BIOSTEC is a joint conference composed of four concurrent conferences: BIODEVICES, BIOINFORMATICS, BIOSIGNALS and HEALTHINF.
These four conferences are always co-located and held in parallel.
Keynote lectures are plenary sessions and can be attended by all BIOSTEC participants.
KEYNOTE SPEAKERS LIST
José C. Príncipe, University of Florida, U.S.A.
Title: Somatosensory Brain Machine Interfaces
Richard Bayford, Middlesex University, U.K.
Title: The Development of Bio Imaging
Jan Cabri and Peter Federolf, Norwegian School of Sport Sciences, Norway
Title: Kinesiological Electromyography: Applications and Challenges
Mamede de Carvalho, Institute of Molecular Medicine - University of Lisbon, Portugal
Title: Clinical Neurophysiology: Engineering and Medicine
Franco Docchio, Università degli studi di Brescia, Italy
Title: Biomedical 2D and 3D Imaging:
State of Art and Future Perspectives in Ophthalmology, Dentistry, Prosthesics and Forensic Medicine
Miguel Castelo Branco, University of Coimbra, Portugal
Title: Novel Trends in Multimodal Imaging and Translational Research in Systems Neuroscience
José C. Príncipe
University of Florida
José C. Príncipe (F'2000) is a Distinguished Professor of Electrical and Computer Engineering with the University of Florida, Gainesville. He is a BellSouth Professor and the Founding Director of the Computational Neuro-Engineering Laboratory, University of Florida. His current research interests are centered in advanced signal processing and machine learning, brain machine interfaces, and the modeling and applications of cognitive systems.
The field of Brain Machine Interfaces are becoming more sophisticated with the improved knowledge of the brain and a more realistic assessment of the disabled user's needs. This talk summarizes current work on architectures and signal processing algorithms for motor BMIS. Two types of symbiotic BMIs, the reward and goal driven will be described. Issues related to the design of the algorithms for spike train signal processing in Reproducing Kernel Hilbert Spaces will also be briefly presented and compared with alternate techniques.
Richard Bayford MSc, PhD, FinstP, FinstIPEM, MIEEE is a Professor in Bio-Modelling and informatics in the Natural sciences department and Head of Biophysics for Middlesex University Centre for investigative Oncology. His expertise is in biomedical image/signal processing, Electrical Impedance Tomography (EIT), Nano technology, Deep brain stimulation, Bio-Modelling, Tele-medical system, sensors and VLSI design. He has worked on several industrially/EU-sponsored research projects, which he was the principle investigator and has been co-investigator on EPSRC/BBSRC research projects. His current research focus is the development of reconstruction algorithm and hardware for new imaging methods for the detection of cancer biomarkers. Recently he has adapted this research area, to addressing the problem of modelling electrical field distribution in the human head for application of Deep Brain Stimulation. He has also pioneered the first reconstruction algorithm to image impedance changes inside the human head.
He has published over 90 journal papers and over 100 papers in international conference proceedings. He has been guest editor on four special issues and co-organizer of three conferences on biomedical application of EIT. He is also editorial in chief of the IoP Physiological Measurements journal, and on the editorial board of the International Journal of Biomedical Imaging in the USA and recently become the Chair of the IPEM's publication committee.
Bio imaging is a technique based on multiple measurements of impedance. When it is used for medical application it relates the biophysical properties of tissues and blood to produce a reconstructed image or map that represent the human physiology. It relies of the bio impedance properties of the biological medium, for example in tumours the cell density often increases. Bio imaging which is often called Electrical impedance tomography (EIT) is a relatively new imaging method that has evolved over the past 30 years. It has the potential to be of great value in clinical diagnosis; however, it is a technically difficult problem to solve in terms of developing hardware for data capture and the algorithms to reconstruct the images. The development of EIT and how it has evolved are presented specifically addressing its clinical applications, examining hardware for the collection of data and reconstruction algorithms to generate images. Finally, this review looks at future developments that are evolving from EIT. These new variations use mixed modalities that may produce interesting new clinical imaging tools.
Norwegian School of Sport Sciences
Norwegian School of Sport Sciences
Brief Bio - Jan Cabri
He received his PhD in Physical Therapy and Motor Rehabilitation in 1989 at the Vrije Universiteit Brussel (BE) were he was a research associate at the Department of Anatomy.
Was awarded an associate professorship, Sports Medicine, Faculty of Medicine, Vrije Universiteit Brussel (BE) in 1992. Was invited professor at the Technical University Lisbon, Faculty of Human Movement (PT) from 1996 to 2009 after which he was appointed a Professor and Head of the Department of Physical Performance, The Norwegian University of Sport and Physical Education (NO).
