Browsing by Subject "Biomedical Engineering"

Now showing items 1-6 of 6

    • Conference Object  

      Artificial neural net algorithms in classifying electromyographic signals 

      Schizas, Christos N.; Pattichis, Constantinos S.; Schofield, I. S.; Fawcett, P. R.; Middleton, Lefkos T. (Publ by IEE, 1989)
      The aim of this work is to examine how Artificial Neural Nets (ANN) can be used as a computerized method for electromyographic diagnosis. For this reason, a number of well defined neuromuscular disorders have been selected, ...
    • Article  

      Artificial Neural Nets in Computer-Aided Macro Motor Unit Potential Classification 

      Schizas, Christos N.; Pattichis, Constantinos S.; Schofield, I. S.; Fawcett, P. R.; Middleton, Lefkos T. (1990)
    • Article  

      Image-based biomechanics of collagen-based tissue equivalents 

      Barocas, V. Η; Sander, E.; Stylianopoulos, T.; Tranquillo, R. (2009)
    • Conference Object  

      Neural networks in computer aided clinical electromyography 

      Schizas, Christos N.; Pattichis, Constantinos S.; Livesay, R. R.; Middleton, Lefkos T. (Publ by IEEE, 1991)
      In concentric needle electromyography, quantitative measurements are applied on the motor unit action potentials, which are recorded from the biceps muscle of normal subjects and patients suffering from neuromuscular ...
    • Conference Object  

      Neural networks: In search of computer-aided diagnosis 

      Schizas, Christos N.; Bonsett, C. A.; Livesay, R. R.; Pattichis, Constantinos S. (Publ by IEEE, 1991)
      The authors introduce the Bonsett Protocol, which quantifies a physician's intuitive and experienced opinions. Neural networks and EMG (electromyographic) signals have been used to enhance the diagnosis of neuromuscular ...
    • Conference Object  

      Unsupervised learning in computer aided macroelectromyography 

      Schizas, Christos N.; Pattichis, Constantinos S.; Livesay, R. R.; Schofield, I. S.; Lazarou, K. X.; Middleton, Lefkos T. (Publ by IEEE, 1991)
      Normals and patients from three disorders have been selected for investigation: (1) motor neurone disease (MND)