A Practical Platform for In-Home Remote Monitoring of Cognitive Frailty

Baylor College of Medicine

Status: Completed

Conditions: Alzheimer Disease; Cognitive Impairment; Cognitive Impairment, Mild; Frailty; Dementia; Alzheimer Disease, Early Onset

Study type: Observational

Funder types: Other; Industry

Identifiers

NCT05754021

43917

Details and patient eligibility

About

Cognitive frailty, characterized by the coexistence of physical frailty and cognitive impairment, is a robust indicator of cognitive decline. Recognizing its significance, the International Association of Gerontology and Geriatrics and the International Academy on Nutrition and Aging have advocated for the use of cognitive frailty assessment as a means of monitoring the progression of mild cognitive impairment towards debilitating conditions like dementia, Alzheimer's disease, and loss of independence. Despite the clear need, a practical and remotely accessible tool for measuring cognitive frailty is currently lacking, especially within the context of telehealth visits. With telehealth video-conferencing becoming increasingly popular, accepted by healthcare payers, and preferred by older adults who may face difficulties traveling to a clinic, there is a pressing need for a software-based solution for remote cognitive frailty assessment that can be easily integrated into existing telehealth systems. This study proposes designing and validating a video-based solution to remotely monitor cognitive-frailty in older adults.

Full description

The investigators are proposing to evaluate the feasibility and accuracy of the Frailty Meter (FM), a cutting-edge video-based solution for remotely assessing frailty. FM determines frailty phenotypes, such as weakness, slowness, reduced range-of-motion, and exhaustion, by quantifying the results of a 20-second rapid repetitive elbow flexion-extension task captured by a standard video camera. Image processing algorithms are then used to estimate the angular velocity of the elbow, and a previously validated model is employed to calculate frailty phenotypes from the speed of elbow rotation. Furthermore, FM can also be used to assess cognitive impairment when applied during dual-task conditions, such as while performing a working memory task. The objective of this study is to validate the effectiveness of this video-based solution in tracking longitudinal changes in cognitive-motor function among older adults.

Enrollment: 100 patients

Sex: All

Ages: 50 to 95 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 50 years or older
• Ambulatory
• Able and willing to provide consent
• May have a diagnosis of mild dementia or pre-dementia or mild cognitive impairment (MCI), or MoCA score of 26 or lower.

Exclusion criteria

• Major bilateral upper-limb disorder
• Major hearing/visual impairment
• History of stroke in the last 90 days
• Receiving hospice care
• Immobility or major mobility disorder: We will exclude those who were bedbound or unable to stand or ambulate with or without walking assistance
• inability to use telemedicine (e.g. no internet at home, severe visual or hearing problem, lack of caregiver support, etc)
• inability or unwillingness to participate in bi-monthly tele-medicine assessments or in-clinic visit (e.g., living farther than 30 mills from the clinic, unavailability of caregivers).
• significant cognitive impairment (MoCA score<16)
• severe dementia
• severe apathy
• severe depression
• in hospice care or palliative care
• history of drug or alcohol abuse over the last six months
• unable to communicate in English or Spanish