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Biomedical signal processing and interpretation

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) 

Staff

Projects

INTERNATIONAL PROJECTSFINANCERPI
DEEPDREAM · A Data-drivEn computational mEthod for PersonalizeD healthcare in chronic REspiratory diseases through big-dAta analytics and dynamical Modelling (2020-2022)European Comission · Marie CurieDaniel Romero
NATIONAL PROJECTSFINANCERPI
SappHiRES · Ecosistema de salud inteligente para la medicina personalizada y la asistencia sanitaria en enfermedades respiratorias y trastornos del sueño (2019 – 2021)Ministerio de Ciencia, Innovación y UniversidadesRaimon Jané
FINISHED PROJECTSFINANCERPI
M-OLDOSA Multimodal analysis and m-Health tools for diagnostic and monitoring improving of Obstructive Lung Disease and Obstructive Sleep Apnea patientsCIBER-BBN, SpainRaimon Jané
MultiTools2Heart Multiscale computational tools to improve diagnosis, risk assessment and treatment in prevalent heart diseasesCIBER-BBN, SpainJuan Pablo Martínez Cortés
Health Risk Assessment and Stratification of patients admitted in the Home Hospitalization & Early Discharge (2019-2020)Fundació EURECATRaimon Jané
Multimodal invasive and non-invasive biomedical signal interpretation and modelling in cardiac, respiratory and neurological disordersMINECO, I+D-Investigación fundamental no orientadaRaimon Jané
M-Bio4Health Biomarcadores fisiológicos multimodales para la monitorización no-invasiva y cuidado a domicilio de pacientes EPOC con comorbilidadesMINECO, Retos investigación: Proyectos I+DRaimon Jané
Study on software comparison of audio recordings and correlation to SAHS eventsR+D contract with Audiodontics, funded by the NIH (USA)Raimon Jané
Novel m-Health tools for unobtrusive sensing and management improving of Obstructive Sleep Apnea patients at homeObra Social La CaixaRaimon Jané
Non-invasive multimodal physiological biomarkers for monitoring COPD patients with comorbidities (2017-2018)With King’s College London, funded by the European Respiratory Society (ERS-LTRF 2017)Raimon Jané

Publications

Equipment

  • Research laboratory with full equipment for acquisition and processing of biomedical signal to test new sensors and to define clinical protocols (preliminary tests and control subjects)
  • Non-invasive Vital Signs Monitor for small lab animals (mice and rats) (Mouse-Ox Plus)
  • BIOPAC system for multichannel cardiac and respiratory biomedical signal acquisition
  • Databases of biomedical signals from hospitals and animal laboratories
  • Snoring analyzer equipment (SNORYZER)
  • Sensors, electrodes and microphones to obtain cardiac, respiratory, neural, muscular and sleep biomedical signals
  • Polisomnographic equipment available in the Sleep Laboratory of collaborator hospital
  • Beat to beat arterial blood pressure and haemodynamic monitor equipment
  • Computing server for high performance biomedical signals
  • Threshold™ IMT (Inspiratory Muscle Trainner) for respiratory muscle training (Phillips™)
  • Robust wearable wireless sensor device Shimmer3 (Shimmer Research Ltd., Dublin, Ireland).

