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WS-7-3 Strategies in electrodiagnostic medicine — an interactive EMG planner
$30
Workshop 7. EMG standardization and expertsystems
(WT) was used to extract MUAP features in the time-frequency domains. The WT for low frequency bands takes a small number of samples, whereas for high frequency bands it takes a large number of samples. Therefore, the WT is appropriate for tracking signals with low frequency components changing slowly in time, and high frequency components changing rapidly in time. The above mentioned MUAP features have been applied to Artificial Neural Network (ANN) diagnostic medals. These models are constructed to resemble some simple organisational principles of the human brain in the classification of signal and image data. Supervised and unsupervised learning algorithms were utitised to train the ANN models investigated to diagnose normals, MND and myopathic patients. In supervised learning the training data is supplied at the input and the generated output is compared with the desired output (disease class); the error difference is used for modifying the ANN connections until learning is accomplished. For supervised learning the back-propagation training algorithm was implemented (Rumelhart et al., 1986). In unsupervised learning, data is presented sequentially at the input without specifying the desired output. These models are capable of self organisation; thus, topologically close output nodes become sensitive to physically similar inputs. The self-organised feature maps algorithm (Kohonen, 1984) has been used for unsupervised learning. A maximum diagnostic yield of 80% was obtained for both learning paradigms. The findings of this study and individual borderline cases will be discussed.
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Strategies in electrodiagnostic medicine - - an interactive EMG planner B. Falck, E. Sfftlberg, L. Korpinen. Department of Clinical Neurophysiology, University Hospital Uppsala, Sweden; Department of Power Engineering, Tampere University of Technology, Finland The strategy of an electrodiagnostic consultation is the plan for the investigation which aims at a correct diagnosis with the available methods and skills. With an optimal strategy the goal is reached with a minimum number of muscles and nerves tested. This is to save the patient from unnecessary discomfort and to reduce the time the doctor and technician need for the investigation. We have designed a prototype multimedia program that will guide the examiner in different clinical problems. The program consists of three parts. The first part deals with individual diseases such as carpal tunnel syndrome and myotonic dystrophy. The essential findings, both expected abnormal findings and expected normal findings are given. The procedure is the recommended tests that should be performed in each disorder. The second part describes differential diagnostic alternatives of commonly encountered symptoms. For instance paresthesias in digits 4 and 5. This may be due to an ulnar neuropathy at the elbow or wrist and also a lesion in the plexus brachialis or a C8 radiculopathy. The third part describes the typical neuromuscular abnormalities associated with different generalized disorders. Many systemic diseases are associated with various neuromuscular abnormalities that are quite typical of that disease. For instance patients with rheumatoid arthritis have carpal tunnel syndrome, axonal polyneuropathy, polymyositis and myasthenia gravis more often than others.
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Expert systems and quality control of the EMG examination
A. Fuglsang-Frederiksen 1, B. Johnsen 1, S. Vingtoft 1, J. R0nager i, p. Barahona, M. Carvalho, P. Fawcett, J.D. Guieu, J. Ladegaard, R. Liguori, W. Nix, G. Otte, I. Schofield, G. Sieben, A. Talbot, M. Veloso, A. Vila. 1Department of Clinical
Neurophysiology, Gentofte Hospital, University of Copenhagen A prospective international evaluation of the knowledge-based expert system KANDID indicated differences in epidemiology, planning strategies and techniques among seven different EMG laboratories (Vingtoft et al. 1993). To obtain standardisation and improve the quality of the E M G examination knowledge about inter-laboratory differences is needed. ESTEEM (European Standardised Telematic Tool to Evaluate EMG Knowledge-based Systems and Methods), a project under the auspices of the European Union, has developed a data structure with standardised terminology for EMG. Results from 716 E M G examinations from 7 different European laboratories were collected in a patient database. The results have shown differences among laboratories with respect to 1) epidemiology, 2) planning strategies: goaloriented studies including clinical examination versus electrodiagnostic screening, 3) techniques and E M G parameters used: e.g. quantitative contra qualitative EMG and near nerve technique contra nerve studies with surface electrodes, 4) pathophysiological interpretations: e.g. specific versus unspecific changes and 5) criteria for diagnosing different disorders. Medical audit during consensus meetings influenced the EMG examination of the clinical neurophysiologist involved. With the knowledge obtained from the ESTEEM EMG database it is possible to suggest standardisation for the issues mentioned above. Expert systems containing this information are being developed. With the EMG communication platform of E S T E E M it will be possible 1) to communicate with expert systems for on-line quality assurance during the EMG examination, and 2) to have electronic medical audit performed by expert clinical neurophysiologist. In this manner quality development of the E M G examination is possible.
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Standardization of "burst EMG" analysis
Arieh N. Gilai. Alyn Hospital, P.O. Box 9117, Jerusalem 91090,
Israel "Burst EMG" is a summated electrical response recorded from muscles during an abrupt movement. The electrical response is generated by a volley of motor unit action potentials that fire rapidly, overlapping and interfering with one another. In cases where voluntary cooperation is poor, abrupt movement could be elicited by external proprioceptive stimulation and an EMG burst would then be the only electrical activity available for analysis. In this study, a method is described in which a burst of EMG is divided into its basic segment components. Each segment is characterized by its duration, amplitude and area. Average segment area is calculated by digitally integrating the segments in a burst of EMG, provided that the burst duration is >300 msec and the potential amplitude is >100 IzV. A normal range is determined for the distribution of segment area. Segment area was calculated for a group of patients with myopathy (N = 68) and neurogenic disorders (N = 33) which were previously diagnosed elsewhere on the basis of history, clinical findings, enzyme studies, muscle biopsy etc. It was found that values of segment area can support a clinical diagnosis by distinguishing normal subjects from patients with neuromuscular disorders.
