A scalable cloud Platform for Active healthcare monitoring applications
- Authors: Balasubramanian, Venki , Stranieri, Andrew
- Date: 2015
- Type: Text , Conference paper
- Relation: 2014 IEEE Conference on e-Learning, e-Management and e-Services, IC3e 2014; Melbourne, Australia; 10th-12th December 2014 p. 93-98
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- Description: Continuous, remote monitoring of patients using wearable sensors can facilitate early detection of many conditions and can help to manage the growing healthcare crisis worldwide. A remote patient monitoring application consists of many emerging services such as wireless wearable sensor configuration, patient registration and authentication, collaborative consultation of doctors, storage and maintenance of electronic health record. The provision of these services requires the development and maintenance of a remote healthcare monitoring application (HMA) that includes a body area wireless sensor network (BASWN) and Health Applications (HA) to detect specific health issues. In addition, the deployment of HMAs for different hospitals is not easily scalable owing to the heterogeneous nature of hardware and software involved. Cloud computing overcomes this aspect by allowing simple and easy maintenance of ICT infrastructure. In this work, we report a real-time-like cloud based architecture known as Assistive Patient monitoring cloud Platform for Active healthcare applications (AppA) using a delegate pattern. The built AppA is highly scalable and capable of spawning new instances based on monitoring requirements from the health care providers, and are aligned with scalable economic models. © 2014 IEEE.
AppA : Assistive patient monitoring cloud platform for active healthcare applications
- Authors: Balasubramanian, Venki , Stranieri, Andrew , Kaur, Ranjit
- Date: 2015
- Type: Text , Conference paper
- Relation: 9th International Conference on Ubiquitous Information Management and Communication, ACM IMCOM 2015; Bali, Indonesia; 8th-10th January 2015
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- Description: Continuous, remote monitoring of patients using wearable sensors can facilitate early detection of many conditions and can help to manage the growing healthcare crisis worldwide. A remote patient monitoring application consists of many emerging services such as wireless wearable sensor configuration, patient registration and authentication, collaborative consultation of doctors, storage and maintenance of electronic health record. The provision of these services requires the development and maintenance of a remote healthcare monitoring application (HMA) that includes a body area wireless sensor network (BASWN) and Health Applications (HA) to detect specific health issues. In addition, the deployment of HMAs for different hospitals is not easily scalable owing to the heterogeneous nature of hardware and software involved. Cloud computing overcomes this aspect by allowing simple and easy maintenance of ICT infrastructure. In this work, we report a realtime- like cloud based architecture known as Assistive Patient monitoring cloud Platform for Active healthcare applications (AppA) using a delegate pattern. The built AppA is highly scalable and capable of spawning new instances based on the monitoring requirements from the health care providers, and is aligned with scalable economic models.
Wearable sensor technology to predict core body temperature : a systematic review
- Authors: Dolson, Conor , Harlow, Ethan , Phelan, Dermot , Gabbett, Tim , Gaal, Benjamin , McMellen, Christopher , Geletka, Benjamin , Calcei, Jacob , Voos, James , Seshadri, Dhruv
- Date: 2022
- Type: Text , Journal article , Review
- Relation: Sensors Vol. 22, no. 19 (2022), p.
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- Description: Heat-related illnesses, which range from heat exhaustion to heatstroke, affect thousands of individuals worldwide every year and are characterized by extreme hyperthermia with the core body temperature (CBT) usually > 40 °C, decline in physical and athletic performance, CNS dysfunction, and, eventually, multiorgan failure. The measurement of CBT has been shown to predict heat-related illness and its severity, but the current measurement methods are not practical for use in high acuity and high motion settings due to their invasive and obstructive nature or excessive costs. Noninvasive predictions of CBT using wearable technology and predictive algorithms offer the potential for continuous CBT monitoring and early intervention to prevent HRI in athletic, military, and intense work environments. Thus far, there has been a lack of peer-reviewed literature assessing the efficacy of wearable devices and predictive analytics to predict CBT to mitigate heat-related illness. This systematic review identified 20 studies representing a total of 25 distinct algorithms to predict the core body temperature using wearable technology. While a high accuracy in prediction was noted, with 17 out of 18 algorithms meeting the clinical validity standards. few algorithms incorporated individual and environmental data into their core body temperature prediction algorithms, despite the known impact of individual health and situational and environmental factors on CBT. Robust machine learning methods offer the ability to develop more accurate, reliable, and personalized CBT prediction algorithms using wearable devices by including additional data on user characteristics, workout intensity, and the surrounding environment. The integration and interoperability of CBT prediction algorithms with existing heat-related illness prevention and treatment tools, including heat indices such as the WBGT, athlete management systems, and electronic medical records, will further prevent HRI and increase the availability and speed of data access during critical heat events, improving the clinical decision-making process for athletic trainers and physicians, sports scientists, employers, and military officers. © 2022 by the authors.
