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Biomedical subjects

M P Beddoes

Publications and source records attributed to M P Beddoes.

12 recordsLinked to original sources
PubMed1993

Multiply sectioned Bayesian networks for neuromuscular diagnosis.

A prototype neuromuscular diagnostic system (PAINULIM) that diagnoses painful or impaired upper limbs has been developed based on Bayesian networks. This paper presents nonmathematically the major knowledge representation issues that arose in the development of PAINULIM. Motivated by the computational overhead of large application domains, and the desire to provide a user with an interface that gives a focused display of a subdomain of current interest, we built PAINULIM using the idea of multiply sectioned Bayesian networks. A preliminary evaluation of PAINULIM with 76 patients has demonstrated good clinical performance.

Artificial Intelligence↗
PubMed1992

Quality control in nerve conduction studies with coupled knowledge-based system approach.

Contemporary equipment used for nerve conduction studies is usually capable of computerized measurement of latency, amplitude, duration, and area of nerve and muscle action potentials and resulting conduction velocities. Abnormalities can be due to technical error or disease. Identification of technical error is a major element of quality control in electromyography, and artificial intelligence could be useful for this purpose. We have developed a coupled knowledge-based prototype system (QUALICON) to assess the correctness of recording and stimulating characteristics in routine conduction studies. QUALICON extracts numeric features from CMAPs or SNAPs, which are translated into symbolic form to drive a Bayesian network. The network uses high-level knowledge to infer the quality of stimulating and recording electrode placement as well as polarity and stimulus strength making recommendations as to the likely technical error when abnormal potentials are detected. A preliminary assessment shows that QUALICON performs as well as manual assessment performed by professionals.

Action Potentials↗
PubMed1989

Practical digital filters for reducing EMG artefact in EEG seizure recordings.

In long-term scalp EEG monitoring of epileptic patients it is virtually impossible, in the present state of the technology, to avoid movement-related artefacts. These often obscure EEG information about the location of the seizure focus. One important example of such artefact is EMG activity. Its removal or suppression is sometimes enough to make otherwise useless EEG traces readable. Different methods of filtering have been applied towards that end. We routinely use a 15 Hz setting on our polygraph in obtaining EEG seizure printouts. We have recently examined digital filters which attenuate EMG beyond what is possible with the 15 Hz filter. A concern has been that the filters are practical in that they run in real time on a simple microprocessor and cause a minimum of confusion between smoothed artefact and actual brain activity.

Electroencephalography↗
PubMed1985

Automation of the seizure investigation unit at the University of British Columbia Health Sciences Centre Hospital.

At the University of British Columbia Health Sciences Centre Hospital we have constructed an automated Seizure Investigation Unit for long term monitoring of epileptic patients. A central component of this system is a new device, developed at the University of British Columbia, which prevents video and EEG records of seizures recorded on video tape from being over-recorded. Computer technology is relied upon to a considerable degree in our unit. Computers are seen, in this phase of development of the SIU, as a means of making patient monitoring less dependent on supervision. They can help to redirect human energy towards complex analysis rather than time consuming and simple monitoring tasks.

Automation↗