Wearable technology including sensors, sensor networks, and the associated devices have opened up space in a variety of applications [...].
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| http://dx.doi.org/10.3390/bios12060396 | DOI Listing |
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Enhancing artificial intelligence-driven sleep apnea diagnosis: The critical importance of input signal proficiency with a focus on mandibular jaw movements.
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December 2024
HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France.
Purpose: This review aims to highlight the pivotal role of the mandibular jaw movement (MJM) signal in advancing artificial intelligence (AI)-powered technologies for diagnosing obstructive sleep apnea (OSA).
Methods: A scoping review was conducted to evaluate various aspects of the MJM signal and their contribution to improving signal proficiency for users.
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Intra- and inter-channel deep convolutional neural network with dynamic label smoothing for multichannel biosignal analysis.
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March 2025
Department of Mechanical Engineering and Intelligent System, the University of Electro-Communications, Tokyo, Japan; Center for Neuroscience and Biomedical Engineering, the University of Electro-Communications, Tokyo, Japan. Electronic address:
Article Synopsis
- Efficient processing of multichannel biosignals is vital for healthcare and human-machine interaction, but existing methods face challenges in feature extraction, model complexity, and generalization to new data.
- The proposed solution is a 1D-based deep intra and inter channel (I2C) convolutional neural network that improves feature extraction while reducing the number of parameters needed.
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Recent Advances in Nanomaterial-Based Biosignal Sensors.
Small
January 2025
Applied Nano and Thermal Science Lab, Department of Mechanical Engineering, Seoul National University, Seoul, 08826, Republic of Korea.
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Study protocol for a consortium linking health medical records, biospecimens, and biosignals in Korean patients with acute kidney injury (LINKA cohort).
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Department of Internal Medicine, Hallym University Sacred Heart Hospital, Anyang, Republic of Korea.
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- The study examines the progression of acute kidney injury (AKI) to acute kidney disease (AKD) or chronic kidney disease (CKD) and aims to identify biomarkers and personalized treatments.
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A Biometric Identification for Multi-Modal Biomedical Signals in Geriatric Care.
Sensors (Basel)
October 2024
School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong 643000, China.
With the acceleration of global population aging, the elderly have an increasing demand for home care and nursing institutions, and the significance of health prevention and management of the elderly has become increasingly prominent. In this context, we propose a biometric recognition method for multi-modal biomedical signals. This article focuses on three key signals that can be picked up by wearable devices: ECG, PPG, and breath (RESP).
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