A method of diagnosing neural-muscular diseases via Fourier spectral analysis is presented in the paper. Application of this analysis allowed for obtaining a series of spectral features. This resulted in a selection of a discriminant ensuring the best sensitivity of the new method, better than the QEMG method used in the clinical practice. Software implementation of the spectral discriminant enabled creation of a computer diagnostic tool supporting EMG examination. The method is fully automated.
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http://dx.doi.org/10.1109/IEMBS.2008.4649356 | DOI Listing |
Front Bioeng Biotechnol
January 2025
Faculty of Physical Education-Abo Qir, Alexandria University, Alexandria, Egypt.
Objective: This study investigated upper limb kinematics and muscle co-activation in wheelchair tennis players during the forehand stroke. By analyzing linear and angular kinematic variables alongside muscle co-activation patterns, the study aimed to provide insights into the biomechanical mechanisms supporting forehand stroke performance.
Method: Fifteen professional male wheelchair tennis players (height: 163.
J Neurosci Methods
January 2025
School of Electrical and Computer Engineering, Gallogly College of Engineering, University of Oklahoma, Norman, OK 73019, USA.
Background: Recent advances in multimodal signal analysis enable the identification of subtle drug-induced anomalies in sleep that traditional methods often miss.
New Method: We develop and introduce the Dynamic Representation of Multimodal Activity and Markov States (DREAMS) framework, which embeds explainable artificial intelligence (XAI) techniques to model hidden state transitions during sleep using tensorized EEG, EMG, and EOG signals from 22 subjects across three age groups (18-29, 30-49, and 50-66 years). By combining Tucker decomposition with probabilistic Hidden Markov Modeling, we quantified age-specific, temazepam-induced hidden states and significant differences in transition probabilities.
Physiol Meas
January 2025
Department of Electrical Engineering, KU Leuven, Kasteelpark Arenberg 10 postbus 2440 3001 LEUVEN Belgium, Leuven, Flanders, 3000, BELGIUM.
Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding sleep disorders. This work introduces PhysioEx, a Python library designed to support the analysis of sleep stages using deep learning and Explainable AI (XAI). Approach: PhysioEx provides an extensible and modular API for standardizing and automating the sleep staging pipeline, covering data preprocessing, model training, testing, fine-tuning, and explainability.
View Article and Find Full Text PDFBMC Musculoskelet Disord
January 2025
The Nick Davey Laboratory, Division of Surgery, Department of Surgery and Cancer, Faculty of Medicine, Sir Michael Uren Hub, Imperial College London, White City Campus, 86 Wood Lane, London, W12 0BZ, UK.
Background: People with joint hypermobility have excessive joint flexibility, which is more common in young women. The people with symptomatic hypermobility report poor balance and even falls. This scoping review aims to identify and map the available evidence related to balance and falling in adults with joint hypermobility to support research planning and ideas for treatment direction.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems.
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