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About
The group’s research addresses the design and development of advanced signal processing techniques and the interpretation of biomedical signals to improve non-invasive monitoring, diagnosis, disease prevention and pathology treatment.
The group focuses its research in a translational way to promote the transfer of our scientific and technological contributions.
Currently, our prototypes are used in hospitals for research purposes and for future industrial developments.
Our main objective is to improve diagnosis capability through the characterization of physiological phenomena and to enhance early detection of major cardiac and respiratory diseases and sleep disorders. We propose and design new signal processing algorithms and develop new biosignal databases, with the collaboration of our hospital partners.
To validate the clinical information of new surface signals, we have developed specific invasive/non-invasive protocols and animal models.
Obstructive Sleep Apnea and Chronic Obstructive Pulmonary Disease
- Novel non-invasive measurements of neural inspiratory drive and time from invasive and noninvasive recordings of respiratory activity (Scientific Reports 2018, 8:16921; IEEE Journal Biomed Health Informatics 2018; IEEE-EMBC 2018: 3342-3345 )
- Evaluation of a wearable device to determine physiological parameters from surface diaphragm electromyography (IEEE Journal Biomed Health Informatics 2018) acquired by concentric ring electrodes (IEEE-EMBC 2018: 3350-3353)
- Characterization of the microvascular cerebral blood flow response to obstructive apneic events (Neurophotonics 2018, 5: 045003) with the ICFO and the Hospital de Sant Pau.
- Improvement of a front-end step for a wearable device for biosignals recording for COPD and OSA patients (IEEE Transactions on Biomedical Circuits and Systems 2018, 12: 774 – 783) with the imec, Eindhoven (NL).
Cardiac and cardiorespiratory diseases
- Novel eingvalue-based method for time delay estimation of respiratory signals in patients with chronic heart failure (Digital Signal Processing 2018, 75: 107-119), with Lund University,Sweden, and University of Zaragoza.
- Cardirespiratory phase synchronization during mental stimuli in healthy subjects (IEEE-EMBC 2018: 5298-5301)
- Estimation of sinus arrhythmia to classify ischemic cardiomyopathy (IEEE-EMBC 2018, 4860-4863) and artifact reconstruction of blood pressure signals (IEEE-EMBC 2018, 4864-4867)
Neurorehabilitation
- Characterization of upper limb muscle’s EMG activity during reaching and grasping (NeuroRehabilitation-ICNR 2018)
