Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Bowen, Mary Elizabeth; Kearns, William D.; Crenshaw, Jeremy R.; Stanhope, Steven J.

doi:10.3791/58834

Cited by 4 publications

(10 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Department of Veterans Affairs (VA) is primed to conduct this research for several reasons. First, the VA has knowledgeable RTLS researchers focusing on multiple geriatric patient populations across several outcome areas [30, 31, 33, 39]. For example, a RTLS has been used to detect a fall in real-time [36] and track the potential spread of multi-drug resistant organisms [29].…”

Section: Discussionmentioning

confidence: 99%

“…The location of the resident will also jump—sometimes putting a path through a wall—if the tag sleeps due to a long period of inactivity and then wakes due to resident movement. Previous work further details smoothing data to improve location precision [31]. Briefly, RTLS data are smoothed using a 5-s moving average time window and then a threshold of 0.7 m of movement is applied.…”

Section: Methodsmentioning

confidence: 99%

“…This creates a stable series of coordinates, resembling the observed resident ambulation. To manage the jumps in data, when computing a day’s motion, distance and time are accrued only when time between points are less than 30 s. These algorithms are custom coded using Python and PHP [31]. After smoothing RTLS data, it is reduced to hourly, daily and weekly measures of ambulation activity (e.g., taking the average for each measure over the course of 7 days).…”

Section: Methodsmentioning

confidence: 99%

“…Previous work details the protocol for the RTLS sensor set up in a long-term care facility [31]. Briefly, this requires mounting sensors in the corners of the unit where tracking is desired and calibrating RTLS tags (embedded in wristbands), and connecting (wirelessly) to a server.…”

Section: Methodsmentioning

confidence: 99%

“…The resident’s location is determined by x and y coordinates which are compared to a known sensor location, and transmitted to the server on the unit [48]. SmartFactory Ubisense software [31] writes x, y coordinates to a SQLite database [49] which is exported to IBM SPSS.…”

Section: Methodsmentioning

confidence: 99%

See 4 more Smart Citations

A research proposal testing a new model of ambulation activity among long-term care residents with dementia/cognitive impairment: the study protocol of a prospective longitudinal natural history study

Bowen

Rowe

et al. 2019

BMC Res Notes

View full text Add to dashboard Cite

Background Excessive and patterned ambulation is associated with falls, urinary tract infections, co-occurring delirium and other acute events among long-term care residents with cognitive impairment/dementia. This study will test a predictive longitudinal data model that may lead to the preservation of function of this vulnerable population. Methods/design This is a single group, longitudinal study with natural observations. Data from a real-time locating system (RTLS) will be used to objectively and continuously measure ambulation activity for up to 2 years. These data will be combined with longitudinal acute event and functional status data to capture patterns of change in health status over time. Theory-driven multilevel models will be used to test the trajectories of falls and other acute conditions as a function of the ambulation activity and demographic, functional status, gait quality and balance ability including potential mediation and/or moderation effects. Data-driven machine learning algorithms will be applied to run screening of the high dimensional RTLS data together with other variables to discover new and robust predictors of acute events. Discussion The findings from this study will lead to the early identification of older adults at risk for falls and the onset of acute medical conditions and interventions for individualized care.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

A research proposal testing a new model of ambulation activity among long-term care residents with dementia/cognitive impairment: the study protocol of a prospective longitudinal natural history study

Bowen

Rowe

et al. 2019

BMC Res Notes

View full text Add to dashboard Cite

show abstract

Changes in Motor Behavior Predict Falls and Identify Acute Events

Bowen

Cacchione

2021

West J Nurs Res

View full text Add to dashboard Cite

This study aimed to examine how changes in motor behavior are associated with falls, delirium, and urinary tract infections (UTIs). Twenty-three (128 observations) skilled nursing residents were examined for up to 18 months. In multilevel models, motor behaviors (e.g., time and distance traveled, gait speed), measured by a real-time locating system, were used to predict falls, UTIs, and delirium. Falls were associated with decreased gait speed ( OR = 0.01; p ≤ 0.001) and path distance ( OR = 0.99; p ≤ 0.05); delirium was associated with increased distance traveled ( OR = 1.01; p ≤ 0.001), path distance ( OR = 1.02; p ≤ 0.001), and decreased time traveled ( OR = 0.99; p ≤ 0.001) and path time ( OR = 0.99; p ≤ 0.001); UTIs were associated with increased distance traveled ( OR = 1.01; p ≤ 0.001), decreased time traveled ( OR = 0.99; p ≤ 0.001), and the number of paths ( OR = 0.91; p ≤ 0.01). Subtle changes in motor behavior may be an early warning sign of falls and acute events. Continuous monitoring may enable clinical staff to prevent, identify early, and/or delay these poor health outcomes.

show abstract

Factors Affecting the Implementation, Use, and Adoption of Real-Time Location System Technology for Persons Living With Cognitive Disabilities in Long-term Care Homes: Systematic Review

Grigorovich¹,

Kulandaivelu²,

Newman³

et al. 2021

J Med Internet Res

View full text Add to dashboard Cite

Background As the aging population continues to grow, the number of adults living with dementia or other cognitive disabilities in residential long-term care homes is expected to increase. Technologies such as real-time locating systems (RTLS) are being investigated for their potential to improve the health and safety of residents and the quality of care and efficiency of long-term care facilities. Objective The aim of this study is to identify factors that affect the implementation, adoption, and use of RTLS for use with persons living with dementia or other cognitive disabilities in long-term care homes. Methods We conducted a systematic review of the peer-reviewed English language literature indexed in MEDLINE, Embase, PsycINFO, and CINAHL from inception up to and including May 5, 2020. Search strategies included keywords and subject headings related to cognitive disability, residential long-term care settings, and RTLS. Study characteristics, methodologies, and data were extracted and analyzed using constant comparative techniques. Results A total of 12 publications were included in the review. Most studies were conducted in the Netherlands (7/12, 58%) and used a descriptive qualitative study design. We identified 3 themes from our analysis of the studies: barriers to implementation, enablers of implementation, and agency and context. Barriers to implementation included lack of motivation for engagement; technology ecosystem and infrastructure challenges; and myths, stories, and shared understanding. Enablers of implementation included understanding local workflows, policies, and technologies; usability and user-centered design; communication with providers; and establishing policies, frameworks, governance, and evaluation. Agency and context were examined from the perspective of residents, family members, care providers, and the long-term care organizations. Conclusions There is a striking lack of evidence to justify the use of RTLS to improve the lives of residents and care providers in long-term care settings. More research related to RTLS use with cognitively impaired residents is required; this research should include longitudinal evaluation of end-to-end implementations that are developed using scientific theory and rigorous analysis of the functionality, efficiency, and effectiveness of these systems. Future research is required on the ethics of monitoring residents using RTLS and its impact on the privacy of residents and health care workers.

show abstract

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

Cited by 4 publications

References 1 publication

A research proposal testing a new model of ambulation activity among long-term care residents with dementia/cognitive impairment: the study protocol of a prospective longitudinal natural history study

A research proposal testing a new model of ambulation activity among long-term care residents with dementia/cognitive impairment: the study protocol of a prospective longitudinal natural history study

Changes in Motor Behavior Predict Falls and Identify Acute Events

Factors Affecting the Implementation, Use, and Adoption of Real-Time Location System Technology for Persons Living With Cognitive Disabilities in Long-term Care Homes: Systematic Review

Contact Info

Product

Resources

About