Abstract

Preventing falls in older people is a real challenge for Public Health. This paper addresses this issue by designing a decision support system which provides a fall risk index. The proposed approach is based on three selected tests (the Timed up and go (TUG), the 30s sit-to-stand and the 4-stage balance tests), which are widely used in the medical sector for assessing mobility and balance of the elderly. During the tests, a video records the older person performing the test and thanks to an image processing algorithm, kinematics and biomechanics parameters are extracted. Based on fuzzy logic, a decision support system fuses all these data and estimates a fall risk index according to the senior's age and gender. It can also assist the Health Professional in making improved medical diagnosis relied on targeted measurements. Simulation results drawing on experimental data of 12 older persons performing the TUG test illustrate the feasibility and the effectiveness of the proposed approach. Objectively assessing the senior's motor functions and the fall risk is possible in less than 10 minutes, at low cost and in an easy and non invasive way.

Highlights

  • United Nations [6] reports that the world’s population aged 65 years and over will increase from 620 million in 2010 to 1.5 billion in 2050, representing 16% of the global population (5% in 1950)

  • Existing solutions generally extract only the relevant parameters but do not analyze the data and let the Health Professional (HP) evaluating the patient’s fall risk from information gathered during the tests. We address this issue by designing a complete solution from data extraction to a decision support system (DSS) which provides a fall risk index (FRI)

  • The first group was composed of 6 persons (69(±3) years) who had not fell in the preceding six months and were able to walk without assistance

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Summary

INTRODUCTION

United Nations [6] reports that the world’s population aged 65 years and over will increase from 620 million in 2010 to 1.5 billion in 2050, representing 16% of the global population (5% in 1950). From a medical point of view, current methods for assessing gait and balance impairments are Tinetti Gait and Balance tests, Berg balance, sit-to-stand and Timed up and go tests [8], [2] These tests are often driven by a subjective observation of the patient by a Health Professional (HP), a physician or a physiotherapist. Most of the kinematics and biomechanics parameters characterizing the motor functions can be collected, in lab or in everyday life, from different technological means such as instrumented surfaces (e.g gait analysis mat,GAITRite ), force platform, treadmill, smart soles in shoes [3], magneto-inertial sensors worn by the elderly [11], video-based system (VICON system ) [7], etc These solutions are either high cost, or non-transportable, or non-secure for elderly, or require time to be carried out (sensors installation and calibration). The patient should maintain each position at least 10 seconds while keeping their eyes open

ASSESSMENT TESTS FOR GAIT AND BALANCE
IMAGE PROCESSING
Detection and tracking module
Gait feature extraction module
Diagnostic of fall risk
CONCLUSIONS
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