IEEE J Biomed Health Inform
Published: May 2014
Enabling large-scale monitoring and classification of a range of motion activities is of primary importance due to the need by healthcare and fitness professionals to monitor exercises for quality and compliance. Past work has not fully addressed the unique challenges that arise from scaling. This paper presents a novel end-to-end system solution to some of these challenges. The system is built on the prescription-based context-driven activity classification methodology. First, we show that by refining the definition of context, and introducing the concept of scenarios, a prescription model can provide personalized activity monitoring. Second, through a flexible architecture constructed from interface models, we demonstrate the concept of a context-driven classifier. Context classification is achieved through a classification committee approach, and activity classification follows by means of context specific activity models. Then, the architecture is implemented in an end-to-end system featuring an Android application running on a mobile device, and a number of classifiers as core classification components. Finally, we use a series of experimental field evaluations to confirm the expected benefits of the proposed system in terms of classification accuracy, rate, and sensor operating life.
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http://dx.doi.org/10.1109/JBHI.2013.2282812 | DOI Listing |
Adv Clin Chem
January 2025
School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, Republic of Korea; Department of Integrated Biomedical and Life Science, Korea University, Seoul, Republic of Korea; BK21FOUR R&E Center for Learning Health Systems, Korea University, Seoul, Republic of Korea; L-HOPE Program for Community-Based Total Learning Health Systems, Korea University, Seoul, Republic of Korea. Electronic address:
The advent of multiomics has ushered in a new era of cancer research characterized by integrated genomic, transcriptomic and proteomic analysis to unravel the complexities of cancer biology and facilitate the discovery of novel biomarkers. This chapter provides a comprehensive overview of the concept of multiomics, detailing the significant advances in the underlying technologies and their contributions to our understanding of cancer. It delves into the evolution of genomics and transcriptomics, breakthroughs in proteomics, and overarching progress in multiomic methodologies, highlighting their collective impact on cancer biomarker discovery.
View Article and Find Full Text PDFJ Psychiatr Res
January 2025
Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. Electronic address:
Background: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to explore the functional changes and interrelationships of multiple brain networks on a millisecond scale. This study aimed to explore the pathological changes of whole-brain functional networks in patients with obsessive-compulsive disorders (OCD) through microstate analysis and further to explore its potential value as an auxiliary diagnostic index.
Methods: Forty-eight OCD patients (33 with more than moderate anxiety symptoms, 15 with mild anxiety symptoms) and 52 healthy controls (HCs) were recruited.
Microb Genom
January 2025
Departamento de Bioqumica, Instituto de Qumica, Universidade de So Paulo, So Paulo, SP, Brazil.
The São Paulo state citrus belt in Brazil is a major citrus production region. Since at least 1957, citrus plantations in this region have been affected by citrus canker, an economically damaging disease caused by subsp. ().
View Article and Find Full Text PDFCureus
December 2024
Anna and Peter Brojde Lung Cancer Center, Sir Mortimer B. Davis Jewish General Hospital, McGill University, Montreal, CAN.
Background A minority of patients receiving stereotactic body radiation therapy (SBRT) for non-small cell lung cancer (NSCLC) are not good responders. Radiomic features can be used to generate predictive algorithms and biomarkers that can determine treatment outcomes and stratify patients to their therapeutic options. This study investigated and attempted to validate the radiomic and clinical features obtained from early-stage and oligometastatic NSCLC patients who underwent SBRT, to predict local response.
View Article and Find Full Text PDFNarra J
December 2024
Department of Epidemiology, Biostatistics, Population Studies and Health Promotion, Faculty of Public Health, Universitas Airlangga, Surabaya, Indonesia.
Patients with generalized myasthenia gravis (MG) often show restrictive spirometry results. Although regular exercise and physical fitness are linked to better respiratory function, there is limited research assessing the effects of aerobic exercise on lung function in MG patients. The aim of this study was to analyze the effect of low-intensity aerobic exercise using a cycle ergometer on lung function parameters in MG patients.
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