Development of an innovative mHealth platform for remote physical activity monitoring and health coaching of cardiac rehabilitation patients

Kitsiou, Spyros; Thomas, Manu Mathew; Marai, G. Elisabeta; Maglaveras, Nicos; Kondos, George T.; Arena, Ross; Gerber, Ben S.

doi:10.1109/bhi.2017.7897223

Cited by 49 publications

(42 citation statements)

References 23 publications

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“…Such requirements go beyond usability and user experience goals: 1) Scalability influences more than just visual scalability (would we be able to store and process on the fly a petascale dataset? [28, 33]); 2) Privacy can affect the publication of a project—several interdisciplinary projects nearly-failed publication because data was revealed to be private, sensitive, or proprietary [23, 51]; 3) Certain scientific user groups have a strong preference for desktop applications (as opposed to web-based) [58], and other groups expect cross-platform compatibility [46]. All the factors above influence the design and outcome of a project.…”

Section: Network Modelmentioning

confidence: 99%

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Marai

2018

IEEE Trans. Visual. Comput. Graphics

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Although visualization design models exist in the literature in the form of higher-level methodological frameworks, these models do not present a clear methodological prescription for the domain characterization step. This work presents a framework and end-to-end model for requirements engineering in problem-driven visualization application design. The framework and model are based on the activity-centered design paradigm, which is an enhancement of human-centered design. The proposed activity-centered approach focuses on user tasks and activities, and allows an explicit link between the requirements engineering process with the abstraction stage—and its evaluation—of existing, higher-level visualization design models. In a departure from existing visualization design models, the resulting model: assigns value to a visualization based on user activities; ranks user tasks before the user data; partitions requirements in activity-related capabilities and nonfunctional characteristics and constraints; and explicitly incorporates the user workflows into the requirements process. A further merit of this model is its explicit integration of functional specifications, a concept this work adapts from the software engineering literature, into the visualization design nested model. A quantitative evaluation using two sets of interdisciplinary projects supports the merits of the activity-centered model. The result is a practical roadmap to the domain characterization step of visualization design for problem-driven data visualization. Following this domain characterization model can help remove a number of pitfalls that have been identified multiple times in the visualization design literature.

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Section: Network Modelmentioning

confidence: 99%

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Marai

2018

IEEE Trans. Visual. Comput. Graphics

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“…Other approaches based on similar devices, such as the Fitbit [28] or Garmin [45], could be extended to develop embedded applications providing real-time monitoring during rehabilitation sessions.…”

Section: Resultsmentioning

confidence: 99%

“…The wearable device is presented as a data collector without providing a real-time feedback of sessions. In [28], Fitbit wearable sensor devices, and personalized coaching with SMS are proposed. In the same way, an ad hoc application was not embedded in the wearable device.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Monitoring in Home-Based Cardiac Rehabilitation Using Wrist-Worn Heart Rate Devices

Medina-Quero

Olmo

Aguilera

et al. 2017

Sensors

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Cardiac rehabilitation is a key program which significantly reduces the mortality in at-risk patients with ischemic heart disease; however, there is a lack of accessibility to these programs in health centers. To resolve this issue, home-based programs for cardiac rehabilitation have arisen as a potential solution. In this work, we present an approach based on a new generation of wrist-worn devices which have improved the quality of heart rate sensors and applications. Real-time monitoring of rehabilitation sessions based on high-quality clinical guidelines is embedded in a wearable application. For this, a fuzzy temporal linguistic approach models the clinical protocol. An evaluation based on cases is developed by a cardiac rehabilitation team.

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“…18,19 To ease this burden while improving the care process, Ibrahim et al 20 developed a multiagent platform to automate the process of collecting user-provided clinical outcome measures without clinician intervention. Health coaching approaches are widely adopted in various health domains to monitor cardiac rehabilitation, 21 promote physical activity at home for elderly, 22 medication adherence, 16 assist pregnant women, 23,24 promote healthy diet, [12][13][14] support individuals with spinal cord injury, 25 and assist with hand therapy. 26 Health coaching systems may vary in their techniques to tackle health issues.…”

Section: Related Workmentioning

confidence: 99%

Assistive Conversational Agent for Health Coaching: A Validation Study

2019

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With increasing physicians' workload and patients' needs for care, there is a need for technology that facilitates physicians work and performs continues follow-up with patients. Existing approaches focus merely on improving patient's condition, and none have considered managing physician's workload. This paper presents an initial evaluation of a conversational agent assisted coaching platform intended to manage physicians' fatigue and provide continuous follow-up to patients. We highlight the approach adapted to build the chatbot dialogue and the coaching platform. We will particularly discuss the activity recommender algorithms used to suggest insights about patients' condition and activities based on previously collected data. The paper makes three contributions: (1) present the conversational agent as an assistive virtual coach,(2) decrease physicians workload and continuous follow up with patients, all by handling some repetitive physician tasks and performing initial follow up with the patient, (3) present the activity recommender that tracks previous activities and patient information and provides useful insights about possible activity and patient match to the coach. Future work focuses on integrating the recommender model with the CoachAI platform and test the prototype with patient's in collaboration with an ambulatory clinic.

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Development of an innovative mHealth platform for remote physical activity monitoring and health coaching of cardiac rehabilitation patients

Cited by 49 publications

References 23 publications

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Activity-Centered Domain Characterization for Problem-Driven Scientific Visualization

Real-Time Monitoring in Home-Based Cardiac Rehabilitation Using Wrist-Worn Heart Rate Devices

Assistive Conversational Agent for Health Coaching: A Validation Study

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