Medical signals and instrumentation

Biomedical signal processing and interpretation

Prof. Dr. Jané, Raimon
Group Leader


Torre I - Planta 9 | Baldiri Reixach, 4 | 08028 | Barcelona
Email : rjaneibecbarcelona.eu

Research Topics

Multichannel-Multimodal Biomedical Signal Processing / Sleep-disordered breathing analysis and interpretation / Non-invasive respiratory monitoring / Respiratory sounds analysis in Chronic Obstructive Pulmonary Disease / Advanced signal processing techniques to define new indices of cardiac risk / Multimodal interactions interpretation of blood pressure, electrocardiogram and respiration


The group’s research addresses the design and development of advanced signal processing techniques and the interpretation of biomedical signals to improve monitoring, diagnosis, disease prevention and pathology treatment. We explore new methods and techniques for multi-channel and multimodal acquisition, processing, modelling and interpretation of clinically relevant information from biomedical signals. Our main objective is to improve the non-invasive diagnosis capability through the characterization of physiological phenomena, and to enhance early detection of major diseases and cardiac, respiratory and sleep disorders.

 

Respiratory sound detection and interpretation in a novel single channel portable device for snore-based screening of Sleep Apnea-Hypopnea Syndrome (SAHS)

 

 

 

 

 

The specific objectives of the group are the proposal and design of novel signal processing algorithms and the development of a new biosignal databases developed jointly with hospitals to assess and validate the performance of the developed algorithms. To validate the clinical information of some new surface signals, we developed specific invasive/non-invasive protocols with the collaboration of our hospital partners. Currently, we are also studying the proposed algorithms in animal models to test performance in studies with well-controlled physiological conditions.

The group focuses its research in a translational way to promote that scientific and technology contributions can be transferred. Currently, our scientific prototypes are used in the hospitals for research purpose and for industrial developments

 



Multimodal biosignal interpretation in a SAHS rat model


Highlights in 2012:
  • We have proposed a new method to classify subjects according to their Sleep Apnea Hypopnea Syndrome (SAHS) severity through snoring signals (Medical Engineering Physics 34, 1213-1220), in collaboration with the Hospital Germans Trias i Pujol, Badalona.
  • We have studied an original definition of regular and non-regular snores and developed a new adaptive detection method, as a novel powerful tool for screening SAHS severity in clinical applications (Medical & Biological Engineering & Computing 50, 373-381), in collaboration with the Hospital Germans Trias i Pujol, Badalona.
  • We have studied the feasibility and efficacy of an automatic noninvasive analysis method for the differentiation of obstructive and central hypopneas based solely on a single-channel nasal airflow signal (Respiration, 2012, DOI: 10.1159/000342010), in collaboration with the Institute of Biomedical Engineering (Karlsruhe), the Klinikum Bethanien and the company MCC-Med, Germany.
  • We analyzed the periodic breathing during ascent to extreme altitude quantified by spectral analysis of the respiratory volume signal as indicator of a subject’s condition at high altitude during physical exercise (IEEE-EMBC 2012, 707-710), in collaboration with the University Hospital of Zurich, Switzerland.
  • We proposed a new method to non-invasive assessment of the diaphragm muscle efficiency (Journal of Electromyography and Kinesiology, DOI:10.1016/j.jelekin.2012.12.007), in collaboration with the Hospital Germans Trias i Pujol, Badalona.
  • We developed new methods to classify patients with mechanical ventilation to predict successful weaning process (IEEE-EMBC 2012, 698-701 and 4349-4352), in collaboration with the Hospital de Sant Pau, Barcelona.
  • We designed and analysed multimodal signals from a rat model of SAHS in collaboration with Daniel Navajas’ group at IBEC and the Biophysics and Bioengineering Unit of the School of Medicine, University of Barcelona.