Automatic video monitoring system for assessment of Alzheimer's disease symptoms
Open accessAbstract
In order to fully capture the complexity of the behavioural, functioning and cognitive disturbances in Alzheimer Disease (AD) and related disorders information and communication techniques (ICT), could be of interest. This article presents using 3 clinical cases the feasibility results of an automatic video monitoring system aiming to assess subjects involved in a clinical scenario. METHOD AND POPULATION: The study was conducted in an observation room equipped with everyday objects for use in activities of daily living. The overall aim of the clinical scenario was to enable the participants to undertake a set of daily tasks that could realistically be achieved in the setting of the observation room. The scenario was divided in three steps covering basic to more complex activities: (1) Directed activities, (2) Semi-directed activities, (3) Undirected ("free") activities. The assessment of each participant of the study was done with an automatic video monitoring system composed of a vision component and an event recognition component. The feasibility study involved three participants: two AD patients and one elderly control participant. RESULTS: The first result of the study was to demonstrate the feasibility of this new assessment method from both the patient and the technical points of view. During the first step the control participant performed all these activities faster than the two AD participants. During the second step of the scenario AD participants were not able to follow the correct order of the tasks and even omitted some of them. Finally during the last step of the scenario devoted to free activities the control participant chose one of the proposed activities (reading) and undertook this activity for almost the entire duration. In contrast, the two AD participants had more difficulties choosing one of the suggested activities and were not able to undertake any one activity in a sustained manner. DISCUSSION: The automatic video monitoring system presented here analyzes human behaviours and looks for changes in activity through the detection of the presence of people and their movements in real time. Once the technique has been standardized, it could significantly enhance the assessment of AD patients in both clinical and clinical trial settings as well as providing further information regarding patient frailty that could enhance their safety and ease caregiver burden.
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ICT allows continuous monitoring of patient's performance and actions in real time and real-life situations.
“In particular, ICT allows continuous monitoring of patient's performance and actions in real time and real-life situations (258–260).”
From The Multidisciplinary Approach to Alzheimer’s Disease and Dementia. A Narrative Review of Non-Pharmacological Treatment (2018) · cites this paper as [260]
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- Authors
- Romdhane, R., Mulin, E., Derreumeaux, A., Zouba, N., Piano, J., Lee, L., Leroi, I., Mallea, P., David, R., Thonnat, M., Bremond, F., & Robert, P. H.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Centre Hospitalier Universitaire de Nice (FR)
- University of Manchester (GB)
- Corresponding author
- Robert, P.H.
- Venue
- The Journal of nutrition, health and aging
- Publisher
- Elsevier BV
- Published
- 2012-03
- Volume
- 16
- Issue
- 3
- Pages
- 213-218
- ISSN
- 1279-7707 (ISSN-L)
- PMC
- PMC12878070
- OpenAlex
- W2164567451
- Cited by
- 32
- References
- 19
- Citations by year
- 2026: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2019: 2 · 2018: 1 · 2016: 4 · 2015: 6 · 2014: 3 · 2013: 7 · 2012: 3
- FWCI
- 4.33
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The journal of nutrition health & aging (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- Research Explorer (The University of Manchester) (publishedVersion)
- HAL (submittedVersion, other-oa)
- Funders
- Agence Nationale de la Recherche (ANR-09-TECS-0016)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Keywords
- Alzheimer's disease, activities of daily living, event recognition, real-time human detection, human motion analysis, behavioral assessment, clinical trial monitoring, patient frailty, caregiver burden, older adults
- MeSH terms
- Activities of Daily Living, Aged, Alzheimer Disease, Feasibility Studies, Female, Humans, Male, Neuropsychological Tests, Population Surveillance, Severity of Illness Index, Video Recording, Diagnostic and Statistical Manual of Mental Disorders
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