Development of a Proxy-Free Objective Assessment Tool of Instrumental Activities of Daily Living in Mild Cognitive Impairment Using Smart Home Technologies

Abstract

Background: The assessment of activities of daily living (ADL) is essential for dementia diagnostics. Even in mild cognitive impairment (MCI), subtle deficits in instrumental ADL (IADL) may occur and signal a higher risk of conversion to dementia. Thus, sensitive and reliable ADL assessment tools are important. Smart homes equipped with sensor technology and video cameras may provide a proxy-free assessment tool for the detection of IADL deficits.Objective:The aim of this paper is to investigate the potential of a smart home environment for the assessment of IADL in MCI.Method: The smart home consisted of a two-room flat equipped with activity sensors and video cameras. Participants with either MCI or healthy controls (HC) had to solve a standardized set of six tasks, e.g., meal preparation, telephone use, and finding objects in the flat.Results: MCI participants needed more time (1384 versus 938 seconds, p < 0.001) and scored less total points (48 versus 57 points, p < 0.001) while solving the tasks than HC. Analyzing the subtasks, intergroup differences were observed for making a phone call, operating the television, and retrieving objects. MCI participants showed more searching and task-irrelevant behavior than HC. Task performance was correlated with cognitive status and IADL questionnaires but not with participants’ age.Conclusion: This pilot study showed that smart home technologies offer the chance for an objective and ecologically valid assessment of IADL. It can be analyzed not only whether a task is successfully completed but also how it is completed. Future studies should concentrate on the development of automated detection of IADL deficits.

How smart homes are used to support older people: An integrative review

“…The selected papers (Table ) included two qualitative interview studies (Peek et al, ; Ravishankar, Burleson, & Mahoney, ) and six descriptive quantitative studies (Akl, Snoek, & Mihailidis, ; Alberdi et al, ; Austin et al, ; Bock et al, ; Jekel, Damian, Storf, Hausner, & Frölich, ; Lussier et al, ). There were also five research papers on device tests (Blasco, Marco, Casas, Cirujano, & Picking, ; Cook, Schmitter‐Edgecombe, & Dawadi, ; Dawadi, Cook, & Schmitter‐Edgecombe, ; Sacco et al, ; Suryadevara & Mukhopadhyay, ).…”

“…The main focus of five studies was smart home devices for daily activities and healthy living. Of the 16 studies we selected, seven looked at smart home devices with regard to the quality of daily activities (Alberdi et al, ; Blasco et al, ; Cook et al, ; Dawadi et al, ; Lussier et al, ; Ravishankar et al, ; Suryadevara & Mukhopadhay, ), four examined older people's safety related to physical environment (Bock et al, ; Cook et al, ; Dawadi et al, ; Pigini et al, ), four looked at physical activity (Austin et al, ; Dawadi et al, ; Gaugler et al, ; Pigini et al, ) and two focused on social isolation and loneliness (Austin et al, ; Jekel et al, ). Some of the studies looked at more than one area.…”

“…Seven of the studies were conducted in the United States (Akl et al, ; Austin et al, ; Bock et al, ; Cook et al, ; Dawadi et al, ; Gaugler et al, ; Ravishankar et al, ), two in France (Mehrabian et al, ; Sacco et al, ), one in Spain and United Kingdom (Blasco et al, ), one in Spain and the United States (Alberdi et al, ) and one each in Germany (Jekel et al, ), the Netherlands (Peek et al, ), New Zealand (Suryadevara & Mukhopadhay, ), Italy (Pigini et al, ) and Canada (Lussier et al, ).…”

“…Based on the results of our review, smart home devices for daily and healthy living had been described as a tools that could be used to evaluate and determine the quality of completed activities (Blasco et al, ; Dawadi et al, ; Lussier et al, ; Ravishankar et al, ) , the time and duration of daily activities (Suryadevara & Mukhopadhyay, ), the use of furniture, objects and domestic appliances (Cook et al, ; Lussier et al, ; Suryadevara & Mukhopadhyay, ) and physical (Alberdi et al, ; Austin et al, ; Dawadi et al, ) and social activity (Austin et al, ; Jekel et al, ). They were operated by sensors (Lussier et al, ; Suryadevara & Mukhopadhyay, ), self‐learning algorithms (Alberdi et al, ; Cook et al, ; Dawadi et al, ) and by evaluating telephone use (Austin et al, ; Jekel et al, ). The evaluation was related to the quality of the daily activities (Cook et al, ; Dawadi et al, ) and social contacts (Austin et al, ; Jekel et al, ) of older people in their normal environments.…”

“…They were operated by sensors (Lussier et al, ; Suryadevara & Mukhopadhyay, ), self‐learning algorithms (Alberdi et al, ; Cook et al, ; Dawadi et al, ) and by evaluating telephone use (Austin et al, ; Jekel et al, ). The evaluation was related to the quality of the daily activities (Cook et al, ; Dawadi et al, ) and social contacts (Austin et al, ; Jekel et al, ) of older people in their normal environments. The detailed data derived from the smart home sensors could be used to evaluate how older people coped with diverse activities, such as dressing and cooking , with changes in their cognitive health status and assess the overall quality of tasks by using learning algorithms (Dawadi et al, ; Lussier et al, ).…”