Smart Home Technologies for Assessing and Monitoring Frailty in Older Adults

NCT ID: NCT05961319

Last Updated: 2024-08-23

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

21 participants

Study Classification

OBSERVATIONAL

Study Start Date

2023-09-20

Study Completion Date

2024-06-30

Brief Summary

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This project aims to address the impact of frailty on older adults, particularly its connection to cognitive impairments such as dementia. By identifying frailty in its early stages, interventions can be designed to slow down the progression of cognitive decline. To achieve this, the project plans to develop a reliable at-home monitoring system that can accurately track frailty in older adults with mild cognitive impairment or dementia. By utilizing cutting-edge technologies such as high-precision indoor positioning and home-installed sensors, referred to as zero-effort technologies (ZETs), the system will collect continuous sensor data, which will be analyzed to identify indicators of frailty.

Detailed Description

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This project is centred around addressing the impact of frailty on older adults and its correlation with cognitive impairments, particularly dementia. The aim is to develop an effective and non-intrusive at-home monitoring system that can accurately track frailty in older adults with mild cognitive impairment or dementia. By identifying frailty in its early stages, interventions can be designed to slow down the progression of cognitive decline and improve the overall well-being of older adults.

To achieve this, the project plans to leverage cutting-edge technologies such as high-precision indoor positioning and home-installed sensors, collectively referred to as zero-effort technologies (ZETs). These technologies require minimal user effort and will provide a continuous stream of sensor data. The collected data will be systematically analyzed to identify indicators of frailty, allowing for early detection and intervention. Importantly, the project recognizes the significance of engaging older adults, caregivers, and healthcare professionals throughout the development process. Their attitudes, beliefs, and perceptions will be taken into consideration to ensure that the monitoring system is meaningful, beneficial, and respects user privacy.

By involving older adults and caregivers in the early stages, the project aims to create a monitoring system that can be seamlessly integrated into the lives of older adults dealing with frailty and cognitive impairments. The goal is to provide an affordable and efficient solution that can be implemented within the comfort and familiarity of their own homes. The continuous tracking of frailty data will enable healthcare professionals and caregivers to deliver timely interventions and support, thereby potentially slowing down the cognitive decline experienced by older adults.

Through the combination of advanced technologies and a user-centred approach, the project intends to bridge the gap between frailty and cognitive impairments in older adults. By identifying frailty at an early stage and tailoring interventions accordingly, personalized and targeted support can be provided to improve the quality of life for older adults with mild cognitive impairment or dementia. Ultimately, the project aims to contribute to the development of effective strategies for managing frailty and cognitive decline, benefiting both older adults and their caregivers, as well as clinicians.

Conditions

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Frailty Frailty Syndrome Frail Elderly Syndrome Pre-Frailty Healthy Healthy Aging Aging Problems Aging Disorder

Study Design

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Observational Model Type

ECOLOGIC_OR_COMMUNITY

Study Time Perspective

PROSPECTIVE

Study Groups

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Utilizing Smart Home Monitoring System in a Simulated Home Environment (in Hospital)

The project involves recruiting participants who will reside in a simulated condo environment within the Glenrose Rehabilitation Hospital. These participants will be remotely monitored using various sensors, including ones that track their interactions with appliances and furniture, smart biomechanics devices that assess their physical balance and strength, and a positioning system. By collecting and analyzing data from these sensors, the project aims to gain insights into the participants' daily activities, functional abilities, physical condition, and spatial behaviour.

Smart-Home Monitoring

Intervention Type DEVICE

During the study, various sensors will be employed to capture participant interactions with appliances and furniture. These sensors may include:

Interaction Sensors: These sensors are designed to recognize users' interactions with appliances and furniture within the smart environment.

Smart Biomechanics Devices: Devices such as a Fitbit device an internet of Things grip Dynamometer will be utilized to assess physical balance and strength.

Positioning System using Ultra-Wide Band (UWB) Technology: This positioning system leverages UWB technology, enabling furniture-level accuracies in interpreting self-care activities.

As participants engage with different elements of the smart environment, these sensors will collect data. Additionally, participants will be recorded via video to further enhance the observational data captured during the study.

