Labcom SmartGaitLab 

Context

By 2050, the aging population will require a rethinking of early detection policies for frailty using new technological means, so as to delay the admission of seniors to specialized facilities, improve therapeutic education, optimize care pathways, and provide healthcare professionals with tools for monitoring individuals. The societal challenge in this area is to prevent falls, which depend on the frailty of the individual. Based on epidemiological research by Thelot, Pedrono, and Lasbeur, it is emphasized that falls are the leading cause of injury-related hospital admissions in this demographic group, with approximately 30% of people over the age of 65 and 50% of people over the age of 80 experiencing at least one fall per year. These falls not only result in direct physical injuries, such as hip fractures requiring hospitalization and surgery, but also have profound psychological repercussions. The fear of falling again can lead to reduced mobility, social isolation, and a condition known as “post-fall syndrome,” characterized by a loss of confidence and increased anxiety. It is therefore essential to be able to qualify and quantify the risk of falling by assessing frailty, the complexity of which lies in its multifactorial nature. Current solutions rely on the use of various standardized tests (TUG, Tinetti, 6-meter test, WSBA, etc.) administered by healthcare professionals in specialized facilities (hospital departments, nursing home workshops, etc.). When a person is diagnosed as a potential “faller” by a practitioner, they may be referred to a health program, which may involve participating in balance workshops or considering home modifications. At the same time, awareness programs have been developed to educate at-risk populations but their effectiveness depends on the person's participation. One of the main pitfalls of these prevention policies is daily (objective) monitoring. Indeed, as soon as the balance workshop sessions are over, people return to their daily lives. This raises the problem of observing the deterioration/improvement of their condition and early identification of the warning signs of a new fall situation, while respecting privacy. 

Objectives

In this context, Labcom SmartGaitLab aims to improve fall prevention through continuous monitoring of automatically recognized TUG activity. The innovation lies in observing and characterizing the person's test (TUG) using radar imaging, which does not require any specific protocol or action. The advantages are 1) Continuous measurement that ensures long-term monitoring of the test. 2) Identification is carried out in a familiar environment, without stress or stigma, which avoids the introduction of bias. Practitioners frequently observe that patients implement strategies to deceive the measurement in a clinical setting (e.g., by fixing a point to compensate for loss of balance during a TUG test). 3) Quantified observations of real-time changes in balance status, and 4) Increased prevention in the event of negative and significant variations in TUG parameters reported to the healthcare professional.