Understanding the different effects of fouling mechanisms on working and reference electrodes in fast-scan cyclic voltammetry for neurotransmitter detection.

Fast-scan cyclic voltammetry (FSCV) is a widely used technique for detecting neurotransmitters. However, electrode fouling can negatively impact its accuracy and sensitivity. Fouling refers to the accumulation of unwanted materials on the electrode surface, which can alter its electrochemical properties and reduce its sensitivity and selectivity. Fouling mechanisms can be broad and may include biofouling, the accumulation of biomolecules on the electrode surface, and chemical fouling, the deposition of unwanted chemical species. Despite individual studies discussing fouling effects on either the working electrode or the reference electrode, no comprehensive study has been conducted to compare the overall fouling effects on both electrodes in the context of FSCV. Here, we examined the effects of biofouling and chemical fouling on the carbon fiber micro-electrode (CFME) as the working electrode and the Ag/AgCl reference electrode with FSCV. Both fouling mechanisms significantly decreased the sensitivity and caused peak voltage shifts in the FSCV signal with the CFME, but not with the Ag/AgCl reference electrode. Interestingly, previous studies have reported peak voltage shifts in FSCV signals due to the fouling of Ag/AgCl electrodes after implantation in the brain. We noticed in a previous study that energy-dispersive spectroscopy (EDS) spectra showed increased sulfide ion concentration after implantation. We hypothesized that sulfide ions may be responsible for the peak voltage shift. To test this hypothesis, we added sulfide ions to the buffer solution, which decreased the open circuit potential of the Ag/AgCl electrode and caused a peak voltage shift in the FSCV voltammograms. Also, EDS analysis showed that sulfide ion concentration increased on the surface of the Ag/AgCl electrodes after 3 weeks of chronic implantation, necessitating consideration of sulfide ions as the fouling agent for the reference electrodes. Overall, our study provides important insights into the mechanisms of electrode fouling and its impact on FSCV measurements. These findings could inform the design of FSCV experiments, with the development of new strategies for improving the accuracy and reliability of FSCV measurements in vivo.

Deep brain stimulation alleviates tics in Tourette syndrome via striatal dopamine transmission.

Tourette syndrome is a childhood-onset neuropsychiatric disorder characterized by intrusive motor and vocal tics that can lead to self-injury and deleterious mental health complications. While dysfunction in striatal dopamine neurotransmission has been proposed to underlie tic behaviour, evidence is scarce and inconclusive. Deep brain stimulation (DBS) of the thalamic centromedian parafascicular complex (CMPf), an approved surgical interventive treatment for medical refractory Tourette syndrome, may reduce tics by affecting striatal dopamine release. Here, we use electrophysiology, electrochemistry, optogenetics, pharmacological treatments and behavioural measurements to mechanistically examine how thalamic DBS modulates synaptic and tonic dopamine activity in the dorsomedial striatum. Previous studies demonstrated focal disruption of GABAergic transmission in the dorsolateral striatum of rats led to repetitive motor tics recapitulating the major symptom of Tourette syndrome. We employed this model under light anaesthesia and found CMPf DBS evoked synaptic dopamine release and elevated tonic dopamine levels via striatal cholinergic interneurons while concomitantly reducing motor tic behaviour. The improvement in tic behaviour was found to be mediated by D2 receptor activation as blocking this receptor prevented the therapeutic response. Our results demonstrate that release of striatal dopamine mediates the therapeutic effects of CMPf DBS and points to striatal dopamine dysfunction as a driver for motor tics in the pathoneurophysiology of Tourette syndrome.

Temporally Resolved Electrochemical Interrogation for Stochastic Collision Dynamics of Electrogenerated Single Polybromide Droplets.

