Experimental Verification of Micro-Doppler Radar Measurements of Fall-Risk-Related Gait Differences for Community-Dwelling Elderly Adults.

Kenshi Saho,Masahiro Fujimoto,Yoshiyuki Kobayashi,Michito Matsumoto

doi:10.3390/s22030930

Abstract

In a previous study, we developed a classification model to detect fall risk for elderly adults with a history of falls (fallers) using micro-Doppler radar (MDR) gait measurements via simulation. The objective was to create daily monitoring systems that can identify elderly people with a high risk of falls. This study aimed to verify the effectiveness of our model by collecting actual MDR data from community-dwelling elderly people. First, MDR gait measurements were performed in a community setting, and the efficient gait parameters for the classification of fallers were extracted. Then, a support vector machine model that was trained and validated using the simulated MDR data was tested for the gait parameters extracted from the actual MDR data. A classification accuracy of 78.8% was achieved for the actual MDR data. The validity of the experimental results was confirmed based on a comparison with the results of our previous simulation study. Thus, the practicality of the faller classification model constructed using the simulated MDR data was verified for the actual MDR data.

Highlights

Falling is a common occurrence in elderly adults, and it is a leading cause of morbidity and disability
As most falls that result in injuries occur during walking [1], daily monitoring systems are required for elderly adults to prevent future falls
We achieved a classification accuracy of 78%, which was better than that of a deep-learning-based model

Summary

Introduction

Falling is a common occurrence in elderly adults, and it is a leading cause of morbidity and disability. As most falls that result in injuries occur during walking [1], daily monitoring systems are required for elderly adults to prevent future falls. For this purpose, a method of assessing fall risk using gait must be developed. Numerous studies have verified that fall risk varies significantly with the gait of different types of people, such as the young, elderly, and those with a history of falling (elderly fallers) [2–4]. The fall risk of elderly fallers is considerably larger than that of healthy elderly people. The early detection of fall risk in elderly adults is essential for reducing and preventing critical accidents due to falling [4]

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Conclusion