Health at hand: A systematic review of smart watch uses for health and wellness

Reeder, Blaine; David, Alexandria

doi:10.1016/j.jbi.2016.09.001

Cited by 315 publications

(189 citation statements)

References 20 publications

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“…An analysis of 73 studies conducted between 2014 and 2016 showed that watches focused on activity and heart rate monitoring, speech therapy adherence, diabetes self-management, and detection of seizures, tremors, scratching, eating and medication-taking behaviours. The paper concluded that more studies are required to really evaluate the efficacy of smart watches [15]. This requirement may be addressed in Electronics 2020, 9, 275 3 of 21 part by a National Institute of Health (NIH) survey into precision medicine earmarked to start later in 2020 [16].…”

Section: Using the Cellphone Networkmentioning

confidence: 99%

A Telespirometer for the Developing World

Brooker

2020

Electronics

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There are numerous examples in which the introduction of expensive medical equipment into the developing world fail for lack of a basic understanding of the device operation, lack of spare parts and poor maintenance. This paper describes the development of a Fleisch pneumotachograph and cellphone based telespirometer that can easily be built from “junk box” medical and electronic components available in the developing world. This approach should introduce a sense of local ownership to the project as well as encouraging participation by the local electronics repair industry. Experimental results confirm that the forced expiratory flow data are reliably modulated onto an audio signal and transmitted by cellphone to a base station for examination by a district nurse or doctor. Flow measurement and data transmission accuracies are sufficiently good for remote diagnoses of chronic obstructive pulmonary disease.

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Section: Using the Cellphone Networkmentioning

confidence: 99%

A Telespirometer for the Developing World

Brooker

2020

Electronics

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“…Examples of intuitive‐level responses include heart rate, breathing rate, galvanic skin response, or evaluation of state anxiety at that moment. Data collection on in‐the‐moment intuitive processes can be facilitated by mobile surveys and new sensor technologies (Reeder & David, ). Intuitive‐level data may provide researchers a better understanding of the biopsychosocial variables occurring at the moment of decision and suggest novel intervention pathways.…”

Section: Two Minds Theorymentioning

confidence: 99%

“…Intuitive-level responses will be more predictive of actual behavior than narrative responses because narrative responses are only one consideration to future intuitive choices. When data are collected in the moment of a decision, the data likely reflect an Intuitive response (Cook, Schmiege, Starr, Carrington, & Bradley-Springer, 2017 (Reeder & David, 2016). Intuitive-level data may provide researchers a better understanding of the biopsychosocial variables occurring at the moment of decision and suggest novel intervention pathways.…”

Section: Implications For Nursingmentioning

confidence: 99%

Applying two minds theory to self‐management of Type 1 diabetes

Messer¹,

Sousa²,

Cook³

2019

Research in Nursing & Health

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Two minds theory (TMT) offers a new approach to changing health behavior. Here, TMT is applied to self‐management of Type 1 diabetes. TMT can be conceptualized as a cycle where a stimulus produces an immediate Intuitive system response leading to health behavior, followed by a conscious narrative system response that is temporally delayed. Narrative responses do not produce behaviors directly but instead lead to conscious beliefs about past events and behavioral intentions for the future, both of which become part of the material considered by the intuitive system in selecting future behaviors. Because of the temporal delay between intuitive behavior and narrative interpretation, and the nonconscious nature of intuitive thought, there is often a gap between intentions and behaviors. This has implications for nursing practice. First, nurses should consider that patient‐reported impressions of the past or future are fundamentally narrative system responses and understand that these may be less predictive of behavior than biopsychosocial measures that are more temporally immediate. Second, nurses can use TMT to inform new strategies for behavior change interventions. For diabetes self‐management, nurses can encourage individuals to leverage environmental cues to prompt self‐management (tricking the intuitive system), provide rewards for self‐management (training the intuitive system), or engage the narrative system via planning, reframing, or attention practices for healthier future decisions. Overall, the TMT addresses the gap between intentions and behavior and should be further developed to inform behavioral health interventions.

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“…Most of these platforms use RESTful API to provide users with collected data, and users can easily obtain their data through simple identification process and a URL. Owing to the evolution of wearable devices, there is a growing application of this technology to medical and healthcare studies using data obtained through wearable devices in place of medical devices [33]. Sensor technology coupled with wearable devices is already producing significant findings from studies, 3 Journal of Sensors and users can be provided with diverse healthcare services by integrating clinical data obtained from sensors on a cloud.…”

Section: Healthcare Platform and Analysismentioning

confidence: 99%

A Study of Prescriptive Analysis Framework for Human Care Services Based On CKAN Cloud

2018

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A number of sensor devices are widely distributed and used today owing to the accelerated development of IoT technology. In particular, this technological advancement has allowed users to carry IoT devices with more convenience and efficiency. Based on the IoT sensor data, studies are being actively carried out to recognize the current situation or to analyze and predict future events. However, research for existing smart healthcare services is focused on analyzing users' behavior from single sensor data and is also focused on analyzing and diagnosing the current situation of the users. Therefore, a method for effectively managing and integrating a large amount of IoT sensor data has become necessary, and a framework considering data interoperability has become necessary. In addition, an analysis framework is needed not only to provide the analysis of the users' environment and situation from the integrated data, but also to provide guide information to predict future events and to take appropriate action by users. In this paper, we propose a prescriptive analysis framework using a 5W1H method based on CKAN cloud. Through the CKAN cloud environment, IoT sensor data stored in individual CKANs can be integrated based on common concepts. As a result, it is possible to generate an integrated knowledge graph considering interoperability of data, and the underlying data is used as the base data for prescriptive analysis. In addition, the proposed prescriptive analysis framework can diagnose the situation of the users through analysis of user environment information and supports users' decision making by recommending the possible behavior according to the coming situation of the users. We have verified the applicability of the 5W1H prescriptive analysis framework based on the use case of collecting and analyzing data obtained from various IoT sensors.

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Health at hand: A systematic review of smart watch uses for health and wellness

Cited by 315 publications

References 20 publications

A Telespirometer for the Developing World

A Telespirometer for the Developing World

Applying two minds theory to self‐management of Type 1 diabetes

A Study of Prescriptive Analysis Framework for Human Care Services Based On CKAN Cloud

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