In this article, we present electrochemical interrogation for collision dynamics of electrogenerated individual polybromide ionic liquid (PBIL) droplets through chronoamperometry combined with fast scan cyclic voltammetry (CA-FSCV). In the CA mode of CA-FSCV, a Pt ultramicroelectrode (UME) acts as the electrochemical generator for PBIL droplets by holding the oxidation potential for Br- in a given time, while FSCV is repetitively performed at a certain frequency. In the FSCV mode of CA-FSCV, a Pt UME serves as the probe to electrochemically monitor Br3- reduction for an adsorbed PBIL droplet during collision with a high temporal resolution. Based on the newly introduced CA-FSCV, we can estimate the dynamic changes in the following parameters for a short collision time: the contact radius of a PBIL droplet on a Pt UME, the concentration of Br- in the droplet, and the apparent charge transfer rate constant for electro-reduction of Br3- to Br- in the droplet, koapp. Moreover, a computational calculation using molecular dynamics is presented that can explain the change in koapp as a function of time for Br- electrolysis in a PBIL droplet. Based on the quantitative estimation of the above parameters, we suggest a more advanced mechanism for the stochastic electrochemical collision process of a PBIL droplet. These findings are important for understanding QBr2n+1/QBr half redox reactions in aqueous energy storage systems, such as Zn-Br redox flow batteries and Br-related redox enhanced electrochemical capacitors.

Feasibility of Applying Fourier Transform Electrochemical Impedance Spectroscopy in Fast Cyclic Square Wave Voltammetry for the In Vivo Measurement of Neurotransmitters.

We previously reported on the use of fast cyclic square wave voltammetry (FCSWV) as a new voltammetric technique. Fourier transform electrochemical impedance spectroscopy (FTEIS) has recently been utilized to provide information that enables a detailed analytical description of an electrified interface. In this study, we report on attempts to combine FTEIS with FCSWV (FTEIS-FCSWV) and demonstrate the feasibility of FTEIS-FCSWV in the in vivo detection of neurotransmitters, thus giving a new type of electrochemical impedance information such as biofouling on the electrode surface. From FTEIS-FCSWV, three new equivalent circuit element voltammograms, consisting of charge-transfer resistance (Rct), solution-resistance (Rs), and double-layer capacitance (Cdl) voltammograms were constructed and investigated in the phasic changes in dopamine (DA) concentrations. As a result, all Rct, Rs, and Cdl voltammograms showed different DA redox patterns and linear trends for the DA concentration (R2 > 0.99). Furthermore, the Rct voltammogram in FTEIS-FCSWV showed lower limit of detection (21.6 ± 15.8 nM) than FSCV (35.8 ± 17.4 nM). FTEIS-FCSWV also showed significantly lower prediction errors than FSCV in selectivity evaluations of unknown mixtures of catecholamines. Finally, Cdl from FTEIS-FCSWV showed a significant relationship with fouling effect on the electrode surface by showing decreased DA sensitivity in both flow injection analysis experiment (r = 0.986) and in vivo experiments. Overall, this study demonstrates the feasibility of FTEIS-FCSWV, which could offer a new type of neurochemical spectroscopic information concerning electrochemical monitoring of neurotransmitters in the brain, and the ability to estimate the degree of sensitivity loss caused by biofouling on the electrode surface.

Tonic Serotonin Measurements In Vivo Using N-Shaped Multiple Cyclic Square Wave Voltammetry.

Here, we present the development of a novel voltammetric technique, N-shaped multiple cyclic square wave voltammetry (N-MCSWV) and its application in vivo. It allows quantitative measurements of tonic extracellular levels of serotonin in vivo with mitigated fouling effects. N-MCSWV enriches the electrochemical information by generating high dimensional voltammograms, which enables high sensitivity and selectivity against 5-hydroindoleacetic acid (5-HIAA), dopamine, 3,4-dihydroxyphenylacetic acid (DOPAC), histamine, ascorbic acid, norepinephrine, adenosine, and pH. Using N-MCSWV, in combination with PEDOT:Nafion-coated carbon fiber microelectrodes, a tonic serotonin concentration of 52 ± 5.8 nM (n = 20 rats, ±SEM) was determined in the substantia nigra pars reticulata of urethane-anesthetized rats. Pharmacological challenges with dopaminergic, noradrenergic, and serotonergic synaptic reuptake inhibitors supported the ability of N-MCSWV to selectively detect tonic serotonin levels in vivo. Overall, N-MCSWV is a novel voltammetric technique for analytical quantification of serotonin. It offers continuous monitoring of changes in tonic serotonin concentrations in the brain to further our understanding of the role of serotonin in normal behaviors and psychiatric disorders.

