Riccardo Barbieri, Ph.D.


Assistant Investigator
Anesthesia, Critical Care and Pain Medicine, Mass General Research Institute
action potentials; arrhythmia, sinus; autonomic nervous system; baroreflex; electrocardiography; heart rate; models, cardiovascular; nonlinear dynamics; signal processing, computer-assisted I am a Biomedical Engineer, expert in signal processing algorithms for analysis and modeling of biological systems. My research interests include: mathematical modeling of biological systems, with emphasis on the cardiovascular system, the central nervous system and the autonomic nervous system; biomedical signal processing, with emphasis on cardiovascular control and cardiovascular variability signals; and signal processing in neurosciences (EEG, Evoked Potentials, single cell neuronal recordings).

Current research focuses on developing and testing novel signal processing algorithms based on point process theory, systems analysis, and state-space estimation in order to provide a more accurate noninvasive assessment and characterization of human cardiovascular control in a broad range of pathophysiological settings.

Cardiovascular recordings are available through important collaborations at local, national and international level. Data include tilt protocol studies, recordings under autonomic blockade, meditation studies, as well as sleep studies.

Of late, we have applied the point process paradigm to data from subjects under nauseogenic stimuli and/or acupuncture, and then correlated them with simultaneous fMRI recordings.

In yet another study, we have meliorated cardiorespiratory assessments by combining several physiological variables in order to predict apnea episodes in premature infants. Further important studies are being pursued for the assessment of depth of anesthesia using heart rate variability and galvanic skin response, of fetal heartbeat, and for automatic quantitative evaluation of human emotional states.

All these applications rely on continuing support from a multidisciplinary team of collaborators and consultants who provide additional expertise in engineering, statistics, cardiology, anesthesiology, and psychology.

By evolving the proposed techniques towards the practitioner’s needs, and possibly leading to improved patient outcomes by both pathological and well-being assessment, this research is expected to have a broad impact in clinical and translational medicine.
Research lab website Publications
rbarbieri1@mgh.harvard.edu
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