The main goal of the study is an unsupervised classification of school children dyslexia. Eye movements of 49 subjects were measured using videooculographic technique (VOG) during two non-reading and one reading tasks. A feature selection was performed obtaining data set consisting of 26 features. Next an inductive modelling technique was applied to data set resulting in extraction of six features...
EEG-based brain computer interface (BCI) provides a completely new communication channel between human brain and computer. Classification of EEG signals is a difficult task, especially when the classification has to be preformed on a single-trial EEG to continuously control a device. Event related desynchronization (ERD) has proven to be induced on the contralateral sensorimotor area during imagination...
The cepstral analysis is proposed with Gaussian mixture models (GMM) method to classify respiratory sounds in two categories: normal and wheezing. The sound signal is divided in overlapped segments, which are characterized by a reduced dimension feature vectors using Mel-frequency cepstral coefficients (MFCC) or subband based cepstral parameters (SBC). The proposed schema is compared with other classifiers:...
Ventricular tachyarrhythmias, in particular ventricular fibrillation (VF), are the primary arrhythmic events in the majority of patients suffering from sudden cardiac death. Attention has focused upon these articular rhythms as it is recognized that prompt therapy can lead to a successful outcome. There has been considerable interest in analysis of the surface electrocardiogram (ECG) in VF centred...
Human communication is saturated with emotional context that aids in interpreting a speakers mental state. Speech analysis research involving the classification of emotional states has been studied primarily with prosodic (e.g., pitch, energy, speaking rate) and/or spectral (e.g., formants) features. Glottal waveform features, while receiving less attention (due primarily to the difficulty of feature...
The power-law shot noise (PLSN) model has been recently proposed for modeling the ultrasound radio-frequency echo. According to it, the spectrum of the in-phase/quadrature/envelope components are power-law functions. The corresponding power-law exponents were shown to possess good tissue characterization ability. A crucial step in the computation of in-phase/quadrature/envelope components is the estimation...
Design of anaesthesia monitor/ pain monitor, using ECG signal only, is presented in this paper. During surgical operations, ECG is picked-up as a routine procedure; the same ECG is used here, hence it is almost noninvasive. Initially heart rate variability (HRV) spectrum is obtained from R-R intervals (RRIs) and the respiratory peak is identified. Following the contour of this peak, a bandpass filter...
A recurrence time statistics T1 is defined and used as a feature extraction method for seizure detection. The preliminary data shows that during seizure T1 generates a peak and this peak clearly distinguishes the seizure state from background activity. When applied to multi-channel ECoG recordings, the spatial-temporal signature of T1 can be clearly observed to discriminate seizures. The T1 feature...
In the current paper a new approach for K-complex detection using a continuous density hidden Markov model (CD-HMM) is presented. The system performance was evaluated in two manners. First using three seconds long segments of K-complexes and of background EEG (classification problem). Second using a whole night record and detecting the K complexes (detection problem). The fist test achieved an equal...
After knee or ankle injury, Freeman has proposed a rehabilitation program consisting in a prolonged maintain of monopodal equilibrium on an unstable plateform. The efficacy of such programs, often debated, is evaluated in the present study by a quantification of equilibrium criteria and electromyographical activities along the rehabilitation program. Our aim is to detect all events in the four EMG...
Detecting action potentials has an important role in analyzing extracellular neuronal recordings. Current algorithms require subjective tuning by a user in the form of user-specified parameters. This work describes a fully automatic template-matching spike detection algorithm that does not require any tuning. This algorithm is robust to noise and performs better than an optimum threshold detection...
In this paper, a model-based seizure detection method using statistically optimal null filters (SONFs) is presented. A template seizure from a patient is first selected and the basis functions required by the SONF are derived from this template seizure using wavelet transform. Subsequent EEG (electroencephalogram) recording is processed by the SONF and the output represents the noise-free estimate...
In a previous paper, we developed a method for the automated estimation of the phase relation between thoracic and abdominal signals measured by noninvasive respiratory inductance plethysmography (RIP). In the present paper, we improve on the phase estimator by including an automated procedure for the detection of periods of gross body movements. We assume that the number of sleep obstructive events...
From the energy point of view, obtaining simultaneous blood pressure and flow rate of the radial artery at the wrist is very important for sphygmic diagnosis in medicine. This work depicts the conceptual design for a noninvasive multi-functional sphygmus detection system. According to Y. C. Fung's flow rate equation, flow rate is a function of the diameter of the blood vessel, two adjacent pressures,...
This work reports research that investigated the relationship of the strength of contraction of different muscles of the lumbar back to maintain static posture. The paper reports the study of surface electromyogram of the muscles and uses scattering and neural networks on the strength of the EMG measured using root mean square (RMS). The signal is studied before and after the removal of electrocardiogram...
This paper proposes a novel system for pathological tremor study and diagnosis. The system described called TCA (tremor coherence analyzer) is based on a electronic device developed for wireless monitoring of physiological variables. The device uses Bluetooth technology to communicate. The proposed technique for pathological tremor analysis uses surface EMG signals. The EMG sensors are located on...
The problem of decomposing electromyographic (EMG) signals is considered. Starting from a graphical model (factor graph) of the problem, a new iterative decomposition algorithm is proposed. It is based on the sum-product (or belief/probability propagation) algorithm and is able to decompose heavily superimposed single- and multi-channel signals.
We have improved the accuracy (sensitivity x specificity) of a knowledge-based system from 90% to well above 95% in decomposing complex EMG 3-channel data into its constituent motor unit action potential (MUAP) trains. The key to achieving this improvement is our use of a probabilistic framework for resolving pulse superpositions through the application of utility maximization at the suprasegmental...