Sensitive and Selective Measurement of Serotonin in Vivo Using Fast Cyclic Square-Wave Voltammetry.

Although N-shaped fast scan cyclic voltammetry (N-FSCV) is well-established as an electroanalytical method to measure extracellular serotonin concentrations in vivo, it is in need of improvement in both sensitivity and selectivity. Based on our previous studies using fast cyclic square-wave voltammetry (FCSWV) for in vivo dopamine measurements, we have modified this technique to optimize the detection of serotonin in vivo. A series of large amplitude square-shaped potentials was superimposed onto an N-shaped waveform to provide cycling through multiple redox reactions within the N-shaped waveform to enhance the sensitivity and selectivity to serotonin measurement when combined with a two-dimensional voltammogram. N-Shaped fast cyclic square-wave voltammetry (N-FCSWV) showed significantly higher sensitivity to serotonin compared to conventional N-FSCV. In addition, N-FCSWV showed better performance than conventional N-shaped FSCV in differentiating serotonin from its major interferents, dopamine and 5-hydroxyindoleascetic acid (5-HIAA). It was also confirmed that the large amplitude of the square waveform did not influence local neuronal activity, and it could monitor electrical stimulation evoked phasic release of serotonin in the rat substantia nigra pars reticulata (SNr) before and after systemic injection of escitalopram (ESCIT, 10 mg/kg i.p.), a serotonin selective reuptake inhibitor.

Differences in theta coherence between spatial and nonspatial attention using intracranial electroencephalographic signals in humans.

A number of previous studies revealed the importance of the frontoparietal network for attention and preparatory top-down control. Here, we investigated the theta (7-9 Hz) coherence of the right frontoparietal networks to explore the differences in connectivity changes for the right frontoparietal regions during spatial attention (i.e., attention to a specific location rather than a specific feature) and nonspatial attention (i.e., attention to a specific feature rather than a specific location) tasks. The theta coherence in both tasks was primarily maintained at a preparatory state, decreases after stimulus onset, and recovers to the level of the preparatory state after the response time. However, the theta coherence of the frontoparietal network during spatial attention was immediately maintained after cue-onset, whereas for the case of nonspatial attention, it was immediately decreased after cue-onset. In addition, the connectivity of the right frontoparietal network, including the middle frontal gyrus and superior parietal lobe, were significantly higher for spatial attention rather than for nonspatial attention, suggesting that the dorsal parts of right frontoparietal network are more engaged in spatial-specific attention from the preparatory state. These findings also suggest that these two attention systems involve the use of different regional connectivity patterns, not only in the cognitive state, but in the preparatory state as well.

Fast Cyclic Square-Wave Voltammetry To Enhance Neurotransmitter Selectivity and Sensitivity.

Although fast-scan cyclic voltammetry (FSCV) has been widely used for in vivo neurochemical detection, the sensitivity and selectivity of the technique can be further improved. In this study, we develop fast cyclic square-wave voltammetry (FCSWV) as a novel voltammetric technique that combines large-amplitude cyclic square-wave voltammetry (CSWV) with background subtraction. A large-amplitude, square-shaped potential was applied to induce cycling through multiple redox reactions within a square pulse to increase sensitivity and selectivity when combined with a two-dimensional voltammogram. As a result, FCSWV was significantly more sensitive than FSCV ( n = 5 electrodes, two-way ANOVA, p = 0.0002). In addition, FCSWV could differentiate dopamine from other catecholamines (e.g., epinephrine and norepinephrine) and serotonin better than conventional FSCV. With the confirmation that FCSWV did not influence local neuronal activity, despite the large amplitude of the square waveform, it could monitor electrically induced phasic changes in dopamine release in rat striatum before and after injecting nomifensine, a dopamine reuptake inhibitor.

A baseline drift detrending technique for fast scan cyclic voltammetry.

