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The gap-startle paradigm has been used as a behavioral method for tinnitus screening in animal studies. This study aimed to investigate gap prepulse inhibition (GPI) of the auditory late response (ALR) as the objective response of the gap-intense sound paradigm in humans. ALRs were recorded in response to gap-intense and no-gap-intense sound stimuli in 27 healthy subjects. The amplitudes of the baseline-to-peak (N1, P2, and N2) and the peak-to-peak (N1P2 and P2N2) were compared between two averaged ALRs. The variations in the inhibition ratios of N1P2 and P2N2 during the experiment were analyzed by increasing stimuli repetitions. The effect of stimulus parameter adjustments on GPI ratios was evaluated. No-gap-intense sound stimuli elicited greater peak amplitudes than gap-intense sound stimuli, and significant differences were found across all peaks. The overall mean inhibition ratios were significantly lower than 1.0, where the value 1.0 indicates that there were no differences between gap-intense and no-gap-intense sound responses. The initial decline in GPI ratios was shown in N1P2 and P2N2 complexes, and this reduction was nearly complete after 100 stimulus repetitions. Significant effects of gap length and interstimulus interval on GPI ratios were observed. We found significant inhibition of ALR peak amplitudes in performing the gap-intense sound paradigm in healthy subjects. The N1P2 complex represented GPI well in terms of suppression degree and test-retest reliability. Our findings offer practical information for the comparative study of healthy subjects and tinnitus patients using the gap-intense sound paradigm with the ALR.

BackgroundOne of the key issues in electroencephalogram (EEG) monitoring is accurate signal acquisition with less cumbersome electrodes. In this study, the L2 phase electro-deposited nanoporous platinum (L2-ePt) electrode is introduced, which is a new type of electrode that utilizes a stable nanoporous platinum surface to reduce the skin-electrode impedance.MethodsL2-ePt electrodes were fabricated using electro-deposition technique. Then, the effect of the nanoporous surface on the surface roughness and the electrode impedance were observed from the L2-ePt electrodes and the flat platinum (FlatPt) electrode. The skin-electrode impedances of the L2-ePt electrodes, a gold cup electrode, and the FlatPt electrode were evaluated when placed on the hairy occipital area of the head in ten subjects. For the validation of using the L2-ePt electrode, a correlational analysis of the alpha rhythms was performed in the same subjects for simultaneous EEG recordings using the L2-ePt and clinically-used EEG electrodes.ResultsThe results indicated that the L2-ePt electrode with a roughness factor of 200 had the lowest mean impedance performance. Moreover, the proposed L2-ePt electrode showed a significantly lower mean skin-electrode impedance than the FlatPt electrode. Finally, the EEG signal quality recorded by the L2-ePt electrode (r = 0.94) was comparable to that of the clinically-used gold cup electrode.ConclusionBased on these results, the proposed L2-ePt electrode is suitable for use in various high-quality EEG applications.

BACKGROUND: Low success and high recurrence of benign paroxysmal positional vertigo (BPPV) after home-based self-treated Epley and Barbeque (BBQ) roll maneuvers is an important issue. OBJECTIVE: To quantify the cause of low success rate of self-treated Epley and BBQ roll maneuvers and provide a clinically acceptable criterion to guide self-treatment head rotations. METHODS: Twenty-five participants without active BPPV wore a custom head-mount rotation monitoring device for objective measurements. Self-treatment and specialist-assisted maneuvers were compared for head rotation accuracy. Absolute differences between the head rotation evaluation criteria (American Academy of Otolaryngology guidelines) and measured rotation angles were considered as errors. Self-treatment and specialist-treated errors in maneuvers were compared. Between-trial variations and age effects were evaluated. RESULTS: A significantly large error and between-trial variation occurred in step 4 of the self-treated Epley maneuver, with a considerable error in the second trial. The cumulative error of all steps of self-treated BBQ roll maneuver was significantly large. Age effect occurred only in the self-treated BBQ roll maneuver. Errors in specialist-treated maneuvers ranged from 10 to 20 degrees. CONCLUSIONS: Real-time feedback of head movements during simultaneous head-body rotations could increase success rates of self-treatments. Specialist-treated maneuvers can be used as permissible rotation margin criteria.

Objective: To mitigate damage from falls, it is essential to provide medical attention expeditiously. Many previous studies have focused on detecting falls and have shown that falls can be accurately detected at least in a laboratory setting. However, a very few studies have classified the different types of falls. To this end, in this paper, a novel energy-efficient algorithm that can discriminate the five most common fall types was developed for wearable systems. Methods: A wearable system with an inertial measurement unit sensor was first developed. Then, our novel algorithm, temporal signal angle measurement (TSAM), was used to classify the different types of falls at various sampling frequencies, and the results were compared with those from three different machine learning algorithms. Results: The overall performance of the TSAM and that of the machine learning algorithms were similar. However, the TSAM outperformed the machine learning algorithms at frequencies in the range of 10-20 Hz. As the sampling frequency dropped from 200 to 10Hz, the accuracy of the TSAM ranged from 93.3% to 91.8%. The sensitivity and specificity ranges from 93.3% to 91.8%, and 98.3% to 97.9%, respectively for the same frequency range. Conclusion: Our algorithm can be utilized with energy-efficient wearable devices at low sampling frequencies to classify different types of falls. Significance: Our system can expedite medical assistance in emergency situations caused by falls by providing the necessary information to medical doctors or clinicians. INDEX TERMS Fall detection, fall type classification, machine learning, temporal signal angle measurement, wearable device.