Addressing the Deployment Challenges of Health Monitoring Devices for a Dementia Study

Collins, Tim; Aldred, Sarah; Woolley, Sandra; Rai, Sahara

doi:10.4108/eai.14-10-2015.2261638

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…The selection of an appropriate activity monitor for a given study is typically determined by the required parameter acquisitions and deployment needs [24] as well as the study budget. However, the calibration and validation of devices [25,26] can be onerous.…”

Section: Introductionmentioning

confidence: 99%

Version Reporting and Assessment Approaches for New and Updated Activity and Heart Rate Monitors

Collins

Woolley

Oniani

et al. 2019

Sensors

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This paper addresses the significant need for improvements in device version reporting and practice across the academic and technical activity monitoring literature, and it recommends assessments for new and updated consumer sensing devices. Reproducibility and data veracity are central to good scholarship, and particularly significant in clinical and health applications. Across the literature there is an absence of device version reporting and a failure to recognize that device validity is not maintained when firmware and software updates can, and do, change device performance and parameter estimation. In this paper, we propose the use of tractable methods to assess devices at their current version and provide an example empirical approach. Experimental results for heart rate and step count acquisitions during walking and everyday living activities from Garmin Vivosmart 3 (v4.10) wristband monitors are presented and analyzed, and the reliability issues of optically-acquired heart rates, especially during periods of activity, are demonstrated and discussed. In conclusion, the paper recommends the empirical assessment of new and updated activity monitors and improvements in device version reporting across the academic and technical literature.

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Section: Introductionmentioning

confidence: 99%

Version Reporting and Assessment Approaches for New and Updated Activity and Heart Rate Monitors

Collins

Woolley

Oniani

et al. 2019

Sensors

Self Cite

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“…Due to issues of cognitive limitations and other risk factors associated with aging, studies have suggested that elderly users, especially PWDs exhibit resistance to the use of healthcare devices [ 2 , 13 ]. Notwithstanding the existence of these studies, other research and projects have demonstrated that, with the right approach to design considerations, this resistance could be reduced tremendously, leading to the adoption of wearable devices by PWDs [ 14 , 15 , 16 , 17 , 18 , 19 ]. For instance, studies have revealed that GPS-based wireless tracking devices, such as GPS Smart Sole, Freedom GPS Locator Watch, Safe-link, Mindme Locate, MXLOCareTM, iTraq3, and PocketFinder+, and others, such as Fitbit, Mi band, Oura ring, and Alice PDx, have been preferred and widely used by PWDs [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Impact of Actual Use Behavior of Healthcare Wearable Devices on Quality of Life: A Cross-Sectional Survey of People with Dementia and Their Caregivers in Ghana

et al. 2022

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The increasing prevalence of dementia has necessitated the introduction and use of healthcare wearable devices to augment the healthcare services delivered to people with dementia (PWDs). Unfortunately, evidence on user feedback and the real impact of the actual use of these devices on the quality of life of PWDs has not been fully explored, especially in the context of developing countries. This study, therefore, seeks to evaluate the impact of actual use behavior (AUB) of healthcare wearable devices on the quality of life (QoL) of PWDs in Ghana by using constructs from the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model and the SF-36 quality of life instrument. Data were collected from patients with dementia and, in some cases, caregivers (acting as proxies) in three administrative regions of Ghana using structured questionnaires. Of the 420 questionnaires distributed, 356 were returned, giving a response rate of (356/420, 84.8%). Three hundred and twenty (320) responses were used for further analysis, employing the Partial Least Squares based on Structural Equation Modeling. The results showed a significant positive relationship between AUB and QoL (p < 0.001). Other predictors such as behavioral intention, facilitating conditions, effort expectancy and social influence were also found to significantly impact the actual use behavior of healthcare wearable devices among PWDs. The study also revealed that 4% (14) of patients rated their reported health transition associated with the use of healthcare wearable devices as excellent, 42.5% (136) as very good, and 39.4% (126) as good, respectively at the time of the study compared to a year ago. This study provided empirical evidence of the positive impact of the actual use of healthcare wearable devices on the quality of life of PWDs and further highlighted the factors that drive actual use behavior among PWDs in Ghana. Based on the findings of this study, stakeholders need to create the necessary conditions that will facilitate the adoption and use of healthcare wearable devices, as this will help improve the quality of life, reduce the burden of the disease on caregivers, and enable independent living of PWDs.

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Wearables and Workload

Schwartz¹,

Oppold

Hancock

2019

Critical Issues Impacting Science, Technology, Society (STS), and Our Future

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Prior research has reported that novelty affects the usage cycle of wearable devices. This chapter investigates the effects of sensation seeking, intensity, novelty, gender, and prior experience on the workload experienced during one aspect of using wearable fitness trackers, the device installation process. Contrary to the authors' hypotheses, prior experience, sensation seeking, intensity, and novelty did not significantly affect workload. The findings suggest that males tend to experience less workload during the setup of wearable fitness trackers; however, only for the Basis B1 and only for some aspects of workload. The claims made by prior research may be limited to specific aspects of the wearable fitness tracker use cycle, and more investigation is needed before broader claims can be made.

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Addressing the Deployment Challenges of Health Monitoring Devices for a Dementia Study

Cited by 3 publications

References 5 publications

Version Reporting and Assessment Approaches for New and Updated Activity and Heart Rate Monitors

Version Reporting and Assessment Approaches for New and Updated Activity and Heart Rate Monitors

Impact of Actual Use Behavior of Healthcare Wearable Devices on Quality of Life: A Cross-Sectional Survey of People with Dementia and Their Caregivers in Ghana

Wearables and Workload

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