Fast scan cyclic voltammetry (FSCV) has been commonly used to measure extracellular neurotransmitter concentrations in the brain. Due to the unstable nature of the background currents inherent in FSCV measurements, analysis of FSCV data is limited to very short amounts of time using traditional background subtraction. In this paper, we propose the use of a zero-phase high pass filter (HPF) as the means to remove the background drift. Instead of the traditional method of low pass filtering across voltammograms to increase the signal to noise ratio, a HPF with a low cutoff frequency was applied to the temporal dataset at each voltage point to remove the background drift. As a result, the HPF utilizing cutoff frequencies between 0.001 Hz and 0.01 Hz could be effectively used to a set of FSCV data for removing the drifting patterns while preserving the temporal kinetics of the phasic dopamine response recorded in vivo. In addition, compared to a drift removal method using principal component analysis, this was found to be significantly more effective in reducing the drift (unpaired t-test p < 0.0001, t = 10.88) when applied to data collected from Tris buffer over 24 hours although a drift removal method using principal component analysis also showed the effective background drift reduction. The HPF was also applied to 5 hours of FSCV in vivo data. Electrically evoked dopamine peaks, observed in the nucleus accumbens, were clearly visible even without background subtraction. This technique provides a new, simple, and yet robust, approach to analyse FSCV data with an unstable background.

An Eye-Blinking-Based Beamforming Control Protocol for Hearing Aid Users With Neurological Motor Disease or Limb Amputation.

For hearing-impaired individuals with neurological motor deficits or finger/arm amputation due to accident or disease, hearing aid adjustment using a conventional finger manipulation-based remote controller is unavailable, and a more dedicated, hands-free alternative is required. In this study, we propose an eye-blinking-based beamforming control scheme for hearing aid users. Three electroencephalogram signals measured around the ears were utilized to detect eye-blinking patterns based on a three-layer artificial neural network. The performance of the proposed control scheme was evaluated by both subjective experiments and objective index comparison tests in simulated situations. Experimental results from the subjective test demonstrated that without the pretraining phase, the accuracy and latency time were 68.57 ± 18.50% and 10.06 ± 0.94 s, respectively; in contrast, after the pretraining phase, both the accuracy and latency time were improved to 91.00 ± 4.69% and 8.60 ± 1.05 s, respectively. In index comparison tests, the proposed control scheme exhibited improvements in the signal-to-noise ratio (SNR) as well as the segmental SNR in all tested situations, as compared to a conventional forward-focusing beamforming algorithm. We believe that the proposed control scheme provides a novel, hands-free way in which to control the operation of hearing aids for hearing-impaired patients with additional motor deficits or amputation.

Decoding Saccadic Directions Using Epidural ECoG in Non-Human Primates.

A brain-computer interface (BCI) can be used to restore some communication as an alternative interface for patients suffering from locked-in syndrome. However, most BCI systems are based on SSVEP, P300, or motor imagery, and a diversity of BCI protocols would be needed for various types of patients. In this paper, we trained the choice saccade (CS) task in 2 non-human primate monkeys and recorded the brain signal using an epidural electrocorticogram (eECoG) to predict eye movement direction. We successfully predicted the direction of the upcoming eye movement using a support vector machine (SVM) with the brain signals after the directional cue onset and before the saccade execution. The mean accuracies were 80% for 2 directions and 43% for 4 directions. We also quantified the spatial-spectro-temporal contribution ratio using SVM recursive feature elimination (RFE). The channels over the frontal eye field (FEF), supplementary eye field (SEF), and superior parietal lobule (SPL) area were dominantly used for classification. The α-band in the spectral domain and the time bins just after the directional cue onset and just before the saccadic execution were mainly useful for prediction. A saccade based BCI paradigm can be projected in the 2D space, and will hopefully provide an intuitive and convenient communication platform for users.

A Supporting Platform for Semi-Automatic Hyoid Bone Tracking and Parameter Extraction from Videofluoroscopic Images for the Diagnosis of Dysphagia Patients.

