Biomedical subjects

S Dandapat

Publications and source records attributed to S Dandapat.

3 recordsLinked to original sources

PubMed1997

Spike detection in biomedical signals using midprediction filter.

Spikes such as QRS complex in ECG, epileptic seizures in EEG, fine crackles in vesicular sound and glottal closure instants in voiced sound are of diagnostic importance. Various methods of spike detection use the amplitude and frequency characteristics of the spikes. Because of the high frequency content, the spikes appear in the error signal when a linear prediction filtering scheme is used. The authors use the method of midprediction filtering for the detection of the spikes. In this method, the present sample is predicted as a weighted average of p recent past and p immediate future samples. The symmetrical nature of midprediction causes the spikes to appear in the error signal with their original basewidths. This can help in improving the reliability of spike detection, as both the amplitude and the duration of the spike can be considered as decision making parameters. It is observed that the high frequency gain of the midprediction filter is higher compared to the high frequency gain of the LPC or endprediction filter. As a result, this method works better than linear prediction for the detection of spikes.

Electrocardiography↗

PubMed1994

Anti-idiotype antibodies to Marek's disease-associated tumour surface antigen in protection against Marek's disease.

Marek's disease-associated tumour surface antigen (MATSA) removed by enzymatic (papain) digestion of Marek's disease tumour cells was fractionated by gel filtration chromatography. The first peak (F1) was used to raise antibody in rabbits. Monoclonal antibody (RPH-6) directed against MATSA and the anti-F1 IgG were used as idiotypic antibodies to raise polyclonal anti-idiotype serum in heterologous hosts; rabbit and goat, respectively. The anti-idiotypes (anti-Id) were purified by affinity chromatography and characterized by competitive binding assay using immunofluorescent (IF) tests. Day-old white Leghorn chicks were immunized with anti-Id to MATSA (Group 1) or anti-Id to F1 (Group 3) and challenged with virulent Marek's disease virus (MDV) on the tenth day post immunization. In positive control groups, the day-old chicks were inoculated with anti-BALB/c mouse globulin (Group 2) and anti-rabbit globulin (Group 4) and challenged with virulent MDV on the tenth day post inoculation. As compared with positive control groups, the vaccinated groups (1 and 3) had considerably lower level of MATSA positive cells during the post challenge observation period. The protection level against MD in the immunized groups was 66.6% (Group 1) and 86.6% (Group 3).

Animals↗

PubMed1993

A knowledge based interpretation system for EMG abnormalities.

The conventional method of diagnosis in electromyography is complex and time consuming, not only due to the large number of parameters, to be considered for diagnosis, but also because of the usual procedure of evaluating the different parameters of EMG signal by visual scanning of the plotted signal. So there is a clear need to make use of computer aided decision support system. In the present work an attempt has been made in the direction of integration into one automated system, the qualitative knowledge of the physician, with possibly sophisticated signal analysis tools which must replace the visual scanning. A software program (in Turbo-C) on a PC-AT has been developed to evaluate the different parameters of MUAP's (motor unit action potential) in a EMG signal. Then an Expert system (in Turbo-Prolog) has been implemented for diagnostic purposes of different muscular abnormalities by making a knowledge base from the different parameters involved in the decision making procedure of clinical electromyography. A hybrid model of rule and frame based Expert system is implemented. An attempt has been made for making a complete system, i.e., for recording, analysis and decision making for diagnosis.

Diagnosis, Computer-Assisted↗