Wearable technology in the sports medicine clinic to guide the return-to-play and performance protocols of athletes following a COVID-19 diagnosis
- Authors: Seshadri, Dhruv , Harlow, Ethan , Thom, Mitchell , Emery, Michael , Phelan, Dermot , Hsu, Jeffrey , Düking, Peter , De Mey, Kristof , Sheehan, Joseph , Geletka, Benjamin , Flannery, Robert , Calcei, Jacob , Karns, Michael , Salata, Michael , Gabbett, Tim , Voos, James
- Date: 2023
- Type: Text , Journal article , Review
- Relation: Digital Health Vol. 9, no. (2023), p.
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- Description: The coronavirus disease 2019 (COVID-19) pandemic has enabled the adoption of digital health platforms for self-monitoring and diagnosis. Notably, the pandemic has had profound effects on athletes and their ability to train and compete. Sporting organizations worldwide have reported a significant increase in injuries manifesting from changes in training regimens and match schedules resulting from extended quarantines. While current literature focuses on the use of wearable technology to monitor athlete workloads to guide training, there is a lack of literature suggesting how such technology can mediate the return to sport processes of athletes infected with COVID-19. This paper bridges this gap by providing recommendations to guide team physicians and athletic trainers on the utility of wearable technology for improving the well-being of athletes who may be asymptomatic, symptomatic, or tested negative but have had to quarantine due to a close exposure. We start by describing the physiologic changes that occur in athletes infected with COVID-19 with extended deconditioning from a musculoskeletal, psychological, cardiopulmonary, and thermoregulatory standpoint and review the evidence on how these athletes may safely return to play. We highlight opportunities for wearable technology to aid in the return-to-play process by offering a list of key parameters pertinent to the athlete affected by COVID-19. This paper provides the athletic community with a greater understanding of how wearable technology can be implemented in the rehabilitation process of these athletes and spurs opportunities for further innovations in wearables, digital health, and sports medicine to reduce injury burden in athletes of all ages. © The Author(s) 2023.
Motivational strategies to improve adherence to physical activity in breast cancer survivors : a systematic review and meta-analysis
- Authors: Pudkasam, Supa , Feehan, Jack , Talevski, Jason , Vingrys, Kristina , Polman, Remco , Chinlumprasert, Nanthaphan , Stojanovska, Lily , Apostolopoulos, Vasso
- Date: 2021
- Type: Text , Journal article
- Relation: Maturitas Vol. 152, no. (2021), p. 32-47
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- Description: Two behavioral change-based strategies for promoting adherence to physical activity (PA) suggested to have the greatest potential are the pedometer and Motivational Interviewing (MI). However, there are no comparisons between these two strategies identifying which one is more effective for improving PA adherence. This systematic review and meta-analysis aimed to determine which PA motivation strategy is more effective for promoting adherence to self-directed PA in female breast cancer survivors. Studies implementing self-directed PA which used a step tracker and/or MI for motivation in female breast cancer survivors were identified from the following databases at two timepoints, September 2019 and June 2020: CENTRAL, PubMed, CINAHL, PsycINFO, and Sportdiscuss. Sixteen randomized controlled trials (RCTs) were selected for data extraction, whereas ten RCTs were included in meta-analysis. Meta-analysis was performed on pooled data to estimate the standardized mean differences in PA duration and step count, and 95% confidence intervals. The number of participants meeting PA recommendations was also analyzed. Subgroup analysis was performed for three motivational strategies (pedometer combined with counselling, with print material or with motivational interviewing). Meta-analysis showed that pedometer combined with another intervention has a small effect on step count (p = 0.03) and a moderate effect on duration of moderate-vigorous physical activity (MVPA) (p = <0.0001) compared to controls. Additionally, motivational strategies increase the number of participants who meet a PA goal (p = 0.005). The findings of this review endorse the use of a step tracker combined with counselling, print material or MI based on behavioral change theory. This approach provided the most consistent positive effect on adherence to self-directed PA among breast cancer survivors. Future studies should evaluate differences between measures of adherence to self-directed PA, to identify the best motivation strategy for improving patient adherence and health outcomes. Systematic review registration: PROSPERO Registration number CRD42020148542 © 2021