Conventional kinematic analysis of videofluoroscopic (VF) swallowing image, most popular for dysphagia diagnosis, requires time-consuming and repetitive manual extraction of diagnostic information from multiple images representing one swallowing period, which results in a heavy work load for clinicians and excessive hospital visits for patients to receive counseling and prescriptions. In this study, a software platform was developed that can assist in the VF diagnosis of dysphagia by automatically extracting a two-dimensional moving trajectory of the hyoid bone as well as 11 temporal and kinematic parameters. Fifty VF swallowing videos containing both non-mandible-overlapped and mandible-overlapped cases from eight patients with dysphagia of various etiologies and 19 videos from ten healthy controls were utilized for performance verification. Percent errors of hyoid bone tracking were 1.7 ± 2.1% for non-overlapped images and 4.2 ± 4.8% for overlapped images. Correlation coefficients between manually extracted and automatically extracted moving trajectories of the hyoid bone were 0.986 ± 0.017 (X-axis) and 0.992 ± 0.006 (Y-axis) for non-overlapped images, and 0.988 ± 0.009 (X-axis) and 0.991 ± 0.006 (Y-axis) for overlapped images. Based on the experimental results, we believe that the proposed platform has the potential to improve the satisfaction of both clinicians and patients with dysphagia.

Comparing the standards of one metabolic equivalent of task in accurately estimating physical activity energy expenditure based on acceleration.

The purpose of the study is to analyse how the standard of resting metabolic rate (RMR) affects estimation of the metabolic equivalent of task (MET) using an accelerometer. In order to investigate the effect on estimation according to intensity of activity, comparisons were conducted between the 3.5 ml O2 · kg-1 · min-1 and individually measured resting VO2 as the standard of 1 MET. MET was estimated by linear regression equations that were derived through five-fold cross-validation using 2 types of MET values and accelerations; the accuracy of estimation was analysed through cross-validation, Bland and Altman plot, and one-way ANOVA test. There were no significant differences in the RMS error after cross-validation. However, the individual RMR-based estimations had as many as 0.5 METs of mean difference in modified Bland and Altman plots than RMR of 3.5 ml O2 · kg-1 · min-1. Finally, the results of an ANOVA test indicated that the individual RMR-based estimations had less significant differences between the reference and estimated values at each intensity of activity. In conclusion, the RMR standard is a factor that affects accurate estimation of METs by acceleration; therefore, RMR requires individual specification when it is used for estimation of METs using an accelerometer.

Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures.

Generalized tonic-clonic seizures (GTCSs) can be underestimated and can also increase mortality rates. The monitoring devices used to detect GTCS events in daily life are very helpful for early intervention and precise estimation of seizure events. Several studies have introduced methods for GTCS detection using an accelerometer (ACM), electromyography, or electroencephalography. However, these studies need to be improved with respect to accuracy and user convenience. This study proposes the use of an ACM banded to the wrist and spectral analysis of ACM data to detect GTCS in daily life. The spectral weight function dependent on GTCS was used to compute a GTCS-correlated score that can effectively discriminate between GTCS and normal movement. Compared to the performance of the previous temporal method, which used a standard deviation method, the spectral analysis method resulted in better sensitivity and fewer false positive alerts. Finally, the spectral analysis method can be implemented in a GTCS monitoring device using an ACM and can provide early alerts to caregivers to prevent risks associated with GTCS.

Monitoring In Vivo Changes in Tonic Extracellular Dopamine Level by Charge-Balancing Multiple Waveform Fast-Scan Cyclic Voltammetry.

