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1.
Comput Inform Nurs ; 35(7): 331-337, 2017 Jul.
Article in English | MEDLINE | ID: mdl-28187009

ABSTRACT

Aging in place is a preferred and cost-effective living option for older adults. Research indicates that technology can assist with this goal. Information on consumer preferences will help in technology development to assist older adults to age in place. The study aim was to explore the perceptions and preferences of older adults and their family members about a fall risk assessment system. Using a qualitative approach, this study examined the perceptions, attitudes, and preferences of 13 older adults and five family members about their experience living with the fall risk assessment system during five points in time. Themes emerged in relation to preferences and expectations about the technology and how it fits into daily routines. We were able to capture changes that occurred over time for older adult participants. Results indicated that there was acceptance of the technology as participants adapted to it. Two themes were present across the five points in time-safety and usefulness. Five stages of acceptance emerged from the data from preinstallation to 2 years postinstallation. Identified themes, stages of acceptance, and design and development considerations are discussed.


Subject(s)
Accidental Falls/prevention & control , Family/psychology , Inventions/statistics & numerical data , Patient Acceptance of Health Care/psychology , Female , Humans , Independent Living , Male , Qualitative Research , Risk Assessment
2.
Gerontologist ; 55 Suppl 1: S78-87, 2015 Jun.
Article in English | MEDLINE | ID: mdl-26055784

ABSTRACT

PURPOSE OF THE STUDY: Falls are a major problem for the elderly people leading to injury, disability, and even death. An unobtrusive, in-home sensor system that continuously monitors older adults for fall risk and detects falls could revolutionize fall prevention and care. DESIGN AND METHODS: A fall risk and detection system was developed and installed in the apartments of 19 older adults at a senior living facility. The system includes pulse-Doppler radar, a Microsoft Kinect, and 2 web cameras. To collect data for comparison with sensor data and for algorithm development, stunt actors performed falls in participants' apartments each month for 2 years and participants completed fall risk assessments (FRAs) using clinically valid, standardized instruments. The FRAs were scored by clinicians and recorded by the sensing modalities. Participants' gait parameters were measured as they walked on a GAITRite mat. These data were used as ground truth, objective data to use in algorithm development and to compare with radar and Kinect generated variables. RESULTS: All FRAs are highly correlated (p < .01) with the Kinect gait velocity and Kinect stride length. Radar velocity is correlated (p < .05) to all the FRAs and highly correlated (p < .01) to most. Real-time alerts of actual falls are being sent to clinicians providing faster responses to urgent situations. IMPLICATIONS: The in-home FRA and detection system has the potential to help older adults remain independent, maintain functional ability, and live at home longer.


Subject(s)
Accidental Falls , Geriatric Assessment/methods , Monitoring, Ambulatory/methods , Risk Assessment , Security Measures , Activities of Daily Living , Aged , Aged, 80 and over , Aging , Algorithms , Female , Gait , Humans , Male , Safety , Video Recording
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