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Human Movement Bioengineering

The central research area of the research group ‘human movement bioengineering’ is to investigate the mechanics of musculoskeletal function during differentactivities (gait analysis, posture and balance, sports activities) and how different pathologies (i.e. diabetes, Parkinson’s Disease, Fragile X syndrome, ACL injury, temporomandibular joint disfunction) impact on the musculoskeletal function.

 

Homepage: http://biomov.dei.unipd.it

 

People:

Human Movement Bioengineering

  • Developing biomechanical tools which allow a better understanding of the impact of training programs or clinical interventions on people's suffering of diabetes, stroke, rheumatic diseases, Parkinson's disease, flat or cavus foot, maxillary transverse discrepancy, fragile X syndrome
  • Developing markerless motion capture software application able to collect data also underwater
  • Developing systems for simultaneous acquisition of motion capture, ground reaction forces and plantar pressure data during gait

Biomedical Image Analysis

This research area focuses on novel techniques for biomedical image processing and analysis, and on the development of diagnostic tools related to this field. It deals with image enhancement techniques, detection and segmentation of anatomical structures and lesions, identification of clinical parameters related to health state and their estimation. The developed techniques range from novel image enhancement and pre-processing methods to advanced machine learning and deep learning techniques for image classification and segmentation.

Image processing and analysis in ophthalmology

  • Corneal nerve images from confocal microscopy: segmentation of nerve structures, estimation of clinical parameters, such as tortuosity, nerve density, etc. Composition of several images into large mosaic images.
  • Corneal epithelium images from confocal and specular microscopy: segmentation of cell contours, estimation of clinical parameters cell density, pleomorphism, polymegethism.

    Biomedical Signal Processing

    Research activities:

    Local Field Potentials (LFP) in the animal model

    • Algorithms for automatic analysis LFP evoked by whisker movements in rats
    • Algorithms to measure phase-amplitude coupling in LFP in mice affected by Alzheimer's disease.

    Homepage: http://bio.dei.unipd.itPeople: Giovanni Sparacino (contact person)

    Hypoglycaemia-induced EEG changes

    • Quantitatification in the frequency, time-frequency and time domains
    • Brain connectivity in hypoglycaemia
    • Effect of hypoglycaemia on EEG complexity

    Homepage: http://bio.dei.unipd.itPeople: Giovanni Sparacino (contact person)

    Biomedical Signal Processing

    EEG Analysis

    • Frequency and time-frequency analysis of EEG, also under trans-magnetic stimulation
    • EEG in hepatic encephalopathy and epilepsy
    • Relationships between infra-slow components of blood flow velocity and EEG variability
    • Assessment of functional connectivity from EEG data
    • Bayesian methods for (single-trial) ERP estimation

    Data analysis, learning and control for biology and medicine

    We develop methodological tools, algorithms and software to analyze data and vital signals reflecting individual health and to exploit them with learning techniques to improve patient therapy, possibly creating real-time feedback mechanisms. Tools are personalized, adaptive, proactive and equipped with intelligent self-diagnostic functions. Models to predict and prevent the incidence of new diseases or medical complications are also investigated.

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