A novel wearable smart patch can monitor various aspects of physical activity, including the dynamics of running, but like any new device developed for such applications, it must first be tested for validity. Here, we compare the step rate while running in place as measured by this smart patch to the corresponding values obtained utilizing ''gold standard'' MEMS accelerometers in combination with bilateral force plates equipped with HBM load cells, as well as the values provided by a three-dimensional motion capture system and the Garmin Dynamics Running Pod. The 15 healthy, physically active volunteers (age = 23 ± 3 years; body mass = 74 ± 17 kg, height = 176 ± 10 cm) completed three consecutive 20-s bouts of running in place, starting at low, followed by medium, and finally at high intensity, all self-chosen. Our major findings are that the rates of running in place provided by all four systems were valid, with the notable exception of the fast step rate as measured by the Garmin Running Pod. The lowest mean bias and LoA for these measurements at all rates were associated consistently with the smart patch.
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http://dx.doi.org/10.3390/s22134897 | DOI Listing |
J Med Chem
January 2025
Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, Copenhagen DK-2100, Denmark.
GABA receptors (GABARs) are the major elements of inhibitory neurotransmission in the central nervous system (CNS). They are established targets for regulation by endogenous brain neuroactive steroids (NASs) such as pregnanolone. However, the complexity of de novo synthesis of NAS derivatives has hindered attempts to circumvent the principal limitations of using endogenous NASs, including selectivity and limited oral bioavailability.
View Article and Find Full Text PDFMikrochim Acta
January 2025
Department of Chemistry, Indian Institute of Technology Palakkad, Palakkad, Kerala, 678557, India.
Compared with previous decades, healthcare has emerged as a key global concern in light of the recurrent outbreak of pandemics. The initial stage in the provision of healthcare involves the process of diagnosis. Countries worldwide advocate for healthcare research due to its efficacy and capacity to assist diverse populations.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Department of Laboratory Medicine, School of Chemical Science and Engineering, Shanghai Tenth People's Hospital of Tongji University, Tongji University, Shanghai, 200092, P. R. China.
The healing of bacterial biofilm-infected wounds is a complex process, and the construction of emerging therapeutic modalities that regulate the microenvironment to magnify therapeutic effects and reduce biotoxicity is still highly challenging. Herein, an engineered microneedle (MN) patch is reported to mediate the efficient delivery of black phosphorus nanosheets (BP NSs) and copper peroxide nanodots (CP NDs) for dual nanodynamic sterilization and methicillin-resistant staphylococcus aureus (MRSA)-infected wound healing. Results demonstrate that the system can eliminate biofilm, reduce cytotoxicity, promote angiogenesis and tissue regeneration by the multiple advantages of chemodynamic therapy (CDT), enhanced photodynamic therapy (PDT), and improved degradation process from BP NSs to phosphate for promoting cell proliferation.
View Article and Find Full Text PDFPhysiol Meas
January 2025
University of Duisburg-Essen, Bismarckstr. 81 (BB), Duisburg, 47057, GERMANY.
Objective: In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes real-time data analysis on the patch itself.
Approach: This paper introduces a novel Python package, tinyHLS (High Level Synthesis), designed
to address these challenges by converting Python-based AI models into platform-independent hardware description language (HDL) code accelerators.
Vis Comput Ind Biomed Art
January 2025
Faculty of Sciences, Sfax, Tunisia.
The vision transformer (ViT) architecture, with its attention mechanism based on multi-head attention layers, has been widely adopted in various computer-aided diagnosis tasks due to its effectiveness in processing medical image information. ViTs are notably recognized for their complex architecture, which requires high-performance GPUs or CPUs for efficient model training and deployment in real-world medical diagnostic devices. This renders them more intricate than convolutional neural networks (CNNs).
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