system in mitigating real-world falls and its effect on community mobility in individuals with high fall risk. The investigators hypothesize that a soft, smart airbag system that uses advanced machine learning algorithms can accurately detect and mitigate falls, deploying appropriately to reduce hip fractures due to falls. The investigators also expect that wearing this device will decrease fear of falling and thus increase community mobility and social interaction.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DEVICE_FEASIBILITY
Masking
NONE
Enrollment
200
Both versions of Airbags features different number of IMU sensors. Participant's will be randomly assigned one of the two versions. The algorithms developed in this project will help the researcher to identify the optimal performance (sensitivity and specificity values for detecting falls). Based on this information the research team will be able to choose a version for home/community deployment portion of the study. Based on the performance of the airbags in detecting true positives (falls) and true negatives (non-falls) accurately one of the airbags will be used in community deployment phase of the study.
Shirley Ryan AbilityLab
Chicago, Illinois, United States
Pre-fall classification performance
Derivation(s) from a confusion matrix
Time frame: 1 year
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