Measuring Speech Discrimination Ability in Sleeping Infants Using fNIRS-A Proof of Principle.

This study used functional near-infrared spectroscopy (fNIRS) to measure aspects of the speech discrimination ability of sleeping infants. We examined the morphology of the fNIRS response to three different speech contrasts, namely "Tea/Ba," "Bee/Ba," and "Ga/Ba." Sixteen infants aged between 3 and 13 months old were included in this study and their fNIRS data were recorded during natural sleep.

Comparing Patient-Specific Variations in Intra-Cochlear Neural Health Estimated Using Psychophysical Thresholds and Panoramic Electrically Evoked Compound Action Potentials (PECAPs).

Purpose: Variations in neural survival along the cochlear implant electrode array leads to off-place listening, resulting in poorer speech understanding outcomes for recipients. Therefore, it is important to develop and compare clinically viable tests to identify these patient-specific intra-cochlear neural differences.

Methods: Nineteen experienced cochlear implant recipients (9 males and 10 females) were recruited for this study.

Resting-State Functional Connectivity Predicts Cochlear-Implant Speech Outcomes.

Objectives: Cochlear implants (CIs) have revolutionized hearing restoration for individuals with severe or profound hearing loss. However, a substantial and unexplained variability persists in CI outcomes, even when considering subject-specific factors such as age and the duration of deafness. In a pioneering study, we use resting-state functional near-infrared spectroscopy to predict speech-understanding outcomes before and after CI implantation.

Brain Functional Connectivity Networks do not Return to Resting-state During Control Trials in Block Design Experiments.

Many studies on morphology analysis show that if short inter-stimulus intervals separate tasks, the hemodynamic response amplitude will return to the resting-state baseline before the subsequent stimulation onset; hence, responses to successive tasks do not overlap. Accordingly, popular brain imaging analysis techniques assume changes in hemodynamic response amplitude subside after a short time (around 15 seconds). However, whether this assumption holds when studying brain functional connectivity has yet to be investigated.

A Parametric Model for Characterizing Time-Variant Single Trials of Block-Design fNIRS Experiments.

Block-design is a popular experimental paradigm for functional near-infrared spectroscopy (fNIRS). Traditional block-design analysis techniques such as generalized linear modeling (GLM) and waveform averaging (WA) assume that the brain is a time-invariant system. This is a flawed assumption.

Impulse Data Models for the Inverse Problem of Electrocardiography.

Objective: To develop, train and test neural networks for predicting heart surface potentials (HSPs) from body surface potentials (BSPs). The method re-frames traditional inverse problems of electrocardiography into regression problems, constraining the solution space by decomposing signals with multidimensional Gaussian impulse basis functions.

Methods: Impulse HSPs were generated with single Gaussian basis functions at discrete heart surface locations and projected to corresponding BSPs using a volume conductor torso model.

A machine learning approach to reconstruction of heart surface potentials from body surface potentials.

Invasive cardiac catheterisation is a precursor to ablation therapy for ventricular tachycardia. Invasive cardiac diagnostics are fraught with risks. Decades of research has been conducted on the inverse problem of electrocardiography, which can be used to reconstruct Heart Surface Potentials (HSPs) from Body Surface Potentials (BSPs), for non-invasive cardiac diagnostics.

Parametric Modeling of Electrocardiograms using Particle Swarm optimization.

The electrocardiogram (ECG) is commonly used to monitor or diagnose adverse heart conditions. While general ECG recordings are widely available, parametric ECG models have been proposed to generate ECG-like signals. Such ECG generators can create extended segments of specific beat morphology or cardiac rhythm, especially in disease states, which can be used to validate cardiac devices or evaluate ECG processing algorithms.