BIOART - BIOsignal Analysis for Rehabilitation and Therapy
El Grup aplica tècniques d'enginyeria al camp mèdic per millorar els processos de rehabilitació i les teràpies clíniques. S'avaluen i monitoritzen mitjançant el processament de biosenyals multicanal (electromiogràfics, electroencefalogràfics, etc.) i l'anàlisi del sistema respiratori. Els algorismes es dissenyen eficientment per tal que les tècniques es puguin adaptar i aplicar a estudis respiratoris, neuromusculars i neurològics. Els objectius són:
1) Avaluació de l'activitat cerebral per ajudar al diagnòstic de malalties neurodegeneratives i a l'eficàcia del tractament ja sigui farmacològic o no.
2) Desenvolupar eines quantitatives per monitoritzar l'activitat muscular i fatigabilitat, així com estratègies de control del sistema nerviós central (SNC) per a l'activació muscular durant exercicis de rehabilitació.
3) Noves eines d'ajut al metge per a la ventilació assistida de malalts amb insuficiència respiratòria Aguda i monitorització de les malalties ventilatòries mitjançant músculs respiratoris.
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Articles de revista [89]
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AML-DECODER: advanced machine learning for HD-sEMG signal classification—decoding lateral epicondylitis in forearm muscles
(2024-10-10)
Article
Open AccessBackground: Innovative algorithms for wearable devices and garments are critical for diagnosing and monitoring disease (such as lateral epicondylitis (LE)) progression. LE affects individuals across various professions and ... -
EEG connectivity patterns in response to gaming and learning-based cognitive stimulations in Rett syndrome
(Elsevier, 2024-07)
Article
Open AccessBackground: Functional connectivity is scarcely studied in Rett syndrome (RTT). Explorations revealed associations between RTT's clinical, genetic profiles, and coherence measures, highlighting an unexplored frontier in ... -
Prevention of cardiometabolic syndrome in children and adolescents using machine learning and noninvasive factors: the CASPIAN-V study
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-09-13)
Article
Open AccessCardiometabolic syndrome (CMS) is a growing concern in children and adolescents, marked by obesity, hypertension, insulin resistance, and dyslipidemia. This study aimed to predict CMS using machine learning based on data ... -
Novel frequency-based approach for detection of steady-state visual evoked potentials for realization of practical brain computer interfaces
(Taylor & Francis Group, 2022-03-13)
Article
Open AccessVarious algorithms for recognizing Steady-State Visual Evoked Potentials have been proposed over the last decade for realizing Brain-Computer Interfaces. However, frequency-domain techniques aside from classical FFT have ... -
Evaluation of connectivity measures to identify seizure onset and propagation zones in refractory epilepsy: a case study with two different post- surgical outcomes
(2023)
Conference lecture
Restricted access - publisher's policyHigh Frequency Oscillations (HFO) have been found very useful in refractory epilepsy. They have been used to identify the epileptogenic zone and as a promising clinical biomarker for presurgical evaluation in childhood ... -
Individualized time windows enhance TMS-EEG signal characterization and improve assessment of cortical function in schizophrenia
(2024-07-06)
Article
Open AccessTranscranial magnetic stimulation and electroencephalography (TMS-EEG) recordings are crucial to directly assess cortical excitability and inhibition in a non-invasive and task-free manner. TMS-EEG signals are characterized ... -
Semi-supervised active transfer learning for fetal ECG arrhythmia detection
(Elsevier, 2023)
Article
Open AccessDeep learning has demonstrated excellent results for ECG anomaly detection, wherein most approaches used supervised learning. The requirement of thousands of manually annotated samples is a concern for state-of-the-art ... -
The burden of type 1 and type 2 diabetes among adolescents and young adults in 24 Western European countries, 1990–2019: Results from the Global Burden of Disease Study 2019
(Frontiers Media SA, 2024-02-14)
Article
Open AccessObjectives: As little is known about the burden of type 1 (T1DM) and type 2 diabetes (T2DM) in adolescents in Western Europe (WE), we aimed to explore their epidemiology among 10–24 year-olds. Methods: Estimates were ... -
Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021
(2024-05-18)
Article
Open Access -
Spinal cord injury patients exhibit changes in motor-related activity and topographic distribution
(2023)
Conference report
Open AccessSpinal Cord Injury (SCI) is a common disease that usually limits the patient’s independence by affecting their motor function. SCI patients usually present neuroplasticity, which allows brain signals transmission through ... -
A dynamic fitting strategy for physiological models: a case study of a cardiorespiratory model for the simulation of incremental aerobic exercise
(Multidisciplinary Digital Publishing Institute (MDPI), 2024-04-11)
Article
Open AccessUsing mathematical models of physiological systems in medicine has allowed for the development of diagnostic, treatment, and medical educational tools. However, their complexity restricts, in most cases, their application ... -
A new force profile signal for a convex solution of muscle force estimation from electromyographic signals
(2023)
Conference report
Open AccessHigh-Density Surface Electromyography (HD-sEMG) is a non-invasive technique for measuring the electrical activity of a muscle with multiple, closely spaced electrodes. Estimation of muscle force is one of the applications ...
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