Gait Analysis by Induced Disorientation in a VR Environment

University Medical Center Rostock

Status: Unknown

Conditions: Disorientation; Young Adults; Mild Dementia; Mild Cognitive Impairment; Older Adults

Study type: Observational

Funder types: Other

Identifiers

NCT04134806

A 2019-0062

Details and patient eligibility

About

The aim of the study is to investigate whether the effect of disorientation on physical motion and gait among dementia patients, can be reliably measured in a laboratory environment, by means of a virtual reality (VR) experimental setup.

Full description

Challenges in wayfinding and orientation are early symptoms of MCI and dementia. These deficits decrease mobility which again leads to further cognitive decline. In a field study, we developed a pattern recognition model of disorientated behaviour based on accelerometric data. However, it is questionable if phases of disorientation also affect gait parameters. Furthermore, there is growing evidence that impaired cognitive functioning is associated with changes in gait performance, e.g. gait variability, measured in dual-task walking conditions. Increases in heart rate and skin conductance have also been reported during instances of disorientation.

Hence, We implemented a 3D environment of a familiar city centre in the GRAIL, which combines a fully instrumented treadmill with a synchronized VR environment. We record gait parameters through the motion capture system, and accelerometric and physiological data using wearable sensors (movisens), for comparability with the SiNDeM field study. Young and old healthy adults will participate in the first phase of the study, while Mild dementia or MCI patients will participate in the later phases. Phases of disorientation will be induced by changing the virtual environment.We aim to assess gait, accelerometric and physiological parameters during instances of disorientation, using the GRAIL (Gait Real-Time Analysis Interactive Lab, Motekforce Link).

The results will further enable the automatic detection of disorientation based on gait parameters, physiological and accelerometric data. This is necessary for the development of a situation-aware assistive system which supports persons with dementia in autonomous outdoor mobility.

Enrollment: 80 estimated patients

Sex: All

Ages: 18 to 85 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• Within the required age bracket
• Mobile
• Dementia

Exclusion criteria

• Other neurological conditions besides dementia
• Inability to understand task instructions, deaf-mute, blindness

Trial design

80 participants in 3 patient groups

Young Adults

Description:

Neurologically healthy young adults between ages 18 and 40

Older Adults

Description:

Neurologically healthy older adults between ages 60 and 85

Mild Cognitive Impairment/Mild Dementia

Description:

Older adults between ages 60 and 85 with Mild Cognitive Impairment or Mild Dementia