Traditionally, e-Health solutions were located at the point of care (PoC), while the new ubiquitous user-centered paradigm draws on standard-based personal health devices (PHDs). Such devices place strict constraints on computation and battery efficiency that encouraged the International Organization for Standardization/IEEE11073 (X73) standard for medical devices to evolve from X73PoC to X73PHD. In this context, low-voltage low-power (LV-LP) technologies meet the restrictions of X73PHD-compliant devices. Since X73PHD does not approach the software architecture, the accomplishment of an efficient design falls directly on the software developer. Therefore, computational and battery performance of such LV-LP-constrained devices can even be outperformed through an efficient X73PHD implementation design. In this context, this paper proposes a new methodology to implement X73PHD into microcontroller-based platforms with LV-LP constraints. Such implementation methodology has been developed through a patterns-based approach and applied to a number of X73PHD-compliant agents (including weighing scale, blood pressure monitor, and thermometer specializations) and microprocessor architectures (8, 16, and 32 bits) as a proof of concept. As a reference, the results obtained in the weighing scale guarantee all features of X73PHD running over a microcontroller architecture based on ARM7TDMI requiring only 168 B of RAM and 2546 B of flash memory.
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http://dx.doi.org/10.1109/TITB.2011.2134861 | DOI Listing |
Mil Med
January 2025
Department of Rheumatology, VA Medical Center Memphis, TN 38104, USA.
Introduction: Patients with chronic inflammatory diseases are often treated with pharmacologic therapies that target the immune system and have an increased risk of infection. These risks can be reduced by vaccination against common pathogens. This quality improvement project aimed to increase pneumococcal and herpes zoster vaccination rates in patients with chronic inflammatory disease on biologic immunosuppressive therapy.
View Article and Find Full Text PDFAnn Biomed Eng
January 2025
Carnegie Applied Rugby Research (CARR) Centre, Carnegie School of Sport, Leeds Beckett University, Leeds, UK.
Purpose: Head acceleration events (HAEs) are a growing concern in contact sports, prompting two rugby governing bodies to mandate instrumented mouthguards (iMGs). This has resulted in an influx of data imposing financial and time constraints. This study presents two computational methods that leverage a dataset of video-coded match events: cross-correlation synchronisation aligns iMG data to a video recording, by providing playback timestamps for each HAE, enabling analysts to locate them in video footage; and post-synchronisation event matching identifies the coded match event (e.
View Article and Find Full Text PDFInt J Colorectal Dis
January 2025
Department of Pathomorphology, Medical University of Gdańsk, Gdańsk, Poland.
Purpose: Liver and lung metastases demonstrate distinct biological, particularly immunological, characteristics. We investigated whether preoperative complete blood count (CBC) parameters, which may reflect the immune system condition, predict early dissemination to the liver and lungs in colorectal cancer (CRC).
Methods: In this retrospective single-centre study, we included 268 resected CRC cases with complete 2-year follow-up and analysed preoperative CBC for association with early liver or lung metastasis development.
Psychol Serv
January 2025
National Center for PTSD, Dissemination and Training Division, VA Palo Alto Health Care System.
The U.S. Department of Veterans Affairs (VA) developed evidence-informed mental health mobile applications (MH apps) to supplement treatment and serve as self-care resources for veterans.
View Article and Find Full Text PDFOnline J Public Health Inform
January 2025
Bureau of Communicable Disease, New York City Department of Health and Mental Hygiene, Long Island City, NY, United States.
Background: Applying nowcasting methods to partially accrued reportable disease data can help policymakers interpret recent epidemic trends despite data lags and quickly identify and remediate health inequities. During the 2022 mpox outbreak in New York City, we applied Nowcasting by Bayesian Smoothing (NobBS) to estimate recent cases, citywide and stratified by race or ethnicity (Black or African American, Hispanic or Latino, and White). However, in real time, it was unclear if the estimates were accurate.
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