Workshop 7. EMG standardization and expertsystems
(WT) was used to extract MUAP features in the time-frequency domains. The WT for low frequency bands takes a small number of samples, whereas for high frequency bands it takes a large number of samples. Therefore, the WT is appropriate for tracking signals with low frequency components changing slowly in time, and high frequency components changing rapidly in time. The above mentioned MUAP features have been applied to Artificial Neural Network (ANN) diagnostic medals. These models are constructed to resemble some simple organisational principles of the human brain in the classification of signal and image data. Supervised and unsupervised learning algorithms were utitised to train the ANN models investigated to diagnose normals, MND and myopathic patients. In supervised learning the training data is supplied at the input and the generated output is compared with the desired output (disease class); the error difference is used for modifying the ANN connections until learning is accomplished. For supervised learning the back-propagation training algorithm was implemented (Rumelhart et al., 1986). In unsupervised learning, data is presented sequentially at the input without specifying the desired output. These models are capable of self organisation; thus, topologically close output nodes become sensitive to physically similar inputs. The self-organised feature maps algorithm (Kohonen, 1984) has been used for unsupervised learning. A maximum diagnostic yield of 80% was obtained for both learning paradigms. The findings of this study and individual borderline cases will be discussed.
•
Strategies in electrodiagnostic medicine - - an interactive EMG planner B. Falck, E. Sfftlberg, L. Korpinen. Department of Clinical Neurophysiology, University Hospital Uppsala, Sweden; Department of Power Engineering, Tampere University of Technology, Finland The strategy of an electrodiagnostic consultation is the plan for the investigation which aims at a correct diagnosis with the available methods and skills. With an optimal strategy the goal is reached with a minimum number of muscles and nerves tested. This is to save the patient from unnecessary discomfort and to reduce the time the doctor and technician need for the investigation. We have designed a prototype multimedia program that will guide the examiner in different clinical problems. The program consists of three parts. The first part deals with individual diseases such as carpal tunnel syndrome and myotonic dystrophy. The essential findings, both expected abnormal findings and expected normal findings are given. The procedure is the recommended tests that should be performed in each disorder. The second part describes differential diagnostic alternatives of commonly encountered symptoms. For instance paresthesias in digits 4 and 5. This may be due to an ulnar neuropathy at the elbow or wrist and also a lesion in the plexus brachialis or a C8 radiculopathy. The third part describes the typical neuromuscular abnormalities associated with different generalized disorders. Many systemic diseases are associated with various neuromuscular abnormalities that are quite typical of that disease. For instance patients with rheumatoid arthritis have carpal tunnel syndrome, axonal polyneuropathy, polymyositis and myasthenia gravis more often than others.
~-~-~
Expert systems and quality control of the EMG examination
A. Fuglsang-Frederiksen 1, B. Johnsen 1, S. Vingtoft 1, J. R0nager i, p. Barahona, M. Carvalho, P. Fawcett, J.D. Guieu, J. Ladegaard, R. Liguori, W. Nix, G. Otte, I. Schofield, G. Sieben, A. Talbot, M. Veloso, A. Vila. 1Department of Clinical
Neurophysiology, Gentofte Hospital, University of Copenhagen A prospective international evaluation of the knowledge-based expert system KANDID indicated differences in epidemiology, planning strategies and techniques among seven different EMG laboratories (Vingtoft et al. 1993). To obtain standardisation and improve the quality of the E M G examination knowledge about inter-laboratory differences is needed. ESTEEM (European Standardised Telematic Tool to Evaluate EMG Knowledge-based Systems and Methods), a project under the auspices of the European Union, has developed a data structure with standardised terminology for EMG. Results from 716 E M G examinations from 7 different European laboratories were collected in a patient database. The results have shown differences among laboratories with respect to 1) epidemiology, 2) planning strategies: goaloriented studies including clinical examination versus electrodiagnostic screening, 3) techniques and E M G parameters used: e.g. quantitative contra qualitative EMG and near nerve technique contra nerve studies with surface electrodes, 4) pathophysiological interpretations: e.g. specific versus unspecific changes and 5) criteria for diagnosing different disorders. Medical audit during consensus meetings influenced the EMG examination of the clinical neurophysiologist involved. With the knowledge obtained from the ESTEEM EMG database it is possible to suggest standardisation for the issues mentioned above. Expert systems containing this information are being developed. With the EMG communication platform of E S T E E M it will be possible 1) to communicate with expert systems for on-line quality assurance during the EMG examination, and 2) to have electronic medical audit performed by expert clinical neurophysiologist. In this manner quality development of the E M G examination is possible.
•
Standardization of "burst EMG" analysis
Arieh N. Gilai. Alyn Hospital, P.O. Box 9117, Jerusalem 91090,
Israel "Burst EMG" is a summated electrical response recorded from muscles during an abrupt movement. The electrical response is generated by a volley of motor unit action potentials that fire rapidly, overlapping and interfering with one another. In cases where voluntary cooperation is poor, abrupt movement could be elicited by external proprioceptive stimulation and an EMG burst would then be the only electrical activity available for analysis. In this study, a method is described in which a burst of EMG is divided into its basic segment components. Each segment is characterized by its duration, amplitude and area. Average segment area is calculated by digitally integrating the segments in a burst of EMG, provided that the burst duration is >300 msec and the potential amplitude is >100 IzV. A normal range is determined for the distribution of segment area. Segment area was calculated for a group of patients with myopathy (N = 68) and neurogenic disorders (N = 33) which were previously diagnosed elsewhere on the basis of history, clinical findings, enzyme studies, muscle biopsy etc. It was found that values of segment area can support a clinical diagnosis by distinguishing normal subjects from patients with neuromuscular disorders.