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An automated diagnosis procedure based on a statistical machine learning methodology using electroencephalograph (EEG) data is proposed for diagnosis of psychiatric illness. First, a large collection of candidate features, mostly consisting of various statistical quantities, are calculated from the subject's EEG. This large set of candidate features is then reduced into a much smaller set of most...
This paper describes the detection of preictal bursting using wavelet transform application and cross-correlation analysis. The wavelet transform is applied to data reduction and signal pre-processing. The extracted features provide simplified signals to process by means of the cross-correlation technique. The algorithm has been tested with a set of preictal data, interictal data and spontaneous crises,...
Brain networks with energy-efficient hubs might support the high cognitive performance of humans and a better understanding of their organization is of relevance not only for studying normal brain development and plasticity but also neuropsychiatric disorders. Here we propose an ultra-fast method to map the distribution of the functional connectivity density (FCD) in the human brain. The method was...
Gastrointestinal (GI) disorder is one of the most common diseases in human body. The swallowable wireless capsule endoscopy has been proved to be a convenient, painless and effective way to examine the whole GI tract. However, lack of motion control makes the movement of the capsule substantially random, resulting in missing diagnosis. In this paper, a locomotion mechanism is developed for the next-generation...
In this paper, the results of a 2-D center-out task in a Fitts's law experiment have been presented for measuring the performance of the Tongue Drive System (TDS). Although the end-user population for TDS is individuals with tetraplegia, in this study, we recruited 6 able-bodied subjects in 3 sessions, conducted in 3 consecutive days. They performed the same task with their right hand using a standard...
Wireless physiological/neurological monitoring in virtual reality (VR) offers a unique opportunity for unobtrusively quantifying human responses to precisely controlled and readily modulated VR representations of health care environments. Here we present such a wireless, light-weight head-mounted system for measuring electrooculogram (EOG) and electroencephalogram (EEG) activity in human subjects...
Biocooperative augmented robots, can enhance rehabilitation therapies by giving the correct assistance at the correct time. Since different patients may benefit from different amounts of assistance or resistance at a given time, predicting when a person enters in an undesired psychophysiological state can provide an intelligent system with important information about when to initiate interaction....
Heart sounds entail crucial heart function information. In conditions of heart abnormalities, such as valve dysfunctions and rapid blood flow, additional sounds are heard in regular heart sounds, which can be employed in pathology diagnosis. These additional sounds, or so-called murmurs, show different characteristics with respect to cardiovascular heart diseases, namely heart valve disorders. In...
Previously, we have reported the presence of oscillations in the graphs we have used to evaluate the Higuchi's fractal dimension in RR intervals time series of congestive heart failure (CHF) patients in the sleep phase but these oscillations hardly appear in all the six hours of the awake phase. In this paper we report the same analysis for heart rate time series for different groups of healthy subjects;...
Heart Rate variability (HRV) is important in characterizing heart functions. However, artifacts and trends are regularly observed to contaminate the HRV sequences. This study proposes a simple and effective preprocessor for the removal of artifacts and trend in the HRV sequences. A thresholding filter is applied to remove artifacts to maintain the HRV sequences in a reasonable range. A wavelet filter...
The paper presents a new method for neuromuscular disorders diagnosis based on analysis of scalograms determined by the Symlet 4 wavelets technique. Obtained results served for extraction of five features, which, after SVM analysis, were reduced to a single decision parameter allowing assigning the investigated cases to one of three groups: myogenic, neurogenic or normal. Software implementation of...
The study was aimed at evaluating the changes in dynamical connectivity, between interictal, preictal and ictal condition, among signals derived from StereoEEG recordings in patients with Taylor's type focal cortical dysplasia (FCD type-II), by means of Partial Directed Coherence and indexes derived from graph theory. Results showed that seizures are characterized by an increased synchronization,...
The apnea-hypopnea index (AHI) plays a major role in determining whether a patient suffers from SAHS, as well as in evaluating the severity of his/her condition. To obtain this index the number of apneas and hypopneas that the patient has experienced during his/her sleep is calculated, and the result is divided by the number of hours of sleep. The standard definitions of apnea and hypopnea require...
This article is concerned with the classification of ECG pulses by using state of the art Continuous Density Hidden Markov Models (CDHMM's). The ECG signal is simultaneously observed at three different level of focus by means of the Wavelet Transform (WT). The types of beat being selected are normal (N), premature ventricular contraction (V) which is often precursor of ventricular arrhythmia, two...
This paper presents a new approach that improves discriminative training criterion for Hidden Markov Models, and is oriented to pathological voice identification. This technique is aimed at maximizing the Area under the Curve of a receiver operating characteristic curve by adjusting the model parameters using as objective function the Mahalanobis distance and the distance between means of the underlying...
The electroencephalogram (EEG) is widely used in the investigation of neurological disorders. Continuous long-term EEG data offers the opportunity to assess patient health over long periods of time, and to discover previously unknown physiological phenomena. However, the sheer volume of information generated by long-term EEG monitoring also poses a serious challenge for both analysis and visualization...
We quantified the mechanical abnormalities of the spastic wrist in chronic stroke survivors, and determined whether these findings were representative of those recorded at the elbow and ankle joints. System identification techniques were used to characterize the mechanical abnormalities of these joints and to identify the contribution of intrinsic and reflex stiffness to these abnormalities. Modulation...
Restoring walking functions will greatly improve the foot-drop patients' life quality. In this work, we sampled 10 healthy subjects' gait data when walking in 4 different stride frequency overground and developed a dynamic Functional Electrical Stimulation (dFES) system for foot-drop patients' walk training, using the processed tibialis anterior (TA) muscle EMG signal. The data sampled under the new...
The worldwide prevalence of epilepsy is approximately 1%, and 25% of epilepsy patients cannot be treated sufficiently by available therapies. Brain stimulation with closed-loop seizure control has recently been proposed as an innovative and effective alternative. In this paper, a portable closed-loop brain computer interface for seizure control was developed and shown with several aspects of advantages,...
Parkinson's disease represents a chronic movement disorder, which is generally proportionally to age. The status of Parkinson's disease is traditionally classified through ordinal scale strategies, such as the Unified Parkinson's Disease Rating Scale. However, the application of the ordinal scale strategy inherently requires highly specialized and limited medical resources for interpretation. An alternative...
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