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The present contribution aims at proposing a comprehensive and tutorial introduction to the practical use of wavelet Leader based multifractal analysis to study heart rate variability. First, the theoretical background is recalled. Second, practical issues and pitfalls related to the selection of the scaling range or statistical orders, minimal regularity, parabolic approximation of spectrum and parameter...
Heart rate variability is a non invasive and indirect measure of the autonomic control of the heart. Therefore, alterations to this control system caused by myocardial ischaemia are reflected in changes in the complex and irregular fluctuations of this signal. Multifractal analysis is a well suited tool for the analysis of this kind of fluctuations, since it gives a description of the singular behavior...
Arrhythmia is a major health problem and is the subject of much research and computational modeling. The impact of this research has been limited by the availability of human data and by difficulties in its translation to clinical practice. This paper describes an expert system for analysis of cardiac electrogram signals, detecting local activation and repolarization times using heuristic algorithms...
Sample Entropy (SampEn) is a nonlinear regularity index that requires the a priori selection of three parameters: the length of the sequences to be compared, m, the patterns similarity tolerance, r, and the number of samples under analysis, N. Appropriate values for m, r and N have been recommended in some cases, such as heart rate, hormonal data, etc., but no guidelines exist for the selection of...
The development of non-invasive tools able to provide valuable information about the effectiveness of a shock in external electrical cardioversion (ECV) is clinically relevant to enhance these protocols in the treatment of atrial fibrillation (AF). The present contribution analyzes the ability of a non-linear regularity index, such as sample entropy (SampEn), to follow-up noninvasively AF organization...
In this paper we show how healthy subjects can operate a non-invasive asynchronous BCI for controlling a FES neuroprosthesis and manipulate objects to carry out daily tasks in ecological conditions. Both, experienced and novel subjects proved to be able to deliver mental commands with high accuracy and speed. Our neuroprosthetic approach relies on a natural interaction paradigm, where subjects delivers...
As a partially invasive and clinically obtained neural signal, the electrocorticogram (ECoG) provides a unique opportunity to study cortical processing in humans in vivo. Functional connectivity mapping based on the ECoG signal can provide insight into epileptogenic zones and putative cortical circuits. We describe the first application of time-varying dynamic Bayesian networks (TVDBN) to the ECoG...
Combining non-invasive monitoring of action-related brain signals with the invasive recordings of the nerve motor output could provide robust natural and bidirectional multimodal Brain-Machine interfaces. One 26 years old, right-handed male who had suffered traumatic trans-radial amputation of the left arm was connected in a bidirectional way with a robotic hand prostheses. Cortical signals related...
Our group has been investigating the development of BCI systems for improving information delivery to a user, specifically systems for triaging image content based on what captures a user's attention. One of the systems we have developed uses single-trial EEG scores as noisy labels for a computer vision image retrieval system. In this paper we investigate how the noisy nature of the EEG-derived labels...
The kinematics of hand movement have been reported to be encoded in neural activities recorded at the primary motor cortex accompanying or immediately preceding the movement. In our earlier study, we demonstrated that the speed of imagined hand movements can be represented in the noninvasive EEG recordings and continuously decoded. In the present work, we aimed to systematically examine the spectral-temporal...
To patients who have lost the functionality of their hands as a result of a severe spinal cord injury or brain stroke, the development of new techniques for grasping is indispensable for reintegration and independency in daily life. Functional Electrical Stimulation (FES) of residual muscles can reproduce the most dominant grasping tasks and can be initialized by brain signals. However, due to the...
Baseline neurodynamics are believed to play an important role in normal brain function. A potentially intrinsic property of the brain is the weak coupling between networks at rest, which enables it to be flexible, adapt, process novel stimuli, and learn. Brain regions become differentially coordinated in response to cognitive task and behavior demands and external stimuli. However, abnormally synchronized...
The responsible pathological mechanisms of essential tremor are not yet clear. In order to understand the mechanisms of the central network its sources need to be found. The cortical sources of both the basic and first “harmonic” frequency of essential tremor are addressed in this paper. The power and coherence were estimated using the multitaper method for EEG and EMG data from 6 essential tremor...
Deep brain stimulation is an increasingly prevalent surgical option in the treatment of a multitude of neurological conditions, most notably Parkinson's disease. The development of a neurofeedback device is driven primarily by stimulator habituation, surgical risk factors, the cost of battery replacement, and reported neuropsychiatric side-effects under prolonged chronic administration. Here we present...
Our objective is to analyze EEG signals recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different phases are observed during the seizure process, including a fast onset activity (FOA). We aim to determine how cerebral structures get involved during this FOA, in particular whether some structure can “drive” some other structures. This paper focuses...
We examined coherence of auditory steady state responses (ASSRs) in magnetoencephalogram to an ongoing sinusoidal amplitude modulated tone presented to the subject's left ear while bursts of white noise of various intensities were presented to the right ear. The results showed a significant enhancement in the real part of coherence of ASSRs obtained from the right and left temporal regions by the...
Surface mechanomyograms (S-MMGs) are recorded from low frequency (<;100 Hz) mechanical oscillations that are naturally generated by skeletal muscle during voluntary contractions. This study investigates a method to determine the propagation directionality of the S-MMG waves. A 3 × 5 grid of skin mounted accelerometers was mounted on the biceps brachii muscle during submaximal voluntary contractions...
A signal quality classification algorithm is presented to evaluate signal quality in ambulatory monitoring system. Acoustic based signal is classified as good signal, weak signal or noisy signal. Certain features in the acquired signal are extracted and analyzed to differentiate the class of signal quality. With this classification, wrong physiological estimation due to poor signal quality can be...
The validation of a blood flow meter is presented. This flow meter is based on the transit time method that uses two ultrasound transducers and a reflector. The measuring is based on the time difference of the upstream and the downstream ultrasound transit time. The validation was based on the norm ANSI Std. N42.17A-2003 of blood flow protocol. We used a flow simulator system with 3 mm pipe, bi-distilled...
The acoustic radiation force has been used as the method to examine the physical properties of materials in several areas. Vibro-acoustography is an acoustic radiation force technique that is being used to perform analysis of mechanical properties of materials. In this application a focused acoustic modulated force excites target which vibrates at the frequency of modulation. The emitted sound is...
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