A Smart-Home System to Unobtrusively and Continuously Assess Loneliness in Older Adults

Abstract

Loneliness is a common condition in older adults and is associated with increased morbidity and mortality, decreased sleep quality, and increased risk of cognitive decline. Assessing loneliness in older adults is challenging due to the negative desirability biases associated with being lonely. Thus, it is necessary to develop more objective techniques to assess loneliness in older adults. In this paper, we describe a system to measure loneliness by assessing in-home behavior using wireless motion and contact sensors, phone monitors, and computer software as well as algorithms developed to assess key behaviors of interest. We then present results showing the accuracy of the system in detecting loneliness in a longitudinal study of 16 older adults who agreed to have the sensor platform installed in their own homes for up to 8 months. We show that loneliness is significantly associated with both time out-of-home (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ {\beta } = -0.88$ \end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.01$ \end{document}) and number of computer sessions (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$ {\beta } = 0.78$ \end{document} and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$p<0.05$ \end{document}). \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$R^{2}$ \end{document} for the model was 0.35. We also show the model’s ability to predict out-of-sample loneliness, demonstrating that the correlation between true loneliness and predicted out-of-sample loneliness is 0.48. When compared with the University of California at Los Angeles loneliness score, the normalized mean absolute error of the predicted loneliness scores was 0.81 and the normalized root mean squared error was 0.91. These results represent first steps toward an unobtrusive, objective method for the prediction of loneliness among older adults, and mark the first time multiple objective behavioral measures that have been related to this key health outcome.

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, ).…”

“…), and it can help healthy older people to continue to live independently in their own home as they age (Brims & Oliver, ; Cho & Kim, ). Technology has been used in older people's homes to collect data on using electronic domestic appliances, such as coffee makers and washing machines, and control everyday routines, such as turning lights on and off and opening and closing doors and windows (Austin et al, ). Different robots have been used to decrease social loneliness and as domestic aids to assess daily activities, such as medication, eating, bathing, getting dressed and mobility (Wu et al, ).…”

Minding the Gap: Reconciling Human and Technical Perspectives on the IoT for Healthy Ageing

“…Specifically, studies showed that digital technology and the digital world raise issue of exclusion that may negatively affect the quality of life of older adults by becoming isolated in the continuous advancement of such technology [47].…”