Dopamine (DA) modulates central neuronal activity through both phasic (second to second) and tonic (minutes to hours) terminal release. Conventional fast-scan cyclic voltammetry (FSCV), in combination with carbon fiber microelectrodes, has been used to measure phasic DA release in vivo by adopting a background subtraction procedure to remove background capacitive currents. However, measuring tonic changes in DA concentrations using conventional FSCV has been difficult because background capacitive currents are inherently unstable over long recording periods. To measure tonic changes in DA concentrations over several hours, we applied a novel charge-balancing multiple waveform FSCV (CBM-FSCV), combined with a dual background subtraction technique, to minimize temporal variations in background capacitive currents. Using this method, in vitro, charge variations from a reference time point were nearly zero for 48 h, whereas with conventional background subtraction, charge variations progressively increased. CBM-FSCV also demonstrated a high selectivity against 3,4-dihydroxyphenylacetic acid and ascorbic acid, two major chemical interferents in the brain, yielding a sensitivity of 85.40 ± 14.30 nA/µM and limit of detection of 5.8 ± 0.9 nM for DA while maintaining selectivity. Recorded in vivo by CBM-FSCV, pharmacological inhibition of DA reuptake (nomifensine) resulted in a 235 ± 60 nM increase in tonic extracellular DA concentrations, while inhibition of DA synthesis (α-methyl-dl-tyrosine) resulted in a 72.5 ± 4.8 nM decrease in DA concentrations over a 2 h period. This study showed that CBM-FSCV may serve as a unique voltammetric technique to monitor relatively slow changes in tonic extracellular DA concentrations in vivo over a prolonged time period.

Neural correlates of spatial and nonspatial attention determined using intracranial electroencephalographic signals in humans.

Few studies have directly compared the neural correlates of spatial attention (i.e., attention to a particular location) and nonspatial attention (i.e., attention to a feature in the visual scene) using well-controlled tasks. Here, we investigated the neural correlates of spatial and nonspatial attention in humans using intracranial electroencephalography. The topography and number of electrodes showing significant event-related desynchronization (ERD) or event-related synchronization (ERS) in different frequency bands were studied in 13 epileptic patients. Performance was not significantly different between the two conditions. In both conditions, ERD in the low-frequency bands and ERS in the high-frequency bands were present bilaterally in the parietal cortex (prominently on the right hemisphere) and frontal regions. In addition to these common changes, spatial attention involved right-lateralized activity that was maximal in the right superior parietal lobule (SPL), whereas nonspatial attention involved wider brain networks including the bilateral parietal, frontal, and temporal regions, but still had maximal activity in the right parietal lobe. Within the parietal lobe, spatial attention involved ERD or ERS in the right SPL, whereas nonspatial attention involved ERD or ERS in the right inferior parietal lobule. These findings reveal that common as well as different brain networks are engaged in spatial and nonspatial attention. Hum Brain Mapp 37:3041-3054, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Low-frequency oscillations in cerebrovascular and cardiovascular hemodynamics: Their interrelationships and the effect of age.

The aim of this study was to investigate how the interrelationships between low-frequency oscillations (LFOs) in the cerebral and systemic cardiovascular hemodynamic systems change with aging and systemic hemodynamic perturbation. Seventeen young adult (28.4±3.5years) and seventeen elderly subjects (69.4±8.7years) underwent continuous measurements of arterial blood pressure (ABP), heart rate (HR), and cerebral oxygenation (oxy-hemoglobin, deoxy-hemoglobin, and total hemoglobin) using near-infrared spectroscopy. The LFOs were subdivided into three frequency intervals (FI-1: 0.01-0.02Hz, FI-2: 0.02-0.06Hz, and FI-3: 0.06-0.15Hz) via spectral analysis based on continuous wavelet transform. The amplitudes of the LFOs at these FIs were calculated to examine the effects of aging and head-up tilt (HUT) on cerebral and cardiovascular hemodynamics. Granger causality (GC) was used for analyzing the causal relationships between the LFOs observed in ABP, oxy-hemoglobin, and HR. The amplitudes of the LFOs were generally higher in young adults than in the elderly and increased significantly only in the younger subjects after HUT. GCs in FI-3 oscillations were significantly higher in young subjects compared to older participants in the HUT state. These results indicate that aging dampens systemic and cerebral hemodynamic regulatory mechanisms, and the interrelationships between systemic and cerebral hemodynamics become weaker with age.

A Diagonal-Steering-Based Binaural Beamforming Algorithm Incorporating a Diagonal Speech Localizer for Persons With Bilateral Hearing Impairment.

