Home Healthcare, Hospice, and Information Technology Innovations Conference

Innovations in Home Healthcare, Hospice, and Information Technology

A forum towards achieving evidence-based diffusion and implementation of innovations

Fri, Nov 3, 2017

Friday, Nov 3, 2017, Washington - D.C.

H3IT: Home Healthcare, Hospice, and Information Technology Conference Chicago, IL, 2016

A Feasibility Study Examining Older Adult Needs

within Smart Home Sensor Deployments

Yong Choi

(yongchoi@uw.edu), George Demiris

1, 2

(gdemiris@uw.edu), Arjmand Samuel

(arjmands@microsoft.com), Danny

Huang

(v-dannhu@microsoft.com)

s older adults age, they are faced with numerous challenges that hinder their independent living such as symp-

toms resulting from chronic health conditions, reduced mobility, social isolation and cognitive decline.

Recent

developments in smart home technology designed to detect and record individuals’ activities and status within

their living spaces present a unique opportunity to improve their health and wellness.

Although there have

been reported beneﬁts resulting from the use of smart home technology,

3,4

the deployment of sensor systems has often been

limited to lab oratory settings due to practical challenges such as managing multiple sensor installations. Furthermore, it

becomes challenging for these new technologies to generate data that can be presented and visualized in a comprehensible

and eﬃcient manner so that older adults themselves can access and interpret information about their activities of daily living.

In this study, we deployed commercially available sensors to community-dwelling older adults’ residences using the Lab of

Things platform for connected devices.

5,6

The primary goal of this study was to understand the information and visualization

needs and preferences of older adults when presented with actual sensor data collected from a 2-month deployment within

the home.

Methods: We are recruiting older adult (65 and older) participants through collaboration with local retirement facilities

in Seattle to take part in a 2-month deployment study. Eligible participants have to be community dwelling older adults

(including residing in an independent living facility), able to give informed consent, and able to read and write English.

The participants are given a choice to choose the sensors they would like to have installed within their home. The sensors

are commercially available and consist of a Door/window sensor and a Multi-sensor (collects data on motion, temperature,

luminosity, and humidity), and a Foscam IP camera. Participants have to select at least one sensor to be eligible for the study.

We use a secure platform, Microsoft’s Lab of Things,

5,6

for collecting and managing data from the sensors. We conduct three

interview sessions one at baseline, one at 1 month, and another at exit. During the interviews we engage participants within

the design of data visualizations derived from the sensor data through a participatory design approach. This involves asking

participants to provide feedback on iterations of the design and also to generate ideas for alternatives to the visualization.

The interviews also seek to gather participant perspectives on sensor use within the home, in particular addressing issues

of intrusiveness, perceived value, and information needs from the visualization. All interviews are audio-recorded and tran-

scribed for content analysis. We also gather demographics and collect participants’ self- reported daily activities (IADL), the

participant’s perceived health and well-being (SF-12), and life-space mobility (LSA), and e-health literacy (eHeals) during

baseline and exit interviews. The University Institutional Review Board approved all study procedures.

Results: The study is currently ongoing. To date ﬁve older adults have been recruited and have ﬁnished mid-point inter-

views. The mean age (SD) of the participants is 91 (4.9) years old. All of our participants have a Bachelor’s degree or higher.

Our ﬁndings so far demonstrate the need to develop interfaces that truly match users’ needs and expectations. Furthermore,

as participants have commented, the processing of visualized information requires that users understand the context of this

assessment (e.g., when data were collected, how they can be used to inform decisions, what the clinical implications of pat-

terns changes may be). We will present recommendations for the design of user interfaces and visualization prototypes based

on the iterative feedback provided by our participants.

Discussion: The innovation brought by the smart home technologies can signiﬁcantly impact the future of home healthcare.

With more and more older adults showing interest in smart home technologies,

the home healthcare industry needs to think

about integrating smart home sensors in their care plan. In order for smart homes to become widely used, we need to ensure

that the information generated by such passive monitoring systems is easily accessible and understood by all stakeholders,

especially older adults, if the use of technology aims to empower them rather than simply monitor every one of their move-

ments.

Conclusion: Despite the p otential of smart home technology, there remains a challenge in increasing acceptance and usage

of these technologies particularly among older adults. Our work highlights that the eﬀective visualization of smart home

data is key to the success and ultimate adoption of smart home applications to support aging in place.

University of Washington, School of Medicine, Biomedical and Health Informatics

University of Washington, School of Nursing

Microsoft Research, Seattle, WA

H3IT: Home Healthcare, Hospice, and Information Technology Conference Chicago, IL, 2016

References

1. Grembowski, D, Patrick, D, Diehr, P, Durham, M, Beresford, S, Kay, E, and Hecht, J. Self-eﬃcacy and health behavior

among older adults. Journal of health and social behavior 1993:89–104.

2. Demiris, G, Hensel, BK, et al. Technologies for an aging society: a systematic review of “smart home” applications.

Yearb Med Inform 2008;3:33–40.

3. Lee, ML and Dey, AK. Embedded assessment of aging adults: A concept validation with stakeholders. In: Pervasive

Computing Technologies for Healthcare (PervasiveHealth), 2010 4th International Conference on-NO PERMISSIONS.

IEEE. 2010:1–8.

4. Demiris, G, Rantz, MJ, Aud, MA, Marek, KD, Tyrer, HW, Skubic, M, and Hussam, AA. Older adults’ attitudes towards

and perceptions of ‘smart home’technologies: a pilot study. Medical informatics and the Internet in medicine 2004;29:87–

94.

5. Brush, A, Jung, J, Mahajan, R, and Scott, J. HomeLab: shared infrastructure for home technology ﬁeld studies. In:

Proceedings of the 2012 ACM Conference on Ubiquitous Computing. ACM. 2012:1108–1113.

6. Brush, A, Filippov, E, Huang, D, et al. Lab of things: a platform for conducting studies with connected devices in multiple

homes. In: Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication. ACM.

2013:35–38.