Interventions

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Smart-Home Monitoring

During the study, various sensors will be employed to capture participant interactions with appliances and furniture. These sensors may include:

Interaction Sensors: These sensors are designed to recognize users' interactions with appliances and furniture within the smart environment.

Smart Biomechanics Devices: Devices such as a Fitbit device an internet of Things grip Dynamometer will be utilized to assess physical balance and strength.

Positioning System using Ultra-Wide Band (UWB) Technology: This positioning system leverages UWB technology, enabling furniture-level accuracies in interpreting self-care activities.

As participants engage with different elements of the smart environment, these sensors will collect data. Additionally, participants will be recorded via video to further enhance the observational data captured during the study.

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* In-patients at the Glenrose Rehabilitation Hospital (GRH) and GRH' visitors or staff (e.g. patients' caregivers, relatives, friends of older adults in-patient or staff at the GRH who are interested in participating) who are 65 years old or older
* For in-patients who are pre-frail or frail according to the scale used at the GRH (can be equivalent to Fried's scale pre-frail/frail (score = 1 - 4). For GRH's visitors or staff, are robust according to Fried's Frail Scale (score=0) as per the definition in (Fried, 2001)
* With or without some level of cognitive impairment (Standardized mini-mental state examination (MMSE) of 21 to 30 ("mild" (24-21) to "could be normal" (25-30)) or the equivalent in the screening tool.
* Have a cognitive ability to interact with the frailty sensors (i.e. scale, dynamometer, smart speaker).
* Have a functional vision and hearing with or without aides (glasses/hearing aids) to be able to interact with furniture and sensors at the ILS and to fill out questionnaires.
* Have functional upper extremity function to be able to interact with furniture and sensors at the ILS.
* Be able to walk independently 15 meters with or without a walking aid.
* If taking antidepressants or narcotics, participants have no changes in the medication for at least 3 months

Exclusion Criteria

* Those with a history of Parkinson's disease or other movement disorders or stroke.

Justification: Movement disorders causing tremors will affect data collection by the sensors

* Those who were taking Sinemet or Aricept
* Older adults who have Influenza, long Covid-19 or another virus that affect their performance
* Unable to count, speak (name objects and say numbers) or comprehend simple instructions in English
* Have severe cardiac or respiratory diseases that prevent them to perform vigorous activities
* Using supplemental oxygen (i.e., must be able to breathe with room air)
Minimum Eligible Age

60 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Alberta Health services

OTHER

Sponsor Role collaborator

Glenrose Foundation

OTHER

Sponsor Role collaborator

University of Alberta

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Jim Raso, MASc

Role: STUDY_CHAIR

Alberta Health services

Locations

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Glenrose Rehabilitation Hospital

Edmonton, Alberta, Canada

Site Status

Corbett Hall, University of Alberta

Edmonton, Alberta, Canada

Site Status

Countries

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Canada

References

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Lewinsohn PM, Seeley JR, Roberts RE, Allen NB. Center for Epidemiologic Studies Depression Scale (CES-D) as a screening instrument for depression among community-residing older adults. Psychol Aging. 1997 Jun;12(2):277-87. doi: 10.1037//0882-7974.12.2.277.

Reference Type BACKGROUND
PMID: 9189988 (View on PubMed)

Chisholm D, Toto P, Raina K, Holm M, Rogers J. Evaluating capacity to live independently and safely in the community: Performance Assessment of Self-care Skills. Br J Occup Ther. 2014 Feb;77(2):59-63. doi: 10.4276/030802214X13916969447038.

Reference Type BACKGROUND
PMID: 25298616 (View on PubMed)

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540

Reference Type BACKGROUND

Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, Seeman T, Tracy R, Kop WJ, Burke G, McBurnie MA; Cardiovascular Health Study Collaborative Research Group. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001 Mar;56(3):M146-56. doi: 10.1093/gerona/56.3.m146.

Reference Type BACKGROUND
PMID: 11253156 (View on PubMed)

Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975 Nov;12(3):189-98. doi: 10.1016/0022-3956(75)90026-6. No abstract available.

Reference Type BACKGROUND
PMID: 1202204 (View on PubMed)

Other Identifiers

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Pro00131722

Identifier Type: -

Identifier Source: org_study_id

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