His research interest in applied (sports) biomechanics and kinesiological electromyography. He is a member of the Scientific Board of the European College of Sports Sciences and of the World Commission of Sport Science, Science and Football Steering Group.
Furthermore, he serves as Section editor in the European Journal of Sport Science.
EMG is the study of muscle function through the recording of the electrical signal the muscle emanate before mechanical contraction. The mechanism of contraction is well documented in the literature and a detailed description would have little or no contribution to the subject of this paper. The action potential of the surface membrane of the muscle fibre is the ultimate cellular source of the electrical potential changes from within a muscle. The cellular unit of contraction is the muscle fibre, but it is the sarcolemma (fibre membrane) that is responsible for the transmission of an impulse, by the Tubular system, to the interior of the fibre where the actual contractile mechanism response is.
The myoelectric signal (MES) is an exceedingly complicated signal which is affected by the anatomical and physiological properties of muscles, the control scheme of the nervous system, as well as the characteristics of the instrumentation that is used to detect and observe it. It can be represented as a complex interference pattern arising from the summation of asynchronously firing motor units in the active muscle, and when obtained with surface electrodes has a rather weak selectivity. Similarly, the electrical activity of a muscle is a combination of individual electrical events in the muscle, and the EMG signal recorded with surface electrodes is a superposed motor unit action potentials (MUAPs).
The raw surface EMG signal, the EMG signal obtained after recording and before the signal processing, has an amplitude range from 0.05 to 5 mV, its frequency characteristics range from 1 to 3000 Hz, although, some authors observed significant energy of the signal only up to 1000 Hz.
Alone, the EMG has a reduced meaning. It is necessary to record other types of data from the performance to relate with EMG signals. Electrogoniometers, force plates and 3D video analysis are the tools more frequently used in synchronicity with the EMG signals. However, the validity and reliability of the EMG signal is still challenged as no real consensus exists with respect to data analysis.
Mamede de Carvalho
Institute of Molecular Medicine - University of Lisbon
Mamede de Carvalho is a medical doctor specialized in Neurology and Neurophysiology, with the highest degree ("Chefe de Serviço") and working in the Neuroscience Department of the University Hospital in Lisbon. After obtaining his PhD in 2000 he underwent evaluation to reach the degree of associated Professor in Neurology. Since 2010 he is the invited Professor of Physiology at the Faculty of Medicine in Lisbon.
He is the head of the Neuromuscular Unit of his Hospital and of the Neuromuscular Unit of the IMM. He is involved in investigating Amyotrophic Lateral Sclerosis, Familial Amyloid Polyneuropathy, Neurophysiology of the Respiratory Muscles, Exercise Training in ALS, Skin biopsy, Magnetic Stimulation and Laser Evoked Potentials. He has more than 130 papers published in International journals. He is in the editorial board of 5 international scientific journals.
Presently he is the President of the Portuguese Association of Clinical Neurophysiology, member at large of the International Federation of Clinical Neurophysiology and President of the International Clinical Neurophysiology Society.
The electrophysiology (the study of the electrical properties of biological cells and tissues) can be applied in medicine to support clinical diagnosis, but also to monitor disease progression or medical interventions or to detect early changes potentially determinant of a different treatment approach. This is clinical neurophysiology.
Classically clinical neurophysiology includes electroencephalography (EEG), electromyography (EMG) and evoked potentials (EPs). However, new techniques have been introduced recently, as transcranial magnetic stimulation (TMS), laser stimulation of small nerve fibers, transcranial direct current stimulation, threshold electrotonus and muscle impedanciometry. In addition, imaging techniques are being merged with neurophysiology, as combined functional MRI and EEG, or ultrasound associated with needle EMG or nerve conduction studies. Finally, new technical advances have been linked to less recent techniques, as TMS theta-burst stimulation, motor unit index or electrocorticography.
Clinical neurophysiology will move from a pure diagnostic test to a method to quantify disease progression. This quality is potentially useful in exploratory clinical trials in humans, or in animal studies. On the other hand, it has been progressively more used in guiding therapeutic interventions, as the best target muscle to receive Botox, or monitoring nervous system injury during risk surgical interventions. The extension of clinical neurophysiology to brain-computer interface, to promote communication in locked-in patients or in moving bionic limbs, are exciting and expanding areas.
