Affiliations: [a] EA CoBTeK, University of Nice Sophia Antipolis, France | [b] School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University Medical Center, Maastricht, The Netherlands | [c] Centre Mémoire de Ressources et de Recherche, CHU de Nice, Nice, France | [d] INRIA - STARS team - Sophia Antipolis, France
Correspondence:
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Correspondence to: Alexandra König, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht, EA CoBTek - Centre Mémoire de Ressources et de Recherche, Institut Claude Pompidou, 10 Rue Molière, 06100 Nice, France. Tel.: +33 0 4 92 03 47 70; Fax: +33 0 4 92 03 47 72; E-mail: [email protected].
Abstract: Over the last few years, the use of new technologies for the support of elderly people and in particular dementia patients received increasing interest. We investigated the use of a video monitoring system for automatic event recognition for the assessment of instrumental activities of daily living (IADL) in dementia patients. Participants (19 healthy subjects (HC) and 19 mild cognitive impairment (MCI) patients) had to carry out a standardized scenario consisting of several IADLs such as making a phone call while they were recorded by 2D video cameras. After the recording session, data was processed by a platform of video signal analysis in order to extract kinematic parameters detecting activities undertaken by the participant. We compared our automated activity quality prediction as well as cognitive health prediction with direct observation annotation and neuropsychological assessment scores. With a sensitivity of 85.31% and a precision of 75.90%, the overall activities were correctly automatically detected. Activity frequency differed significantly between MCI and HC participants (p < 0.05). In all activities, differences in the execution time could be identified in the manually and automatically extracted data. We obtained statistically significant correlations between manually as automatically extracted parameters and neuropsychological test scores (p < 0.05). However, no significant differences were found between the groups according to the IADL scale. The results suggest that it is possible to assess IADL functioning with the help of an automatic video monitoring system and that even based on the extracted data, significant group differences can be obtained.
Keywords: Alzheimer's disease, assessment, autonomy, dementia, mild cognitive impairment, information and communication technologies, instrumental activities of daily living, video analyses
