Validation of an Automatic Video Monitoring System for the Detection of Instrumental Activities of Daily Living in Dementia Patients

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.

Adaptive monitoring system for e-health smart homes

“…Their system, however, do not take into account system resource consumption. König et al have studied the use of a video monitoring system for automatic event recognition for the assessment of IADL in dementia patients [23]. Their system enabled automatic detection of differences in the execution time of activities between healthy subjects and mild cognitive impaired patients.…”

Development of Automatic Speech Recognition Techniques for Elderly Home Support: Applications and Challenges

“…Techniques based on very simple and low cost sensors (PIR) [13] or on video analysis [19] are very popular, however they can not be used for interaction purpose unless they are completed by a tactile device (smart phone), while VocalUser Interface (VUI) may be well adapted because a natural language interaction is relatively simple to use and well adapted to people with reduced mobility or visual impairment [27]. However, there are still important challenges to overcome before implementing VUIs in a smart home [36] and this new technology must be validated in real conditions with potential users [25].…”

Assistive Technologies to Address Capabilities of People with Dementia: From Research to Practice

“…First, research on technologies specifically designed for people with dementia, mostly driven by multi-disciplinary academic/industrial teams and funded by national or international grants, usually results in the production of prototypes to demonstrate practical feasibility and attract further research funding. An example of such upstream research is a validated automatic video monitoring system for the detection of instrumental activities of daily living in people with dementia (König et al, 2015). A second approach is to adapt existing technologies to new potential usage by people with dementia, usually funded by technology industrials seeking first sales or commercial target extension, with eventual support from local or regional partners.…”