Immersive Virtual Reality Using a Head Mounted Display and Modelling Using Machine Learning Algorithms to Assess Risk of Falling in the Elderly and Patients With Parkinson's Disease.
Trial Snapshot
- Phase
- Not Applicable
- Sponsor
- Enrollment
- 116
- Locations
- 2
- Primary Endpoint
- Timed Up & Go in virtual reality (VR)
Study Overview
Brief Summary
The process of ageing affects at the same time the sensory, cognitive and driving functions. Furthermore, ageing is often accompanied by pathologies increasing the effects of the senescence. An ageing subject will have then more difficulties in maintaining balance control and will have a falling risk with sometimes critical consequences for the quality of life.
The risk of fall is estimated by tests at the same time of current life and with scores of sensitivity and specificity which must be improved. In a review including 25 studies (2 314 subjects), show a sensitivity of 32 % and a specificity of 73 % on the test "Timed Up and Go" (TUG) with a threshold at 13.5 seconds.
In addition, the fall occurs in a multifactorial context when a subject interacts with his environment. It therefore seems essential to test balance control or falling risk of individuals as close as possible to the situations of daily life. This research, based on the TUG, will aim to assess the neuro-psycho-motor behavior of subjects in situations close to daily life using a Virtual Reality (VR) and Human Metrology platform.
The results could ultimately lead to increased sensitivity and specificity in assessing the risk of falling with a TUG performed in VR, compared to the classic TUG, which is commonly used by healthcare professionals and thus allow for earlier or more appropriate management of the subject in preventing the risk of falling. This could allow healthcare professionals to better understand the risk of falling and thus guide medical recommendations and prescribing, particularly in terms of appropriate physical activity programs.
Study Design
- Study Type
- Interventional
- Allocation
- Non Randomized
- Intervention Model
- Parallel
- Primary Purpose
- Prevention
- Masking
- None
Eligibility Criteria
- Ages
- 65 Years to 80 Years (Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Non-faller elderly
- •Male and female
- •Age between 65 and 80 years old
- •Autonomous
- •Reporting no fall in the last 12 months
- •Fallers elderly
- •Male and female
- •Age between 65 and 80 years old
- •Autonomous
- •Reporting at least 1 fall in the last 12 months
- •Non-faller Patients with Parkinson's disease
- •Male and female
- •Age between 65 and 80 years old
- •Autonomous
- •Reporting no fall in the last 12 months
- •Dopa-sensitive
- •In ON period of treatment of Parkinson's disease
Exclusion Criteria
- •Hearing loss preventing understanding of the instructions and listening to the sound message
- •Visual acuity not compatible with the test procedure in virtual reality
- •Inability to move without assistance
- •Not understanding written and oral French, illiteracy, dementia
- •Treatment including psychotropic drugs
- •Person in emergency situation,
- •Major person subject to a legal protection measure (guardianship, curator, safeguard of justice),
- •Major person unable to express his consent,
- •Hospitalized person,
- •Person deprived of liberty by a judicial or administrative decision, the persons being the object of psychiatric care by virtue of articles L. 3212-1 and L. 3213-1 of the french Code of Public Health,
- •Person likely, in the opinion of the investigator, not to be cooperating or respectful of the obligations inherent to participation in the study
- •Person with a predisposition to epilepsy
Arms & Interventions
Non falling elderly
Intervention: Metrology of motor behavior (Other)
Falling elderly
Intervention: Metrology of motor behavior (Other)
Non falling patients with Parkinson's disease
Intervention: Metrology of motor behavior (Other)
Outcomes
Primary Outcomes
Timed Up & Go in virtual reality (VR)
Time Frame: Baseline
Time
Secondary Outcomes
- Kinetics analysis(Baseline)
- Timed Up & Go (non VR condition)(Baseline)
- Validation of the TUG in VR condition(1 year follow-up)
- Correlation between TUG and TUG VR times and fall follow-up(1 year follow-up)
- Kinematics analysis(Baseline)
- Physiological analysis 1(Baseline)
- Physiological analysis 2(Baseline)
- Physiological analysis 3(Baseline)
- Visual attention analysis(Baseline)
- Psychology analysis 1(Baseline)
- Psychology analysis 2(Baseline)
- Psychology analysis 3(Baseline)
- Automated learning and falling risk estimation(up to 3 years)