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Biomedical subjects

J I Aunon

Publications and source records attributed to J I Aunon.

At least 19 recordsLinked to original sources
PubMed1990

A new mode of communication between man and his surroundings.

The material presented in this paper is the result of a research project that was designed to study the feasibility of establishing an alternative mode of communication between man and his surroundings. The new form of communication proposed uses only the subject's brain waves with no overt physical action required. Subjects' electroencephalograms (EEG) were recorded while they performed various mental tasks designed to elicit hemispheric responses. Features formed from the EEG recording were then used as inputs into a Bayes quadratic classifier to test classification accuracy between the various tasks. The results obtained indicate that it is possible to accurately distinguish between any pair of the five tasks investigated. A comparison between three different methods for creating the feature sets is also presented.

Adult↗
PubMed1990

On intersensory evoked potentials.

It has been found in a variety of studies that, for human observers, reaction time is faster to a sound than to a light. The study being reported here was designed to test the hypothesis of audio-visual facilitation when a flash precedes a sound by about 30 to 50 milliseconds. It is hypothesized that the electrophysiological result of this facilitation will be an increased energy of the event related potential (ERP) resulting from the interaction between the visual and auditory processes. The stimuli consisted of a click (A), a flash (V), a simultaneous flash-click (AV), a flash preceding the click by 40 milliseconds (AV40) and by 80 milliseconds (AV 80). All of the stimuli were presented to the subject at random. Comparison of the ERP averages for the five subjects tested, and for the above mentioned conditions, supported the hypothesis of sensory integration. The AV40 averages indicated a larger recruitment of cells, as evidenced by a larger response than the AV, A, or V responses separately.

Adaptation, Physiological↗
PubMed1982

On the classification of single evoked potentials using a quadratic classifier.

It has been shown that using a computationally simple technique it is possible to classify single event-related potentials associated with upper and lower visual field stimulation with a high degree of accuracy. A flow chart of the algorithm and the FORTRAN 77 computer program required to perform the classification just described are included in the Appendix. The program as given in the Appendix is for a 2 class problem only. Memory limitations (33000 bytes 16-bit words) per user in the time-shared system utilized limits the amount of data that may be in core at any one time. A 2 class, 5 step problem takes approximately 5 min in a PDP ll/45 System (Digital Equipment Corp.).

Adult↗
PubMed1981

Signal processing in evoked potential research: averaging and modeling.

Three separate topics are covered in this review. The first deals with the technique of signal averaging. The concept of ensemble averaging is explored, and alternatives to this traditional tool are considered such as crosscorrelation averaging, latency corrected averaging, median averaging, etc. Different measures of variability of single evoked potentials are finally discussed. The second topic deals with modeling of the evoked potentials. The direct and inverse problems of source localization are discussed. Recent results of the application of these techniques to single evoked potentials are given. The third topic deals with the use of principal components for signal representation and comparison. Geometric consideration and varimax rotation of coefficients are discussed and examples given.

Brain↗
PubMed1981

Signal processing in evoked potential research: applications of filtering and pattern recognition.

The separate but closely related topics of waveform estimation by filtering and information extraction by pattern recognition are covered in this review. Because of the low signal-to-noise ratio generally encountered in evoked potential research, a variety of filtering methods have been employed for improving waveform estimation. Initially the filtering was done with analog devices but with the availability of high performance minicomputers virtually all filtering is now done digitally. Filters of various types are considered. Among them are single and multiple channel Wiener filtering, Kalman filtering, minimum mean square error filtering, maximum signal-to-noise filtering, and several types of nonlinear filters. The application of adaptive filtering techniques is also considered. In recent years there has been a continual increase in the application of pattern recognition techniques to the processing of evoked potentials. The techniques are based on statistical decision theory and the underlying basis of these procedures is reviewed. The technique of linear stepwise discriminant analysis is considered as well as the use of general discriminant functions of linear and quadratic types. Applications of these procedures to psychophysiological testing are discussed with particular emphasis on auditory and visual event-related potentials.

Evoked Potentials↗
PubMed1978

Computer techniques for the processing of evoked potentials.

A computer technique is described for the systematic characterization of brain evoked potentials. Preprocessing of the data by a causal digital filter is followed by a peak search and identification procedure. A latency histogram of the peaks found is constructed to determine the ranges or clusters of peaks within the single evoked potential. Peaks found within the clusters are then corrected to the mean latency of the cluster and a latency corrected average version of the evoked potential constructed.

Adult↗
PubMed1977

VEP and AEP variability: interlaboratory vs. intralaboratory and intersession vs. intrasession variability.

The VEP and AEP of a normal adult were recorded at single sessions in five laboratories that used different instrumentation. The results were compared with VEP and AEP data recorded at eight weekly testing sessions at one of the labs. The interlaboratory standard deviation was found to be over twice as large as the intralaboratory standard deviation measured over an eight week period. Intrasession EP variability was significantly less than intersession variability.

Adult↗