Collaborations

  • Dr. J. Mark Ansermino
    Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, Canada
  • Prof. Antonio Bayes Genis
    Grup ICREC, Servei Cardiología Hospital Universitari Germans Trias i Pujol, Barcelona
  • Dr. Salvador Benito
    Hospital de la Santa Creu i Sant Pau, Barcelona
  • Prof. Dr. Konrad Bloch
    Pulmonary Division, University of Zurich, Switzerland
  • Prof. Armin Bolz
    Institute of Biomedical Engineering, University of Karlsruhe, Germany
  • Prof. Manuel Doblaré
    Grupo de Mecánica Estructural y Modelado de Materiales, Universidad de Zaragoza, Spain
  • Prof. Guy Dumont
    Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada
  • Prof. Ramon Farré
    Unitat de Biofísica i Bioenginyeria, Facultat de Medicina, Barcelona
  • Dr. Javier García-Casado
    Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano, Universidad Politécnica de Valencia
  • Dr. Joaquim Gea
    Servei Pneumologia, Hospital del Mar-IMIM, Barcelona
  • Dr. Alfredo Hernández
    Laboratoire Trataiment du Signal et de l’Image, Université de Rennes 1, Instituto Francés de Salud (INSERM), France
  • Dr. Eric Laciar
    Departamento de Electrónica y Automática, Universidad Nacional de San Juan, Argentina
  • Prof. Pablo Laguna
    Instituto de Investigación de Aragón (I3A), Universidad de Zaragoza, Spain
  • Dr. Barry Mersky
    Audiodontics, LLC, Bethesda, Maryland, USA
  • Prof. Dr. Thomas Penzel
    Interdisciplinary Sleep Center, Charité University Hospital, Berlin, Germany
  • Dr. Josep Morera Prat
    Servicio de Neumología, Hospital Germans Trias i Pujol, Badalona, Spain
  • Prof. Winfried J. Randerath
    Institut für Pneumologie, Klinik Bethanien, Solingen, Germany
  • Dr. Juan Ruiz
    Servei de Pneumología de l’Hospital Germans Trias i Pujol de Badalona
  • Dr. Matthias Schwaibold
    MCC-Med GmbH & Co. KG, Karlsruhe, Germany
  • Prof. Dr. Lotfi Senhadji
    Laboratoire Traitement du Signal et de l’Image (LTSI), Université de Rennes 1, Institut National de la Santé et de la Recherche Médicale (INSERM), France
  • Prof. Leif Sörnmo
    Signal processing group, Lund University, Sweden
  • Prof. Dr. Jaume Veciana
    Grupo de Nanociencia Molecular y Materiales Orgánicos del Instituto de Ciencia de Materiales de Barcelona (NANOMOL-CSIC), Barcelona
  • Prof. Andreas Voss
    University of Applied Sciences, Jena, Germany
  • Dr. Pierluigi Casale
    Laboratory for advanced research in microelectronics (IMEC), Eindhoven, The Netherlands
  • Dr. Francky Catthoor
    Laboratory for advanced research in microelectronics (IMEC), Leuven, Belgium
  • Dr. Miquel Domenech
    Dep. of Social Psychology, Universitat Autònoma de Barcelona
  • Dr. Caroline Jolley / Dr. John Moxham
    King’s College London, UK

News

IBEC’s Biomedical Signal Processing and Interpretation (BIOSPIN) group have published a paper with King’s College London that offers new techniques to monitor COPD patients by non-invasive methods. COPD – chronic obstructive pulmonary disease – is a progressive lung condition with no cure in which the patient’s airways become narrowed. Together with other mechanical abnormalities, airways obstruction increases the load on the respiratory muscles. This, in combination with respiratory muscle weakness in COPD patients, increases load-capacity imbalance and contributes to breathlessness. The IBEC group’s paper elucidates a new way of assessing inspiratory muscle function using mechanomyography, a non-invasive measure of muscle vibration associated with muscle contraction, jointly with surface electromyography.

IBEC celebrates COPD breakthroughs on World COPD Day

IBEC’s Biomedical Signal Processing and Interpretation (BIOSPIN) group have published a paper with King’s College London that offers new techniques to monitor COPD patients by non-invasive methods. COPD – chronic obstructive pulmonary disease – is a progressive lung condition with no cure in which the patient’s airways become narrowed. Together with other mechanical abnormalities, airways obstruction increases the load on the respiratory muscles. This, in combination with respiratory muscle weakness in COPD patients, increases load-capacity imbalance and contributes to breathlessness. The IBEC group’s paper elucidates a new way of assessing inspiratory muscle function using mechanomyography, a non-invasive measure of muscle vibration associated with muscle contraction, jointly with surface electromyography.

Some research published in PLOS ONE represents a new step towards translating IBEC’s basic research – specifically the novel signal processing and interpretation algorithms developed by Raimon Jané’s group – to clinical applications in hospitals. The group collaborated with the Hospital del Mar-IMIM in Barcelona to tackle the current lack of instruments for assessing respiratory muscle activation during the breathing cycle in clinical conditions.

Non-invasive analysis technique contributes to a better understanding of COPD

Some research published in PLOS ONE represents a new step towards translating IBEC’s basic research – specifically the novel signal processing and interpretation algorithms developed by Raimon Jané’s group – to clinical applications in hospitals. The group collaborated with the Hospital del Mar-IMIM in Barcelona to tackle the current lack of instruments for assessing respiratory muscle activation during the breathing cycle in clinical conditions.

Some IBEC research published in PlosOne offers a step towards better screening of patients with asthma and other sufferers of obstructive pulmonary diseases. The new integrated approach to continuous adventitious respiratory sound (CAS) analysis, developed by Raimon Jané’s Biomedical Signal Processing and Interpretation group within the framework of IBEC’s Joint Research Unit with the Institut d’Investigació Hospital Germans Trias i Pujol (IGTP), improves assessment in the clinic.

Screening improvements for asthma and obstructive pulmonary disease patients

Some IBEC research published in PlosOne offers a step towards better screening of patients with asthma and other sufferers of obstructive pulmonary diseases. The new integrated approach to continuous adventitious respiratory sound (CAS) analysis, developed by Raimon Jané’s Biomedical Signal Processing and Interpretation group within the framework of IBEC’s Joint Research Unit with the Institut d’Investigació Hospital Germans Trias i Pujol (IGTP), improves assessment in the clinic.

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