A Pilot Study on a Smart Home for Elders Based on Continuous In-Home Unobtrusive Monitoring Technology

Purpose: This article reports on a pilot study of a smart home for elders (SHfE) designed to continuously monitor senior adults’ daily behaviors and the living environment of their residential homes using the application of unobtrusive sensors. SHfE users include older adults, their family members, and healthcare staff. Background: Globally, countries are experiencing the challenges of an increasingly aging population. A healthy environment is essential to support aging in place. By applying information and communications technology to building environments to support health, smart homes may be an option to provide a low-cost, comfortable, and user-friendly living environment for older adults. Method: A pilot study was conducted in a capital city in the Yangtze River Delta Agglomerations in China to verify the feasibility of the SHfE. One female older adult participated in the pilot study, which was conducted from November 2015 to January 2016. Results: The results indicated that the SHfE is a feasible way to analyze the behaviors (e.g., sleeping, cooking, water usage) of the elder and monitor the built environment (e.g., temperature, windows, and doors). Conclusions: The pilot study can be used as a baseline for further comprehensive experiments, case studies, and surveys to gain a better understanding of a smart healthy environment for older adults. On the basis of the current study, several recommendations are put forward for further implementation of the SHfE, including integrating multiple unobtrusive sensing devices; detecting fall accidents; monitoring indoor lighting, noise, and ventilation; remotely controlling electrical appliances; and developing the system with various languages. It is anticipated that the SHfE will be adopted in seniors’ residential homes in countries around the world which face an increasingly aging population.

[1]  Chris D. Nugent,et al.  Detection of aberrant behaviour in home environments from video sequence , 2010, Ann. des Télécommunications.

[2]  A. Hanson,et al.  Older adults' participation in the development of smart environments: an integrated review of the literature. , 2013, Geriatric nursing.

[3]  R. Hwang,et al.  Field study on behaviors and adaptation of elderly people and their thermal comfort requirements in residential environments. , 2010, Indoor air.

[4]  Subhas Mukhopadhyay,et al.  Forecasting the behavior of an elderly using wireless sensors data in a smart home , 2013, Eng. Appl. Artif. Intell..

[5]  Kwok-wai Mui,et al.  A Field Survey of the Expected Desirable Thermal Environment for Older People , 2009 .

[6]  Andre Gustavo Adami,et al.  Unobtrusive assessment of activity patterns associated with mild cognitive impairment , 2008, Alzheimer's & Dementia.

[7]  John A. Stankovic,et al.  Context-aware wireless sensor networks for assisted living and residential monitoring , 2008, IEEE Network.

[8]  David I Buckley,et al.  Outpatient case management for adults with medical illness and complex care needs , 2013 .

[9]  J. Gubrium,et al.  A theoretical model to explain the smart technology adoption behaviors of elder consumers (Elderadopt). , 2017, Journal of aging studies.

[10]  Gregory D. Abowd,et al.  The Aware Home: A Living Laboratory for Ubiquitous Computing Research , 1999, CoBuild.

[11]  Jingyu Yu,et al.  Impact of the built environment and care services within rural nursing homes in China on quality of life for elderly residents , 2017 .

[12]  Melody Moh,et al.  A prototype on RFID and sensor networks for elder healthcare: progress report , 2005, E-WIND '05.

[13]  William R. Hersh,et al.  Telehealth: Mapping the Evidence for Patient Outcomes From Systematic Reviews , 2016 .

[14]  David I. Levine,et al.  Using Unobtrusive Sensors to Measure and Minimize Hawthorne Effects: Evidence from Cookstoves , 2017 .

[15]  Organización Mundial de la Salud.  Global Health and Aging , 2011 .

[16]  M. Shamim Hossain,et al.  Cyber-physical cloud-oriented multi-sensory smart home framework for elderly people: An energy efficiency perspective , 2017, J. Parallel Distributed Comput..

[17]  S. Czaja,et al.  Advancing the Aging and Technology Agenda in Gerontology. , 2015, The Gerontologist.

[18]  Eleni Stroulia,et al.  International Journal of Medical Informatics , 2016 .

[19]  T. Hayes,et al.  One walk a year to 1000 within a year: continuous in-home unobtrusive gait assessment of older adults. , 2012, Gait & posture.

[20]  Marilyn Cash,et al.  Assistive technology and people with dementia , 2003 .

[21]  Ruzena Bajcsy,et al.  USING SMART SENSORS AND A CAMERA PHONE TO DETECT AND VERIFY THE FALL OF ELDERLY PERSONS , 2005 .

[22]  P. Pasquina,et al.  Sensor technology for smart homes. , 2011, Maturitas.

[23]  S. Corrao,et al.  Effects of ambient temperature, humidity, and other meteorological variables on hospital admissions for angina pectoris , 2012, European journal of preventive cardiology.

[24]  Harald Künemund,et al.  Gero-Technology: Old Age in the Electronic Jungle , 2013 .

[25]  Kaiqi Huang,et al.  ISEE Smart Home (ISH): Smart video analysis for home security , 2015, Neurocomputing.

[26]  Sherif Sakr,et al.  The family of mapreduce and large-scale data processing systems , 2013, CSUR.

[27]  G. Demiris,et al.  Technologies for an Aging Society: A Systematic Review of “Smart Home” Applications , 2008, Yearbook of Medical Informatics.

[28]  Hang Yu,et al.  Thermal comfort and adaptation of the elderly in free-running environments in Shanghai, China , 2017 .

[29]  Takuya Maekawa,et al.  Unobtrusive detection of body movements during sleep using Wi-Fi received signal strength with model adaptation technique , 2018, Future Gener. Comput. Syst..

[30]  William C. Mann,et al.  The Gator Tech Smart House: a programmable pervasive space , 2005, Computer.

[31]  Li-Chen Fu,et al.  Robust Location-Aware Activity Recognition Using Wireless Sensor Network in an Attentive Home , 2009, IEEE Transactions on Automation Science and Engineering.

[32]  K. Courtney.  Privacy and Senior Willingness to Adopt Smart Home Information Technology in Residential Care Facilities , 2008, Methods of Information in Medicine.

[33]  M. Leung,et al.  Impact of facilities management on the quality of life for the elderly in care and attention homes – Cross-validation by quantitative and qualitative studies , 2017 .

[34]  Wan Young Chung,et al.  Activity monitoring from real-time triaxial accelerometer data using sensor network , 2007, 2007 International Conference on Control, Automation and Systems.

[35]  Norm Archer,et al.  Online self-management interventions for chronically ill patients: Cognitive impairment and technology issues , 2014, Int. J. Medical Informatics.

[36]  Álvaro Marco,et al.  Location-based services for elderly and disabled people , 2008, Comput. Commun..

[37]  Cem Ersoy,et al.  Wireless sensor networks for healthcare: A survey , 2010, Comput. Networks.

[38]  Marjorie Skubic,et al.  Average in-home gait speed: investigation of a new metric for mobility and fall risk assessment of elders. , 2015, Gait & posture.

[39]  Damith Chinthana Ranasinghe,et al.  Recognition of falls using dense sensing in an ambient assisted living environment , 2017, Pervasive Mob. Comput..