Christian Bock1,2, George Demiris1,3, Yong Choi1, Thai Le1, Hilaire J Thompson3, Arjmand Samuel4, Danny Huang4. 1. Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Seattle, WA, USA. 2. Ruprecht-Karls-University of Heidelberg, Heidelberg, Germany. 3. Biobehavioral Nursing and Health Systems, School of Nursing, University of Washington, Seattle, WA, USA. 4. Microsoft Research, Seattle, WA, USA.
Abstract
BACKGROUND: The use of smart home sensor systems is growing primarily due to the appeal of unobtrusively monitoring older adult health and wellness. However, integrating large-scale sensor systems within residential settings can be challenging when deployment takes place across multiple environments, requiring customization of applications, connection across various devices and effective visualization of complex longitudinal data. OBJECTIVE: The objective of the study was to demonstrate the implementation of a smart home system using an open, extensible platform in a real-world setting and develop an application to visualize data real time. METHODS: We deployed the open source Lab of Things platform in a house of 11 residents as a demonstration of feasibility over the course of 3 months. The system consisted of Aeon Labs Z-wave Door/Window sensors and an Aeon Labs Multi-sensor that collected data on motion, temperature, luminosity, and humidity. We applied a Rapid Iterative Testing and Evaluation approach towards designing a visualization interface engaging gerontological experts. We then conducted a survey with 19 older adult and caregiver stakeholders to inform further design revisions. RESULTS: Our initial visualization mockups consisted of a bar chart representing activity level over time. Family members felt comfortable using the application. Older adults however, indicated it would be difficult to learn to use the application, and had trouble identifying utility. A key for older adults was ensuring that the data collected could be utilized by their family members, physicians, or caregivers. CONCLUSIONS: The approach described in this work is generalizable towards future smart home deployments and can be a valuable guide for researchers to scale a study across multiple homes and connected devices, and to create personalized interfaces for end users.
BACKGROUND: The use of smart home sensor systems is growing primarily due to the appeal of unobtrusively monitoring older adult health and wellness. However, integrating large-scale sensor systems within residential settings can be challenging when deployment takes place across multiple environments, requiring customization of applications, connection across various devices and effective visualization of complex longitudinal data. OBJECTIVE: The objective of the study was to demonstrate the implementation of a smart home system using an open, extensible platform in a real-world setting and develop an application to visualize data real time. METHODS: We deployed the open source Lab of Things platform in a house of 11 residents as a demonstration of feasibility over the course of 3 months. The system consisted of Aeon Labs Z-wave Door/Window sensors and an Aeon Labs Multi-sensor that collected data on motion, temperature, luminosity, and humidity. We applied a Rapid Iterative Testing and Evaluation approach towards designing a visualization interface engaging gerontological experts. We then conducted a survey with 19 older adult and caregiver stakeholders to inform further design revisions. RESULTS: Our initial visualization mockups consisted of a bar chart representing activity level over time. Family members felt comfortable using the application. Older adults however, indicated it would be difficult to learn to use the application, and had trouble identifying utility. A key for older adults was ensuring that the data collected could be utilized by their family members, physicians, or caregivers. CONCLUSIONS: The approach described in this work is generalizable towards future smart home deployments and can be a valuable guide for researchers to scale a study across multiple homes and connected devices, and to create personalized interfaces for end users.
Keywords:
Data display; aged; remote sensing technology
Authors: Gregory L Alexander; Andrew Georgiou; Kevin Doughty; Andrew Hornblow; Anne Livingstone; Michelle Dougherty; Stephen Jacobs; Malcolm J Fisk Journal: Int J Med Inform Date: 2020-01-24 Impact factor: 4.046