Objectives: The new wave of wireless technologies, fitness trackers, and body sensor devices can have great impact on healthcare systems and the quality of life. However, there have not been enough studies to prove the accuracy and precision of these trackers. The objective of this study was to evaluate the accuracy, precision, and overall performance of seventeen wearable devices currently available compared with direct observation of step counts and heart rate monitoring.
Methods: Each participant in this study used three accelerometers at a time, running the three corresponding applications of each tracker on an Android or iOS device simultaneously. Each participant was instructed to walk 200, 500, and 1,000 steps. Each set was repeated 40 times. Data was recorded after each trial, and the mean step count, standard deviation, accuracy, and precision were estimated for each tracker. Heart rate was measured by all trackers (if applicable), which support heart rate monitoring, and compared to a positive control, the Onyx Vantage 9590 professional clinical pulse oximeter.
Results: The accuracy of the tested products ranged between 79.8% and 99.1%, while the coefficient of variation (precision) ranged between 4% and 17.5%. MisFit Shine showed the highest accuracy and precision (along with Qualcomm Toq), while Samsung Gear 2 showed the lowest accuracy, and Jawbone UP showed the lowest precision. However, Xiaomi Mi band showed the best package compared to its price.
Conclusions: The accuracy and precision of the selected fitness trackers are reasonable and can indicate the average level of activity and thus average energy expenditure.
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http://dx.doi.org/10.4258/hir.2015.21.4.315 | DOI Listing |
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Department of Immuno-Oncology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, 510080, China.
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Pediatric Dentistry Department, Faculty of Dentistry, Başkent University, 06490, Ankara, Turkey.
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Department of Management Information Systems, National Chung Hsing University, Taichung, 402, Taiwan.
Background: miRNAs (microRNAs) are endogenous RNAs with lengths of 18 to 24 nucleotides and play critical roles in gene regulation and disease progression. Although traditional wet-lab experiments provide direct evidence for miRNA-disease associations, they are often time-consuming and complicated to analyze by current bioinformatics tools. In recent years, machine learning (ML) and deep learning (DL) techniques are powerful tools to analyze large-scale biological data.
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January 2025
Department of Nuclear Medicine (PET Center), Key Laboratory of Biological Nanotechnology of National Health Commission, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan, 410000, China.
Purpose: The accurate assessment of inflammatory activity of the extraocular muscles (EOMs) in thyroid associated ophthalmopathy (TAO) is crucial for formulating subsequent treatment strategies and prognostic judgments. This study aims to explore the efficacy of using [Ga]DOTATATE PET/CT to assess the inflammatory activity of EOMs in TAO patients.
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Sci Rep
January 2025
Department of Basic Sciences, Faculty of Dentistry, Universidad de Antioquia U de A, Medellín, 050010, Colombia.
The NLRP3 inflammasome, regulated by TLR4, plays a pivotal role in periodontitis by mediating inflammatory cytokine release and bone loss induced by Porphyromonas gingivalis. Periodontal disease creates a hypoxic environment, favoring anaerobic bacteria survival and exacerbating inflammation. The NLRP3 inflammasome triggers pyroptosis, a programmed cell death that amplifies inflammation and tissue damage.
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