Falls are a health issue that is both common among older adults (affecting 1 in 2 people each year after age 80) and serious due to their traumatic, psychological, and functionally disabling complications. The international literature shows that it is possible to prevent recurrent falls by addressing the risk factors for falls, particularly by combating a sedentary lifestyle and deconditioning through regular standing and mobility exercises as part of a rehabilitation program. As part of France's major national plan to prevent falls among older adults, and at a time when medicine is becoming increasingly personalized, prescribing a digitally assisted self-rehabilitation program for people over 65 following a fall could enable as many people as possible to benefit from rehabilitation that boosts their motivation and reduces the time spent by healthcare professionals, while ensuring high-quality follow-up care.
LNA Santé, in collaboration with the Angers and Nantes University Hospitals, has developed a personalized, digitally assisted fall prevention program (the Stand'hop app) comprising three types of activities: tailored physical exercises, structured lifestyle advice, and an objective measurement of the patient's physical activity. Before moving forward with a larger-scale clinical trial to evaluate the effectiveness of this personalized, digitally assisted fall prevention program, the present study DigiWalk aims to describe changes in walking performance over 7 weeks among older adults who have experienced falls, when the program is used as an adjunct to standard care, compared to changes observed in older adults who have experienced falls and receive only standard care.
Inclusion Criteria:
Exclusion Criteria:
Issam.Bilal@chu-angers.fr02.41.35.68.28 ext. +33
DRCI-Promotion-Interne@chu-angers.fr
Spatio-temporal Parameters of Walking in Patients Hospitalized in Acute Geriatrics
Effectiveness of a Home-Based Multicomponent Exercise Program With Digital Support in Community-Dwelling Older Adults With Falls
Longitudinal Analysis of Gait Variability to Predict Falls in Parkinson's Disease
Study of Static and Dynamic Posturographic Elements Predictive of Falls in the Institutionalized Elderly
Effect of a Foot Muscle Strengthening Program in Mobile Older Adults Adults
The Effectiveness of a Self-managed Digital Exercise Programme to Prevent Falls in Older Community-dwelling People
Gait Parameters Analysis in Post-stroke Patients and in Elderly Fallers
An Innovative Gait Training Program in Immersive Virtual Reality for Healthy Older Adults