Previously suggested diagonal-steering algorithms for binaural hearing support devices have commonly assumed that the direction of the speech signal is known in advance, which is not always the case in many real circumstances. In this study, a new diagonal-steering-based binaural speech localization (BSL) algorithm is proposed, and the performances of the BSL algorithm and the binaural beamforming algorithm, which integrates the BSL and diagonal-steering algorithms, were evaluated using actual speech-in-noise signals in several simulated listening scenarios. Testing sounds were recorded in a KEMAR mannequin setup and two objective indices, improvements in signal-to-noise ratio (SNRi ) and segmental SNR (segSNRi ), were utilized for performance evaluation. Experimental results demonstrated that the accuracy of the BSL was in the 90-100% range when input SNR was -10 to +5 dB range. The average differences between the γ-adjusted and γ-fixed diagonal-steering algorithms (for -15 to +5 dB input SNR) in the talking in the restaurant scenario were 0.203-0.937 dB for SNRi and 0.052-0.437 dB for segSNRi , and in the listening while car driving scenario, the differences were 0.387-0.835 dB for SNRi and 0.259-1.175 dB for segSNRi . In addition, the average difference between the BSL-turned-on and the BSL-turned-off cases for the binaural beamforming algorithm in the listening while car driving scenario was 1.631-4.246 dB for SNRi and 0.574-2.784 dB for segSNRi . In all testing conditions, the γ-adjusted diagonal-steering and BSL algorithm improved the values of the indices more than the conventional algorithms. The binaural beamforming algorithm, which integrates the proposed BSL and diagonal-steering algorithm, is expected to improve the performance of the binaural hearing support devices in noisy situations.

An environment-adaptive management algorithm for hearing-support devices incorporating listening situation and noise type classifiers.

In order to provide more consistent sound intelligibility for the hearing-impaired person, regardless of environment, it is necessary to adjust the setting of the hearing-support (HS) device to accommodate various environmental circumstances. In this study, a fully automatic HS device management algorithm that can adapt to various environmental situations is proposed; it is composed of a listening-situation classifier, a noise-type classifier, an adaptive noise-reduction algorithm, and a management algorithm that can selectively turn on/off one or more of the three basic algorithms-beamforming, noise-reduction, and feedback cancellation-and can also adjust internal gains and parameters of the wide-dynamic-range compression (WDRC) and noise-reduction (NR) algorithms in accordance with variations in environmental situations. Experimental results demonstrated that the implemented algorithms can classify both listening situation and ambient noise type situations with high accuracies (92.8-96.4% and 90.9-99.4%, respectively), and the gains and parameters of the WDRC and NR algorithms were successfully adjusted according to variations in environmental situation. The average values of signal-to-noise ratio (SNR), frequency-weighted segmental SNR, Perceptual Evaluation of Speech Quality, and mean opinion test scores of 10 normal-hearing volunteers of the adaptive multiband spectral subtraction (MBSS) algorithm were improved by 1.74 dB, 2.11 dB, 0.49, and 0.68, respectively, compared to the conventional fixed-parameter MBSS algorithm. These results indicate that the proposed environment-adaptive management algorithm can be applied to HS devices to improve sound intelligibility for hearing-impaired individuals in various acoustic environments.

A new asymmetric directional microphone algorithm with automatic mode-switching ability for binaural hearing support devices.

For hearing support devices, it is important to minimize the negative effect of ambient noises for speech recognition but also, at the same time, supply natural ambient sounds to the hearing-impaired person. However, conventional fixed bilateral asymmetric directional microphone (DM) algorithms cannot perform in such a way when the DM-mode device and a dominant noise (DN) source are placed on the same lateral hemisphere. In this study, a new binaural asymmetric DM algorithm that can overcome the defects of conventional algorithms is proposed. The proposed algorithm can estimate the position of a specific DN in the 90°-270° range and switch directional- and omnidirectional-mode devices automatically if the DM-mode device and the DN are placed in opposite lateral hemispheres. Computer simulation and KEMAR mannequin recording tests demonstrated that the performance of the conventional algorithm deteriorated when the DM-mode device and the DN were placed in the opposite hemisphere; in contrast, the performance of the proposed algorithm was consistently maintained regardless of directional variations in the DN. Based on these experimental results, the proposed algorithm may be able to improve speech quality and intelligibility for hearing-impaired persons who have similar degrees of hearing impairment in both ears.