Results 241 to 250 of about 1,588,862 (288)

Respiratory waveform pattern recognition using digital techniques

Computers in Biology and Medicine, 1989
An algorithm for detection of ventilatory events using digital signal processing techniques is described. Start and end of inspiration of each breath are detected using a combination of first derivative peak detection and second derivative analysis for edge detection.
G G Haddad, G G Haddad
exaly   +3 more sources

Automatic Radar Waveform Recognition

IEEE Journal of Selected Topics in Signal Processing, 2007
In this paper, a system for automatically recognizing radar waveforms is introduced. This type of techniques are needed in various spectrum management, surveillance and cognitive radio or radar applications. The intercepted radar signal is classified to eight classes based on the pulse compression waveform: linear frequency modulation (LFM), discrete ...
Jarmo Lundén, Visa Koivunen
openaire   +1 more source

Pattern Recognition Applied to Monitoring Waveforms

IEEE Transactions on Biomedical Engineering, 1975
This paper demonstrates that fetal heart rate (FHR) patterns can be classified by algorithmically determined linear discriminants. A nonparametric learning algorithm was applied to 17 samples of five-vectors. The coordinates of each sample vector were visual features derived from the FHR curve and the simultaneous uterine contraction pressure data in ...
W R, Valenzuela, A, Klinger, J S, McDonald   +2 more
openaire   +2 more sources

Sequential feature extraction for waveform recognition

Proceedings of the May 5-7, 1970, spring joint computer conference on - AFIPS '70 (Spring), 1970
Many practical waveform recognition problems involve a sequential structure in time. One obvious example is speech. The information in speech can be assumed to be transmitted sequentially through a phonetic structure. Other examples are seismograms, radar signals, or television signals.
William J. Steingrandt, Stephen S. Yau
openaire   +1 more source

Optimal recognition of neuronal waveforms

Biological Cybernetics, 1979
Statistically optimal methods for identifying single unit activity in multiple unit recordings are discussed. These methods take into account both the nerve impulse waveforms and the firing patterns of the units. A generalized least-squares fit procedure is shown to be the optimal recognition scheme under some reasonable statistical assumptions, but ...
openaire   +3 more sources

Optimal Recognition Of Neural Waveforms

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society Volume 13: 1991, 2005
The investigation of biological neural networks requires reliable classification of neural action potentials in extracellular recordings. When the signal-to-noise ratio is bw, when the spike waveforms gradually change shape and amplitude, or when spikes overlap, the current sorting techniques cannot provide robust on-line operation due to their noise ...
I.N. Bankman, K.O. Johnson, W. Schneider
openaire   +1 more source

Waveform recognition with 10,000 ECGs

Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163), 2002
A method for the comparison and interpretation of 12-lead ECGs without feature extraction is introduced. One beat of the test ECG with unknown diagnosis is compared with ECGs from an ECG database with available diagnoses. With the aid of modified cross correlation methods, reference cases are selected from the ECG database which best match the signal ...
R. Bousseljot, D. Kreiseler
openaire   +1 more source

EKG waveform recognition procedure

Proceedings of the Fifteenth Annual Northeast Bioengineering Conference, 2003
A fast, accurate, and robust EKG (electrocardiogram) waveform-recognition algorithm has been developed for a personal computer. The method uses the convolution of raw EKG data with one or more sample EKG waveform templates as a recognition signal. Recognition occurs when the convolution exceeds a user-defined reference level.
G. Dwyer, Y. Noguchi, H.H. Szeto
openaire   +1 more source

An experimental system for the waveform recognition of impedance plethysmography

[1988 Proceedings] 9th International Conference on Pattern Recognition, 2003
An impedance waveform recognition system is developed which can perform both cardiac and pulmonary waveform recognition in a single system. The basic structure of the system is outlined, with special attention to the recognition of the four physiological signals: electrocardiogram, dz/dt, Delta Z, and phonocardiogram.
Tian-You Gu, Bao-Yong Wu, Cheng-Lin Zhang, Dian-Cheng Zhang   +3 more
openaire   +1 more source

Sensitivity of Diagnostic Classification to Variations in Waveform Recognition

2015
info:eu-repo/semantics ...
Lanckriet, J., De Jongh, G., Kornreich, Frédéric   +2 more
openaire   +3 more sources