The advances in this area are depended on a close collaboration between the clinical neurophysiologists and engineers. This encloses recording system, data analysis and presentation, storing and report facility. The future invites for integration between neurophysiology and other tools as functional imaging, which requires adapted equipment and rapid solution of complex algorithms. We need understand the next step to anticipate future requirements. The possibility of altering nervous system function by external electrical modulation, as occurs in Parkinson disease subthalamic nucleus stimulation, is an open avenue. Central nervous system structures, such as the cortex, to treat pain, epilepsy or stroke lesion, are next advances. But, other areas need to be considered, as intelligent peripheral nerve or ideo-muscular stimulators able adapt function to metabolic needs.
The specific expertise of certain national medical groups should be explored in future projects with technical groups interested in promoting advances in particular applications, such as original interventions to treat weakness, to easy patient-caregiver communication or to relieve pain.
State of Art and Future Perspectives in Ophthalmology, Dentistry, Prosthesics and Forensic Medicine
Università degli studi di Brescia
Prof. Franco Docchio was gaduated in 1976 in nuclear engineering, and is full Professor of Optoelectronics at the University of Brescia, Italy. He is Fellow of the European Optical Society, member of the IEEE and of the Italian Optical Society, member of the Atheneum of Sciences and Arts of Brescia. He has been Vice Dean of the Faculty of Engineering, Vice Rector of the University, and member of the Communications Superior Council of Italy.
He is a co-founder and tutor of a number of spin-off companies active in 2D and 3D imaging, optical measurements, LED illumination optics, laser development, and fibre optics.
The rapid evolution of optoelectronic components and of the processing capability of even portable or handheld computers has opened new scenarios for a wide number of applications of imaging techniques to the biomedical domain, as well as to other domains such as industrial, cultural heritage, etc. Classical 2D imaging is rapidly being replaced by more advanced 3D imaging that by far increases the depth of information available for diagnosis, storage, retrieval, study and classification.
Ophthalmology, dentistry, prosthetics and forensic medicine are among the biomedical research areas where our laboratory has been active so far in relation to 2D and 3D images, supported by a number of start-ups formed as spinoffs of the laboratory. In the talk, a summary of the activities carried out, and of the future perspectives in these fields will be given, giving emphasis also to the newest techniques of biomedical image processing.
Miguel Castelo Branco
University of Coimbra
MCB is the Scientific Coordinator of the National Functional Brain Imaging Scientific initiative. He is also the Head of ICNAS, a Medical Imaging Infrastructure at the University of Coimbra and IBILI, a Research Unit of our National Scientific System. His lab is representing his own host University in this national Imaging Consortium. Under his leadership IBILI was classified as an Excellent Research Unit by international evaluation panels. He also has strong experience in preclinical and clinical research (including clinical trials involving drug therapies). He has also been involved in “spin-off” initiatives and entrepreneurial consortia between academia and the industry. He is currently also coordinating an innovation project with the DoIt Consortium of the Health Cluster of Portugal. He has made interdisciplinary contributions in the fields of Cognitive Neuroscience, Human and Animal Neurophysiology, Visual Neuroscience, Human Psychophysics, Functional Brain Imaging and translational research in Neurology. He has been also involved in generating interdisciplinary work with scientists working in the field of neuropsychology, neuroinformatics and neuroengineering. His lab has formerly accomplishing tasks in the context of several European Networks, (Evi-Genoret, BACS and now an e-Rare Consortium), and has succeed in collaborating with labs working in other fields of knowledge such as Human Genetics and Clinical Neuroscience. His work in fundamental neuroscience ranges from sensory biophysics to visual attention and high level processes in human neurophysiology. In recent work he has also focused on temporal dynamics of perceptual decision mechanisms and the role of context. In his translational research he could separate low vs. high level impairment in visual cognition in a genetic neurodevelopmental model, Williams Syndrome. He has further studied parallel pathways to quantitatively analyze visual and motor aging in neurodegenerative disorders (in particular Parkinson Disease). His laboratory is very experienced in Visual and Cognitive Impairment questions, and the role of innate factors and learning in shaping cognitive performance. In recent work, the lab has characterized several disease models of genetic vs. acquired visual impairments. One major goal is to provide models of visual and cognitive impairment based on new structure-function and genotype-phenotype correlations that may help define novel rehabilitation strategies. Finally, the lab has established multimodal approaches in neurological disorders (including epilepsy) that allowed to better unraveling structure function correlations and functional reorganization of visual search implicit vs. explicit memory circuits.
Our research involves linking engineering approaches with physiological studies in animals and humans, in health and disease. We will discuss the use statistical classification approaches in the discovery of multivariate biomarkers of diseases of the brain as well as in clinical applications of brain computer interfaces. Also, we will discuss model and data driven approaches to understand brain function in health and disease, in particular in which concerns decision making processes. Finally we will address the importance of biomedical databases and longitudinal studies in brain development and ageing.