Bioresorbable thin-film silicon diodes for the optoelectronic excitation and inhibition of neural activities.

Neural activities can be modulated by leveraging light-responsive nanomaterials as interfaces for exerting photothermal, photoelectrochemical or photocapacitive effects on neurons or neural tissues. Here we show that bioresorbable thin-film monocrystalline silicon pn diodes can be used to optoelectronically excite or inhibit neural activities by establishing polarity-dependent positive or negative photovoltages at the semiconductor/solution interface. Under laser illumination, the silicon-diode optoelectronic interfaces allowed for the deterministic depolarization or hyperpolarization of cultured neurons as well as the upregulated or downregulated intracellular calcium dynamics. The optoelectronic interfaces can also be mounted on nerve tissue to activate or silence neural activities in peripheral and central nervous tissues, as we show in mice with exposed sciatic nerves and somatosensory cortices. Bioresorbable silicon-based optoelectronic thin films that selectively excite or inhibit neural tissue may find advantageous biomedical applicability.

Towards Evaluating Pitch-Related Phonation Function in Speech Communication Using High-Density Surface Electromyography.

Pitch, as a sensation of the sound frequency, is a crucial attribute toward constructing a natural voice for communication. Producing intelligible sounds with normal pitches depend on substantive interdependencies among facial and neck muscles. Clarifying the interrelations between the pitches and the corresponding muscular activities would be helpful for evaluating the pitch-related phonating functions, which would play a significant role both in training pronunciation and in assessing dysphonia. In this study, the speech signals and the high-density surface electromyography (HD sEMG) signals were synchronously acquired when phonating [a:], [i:], and [ә:] vowels with increasing pitches, respectively. The HD sEMG energy maps were constructed based on the root mean square values to visualize spatiotemporal characteristics of facial and neck muscle activities. Normalized median frequency (nMF) and root-mean square (nRMS) were correspondingly extracted from the speech and sEMG recordings to quantitatively investigate the correlations between sound frequencies and myoelectric characteristics. The results showed that the frame-wise energy maps built from sEMG recordings presented that the muscle contraction strength increased monotonously across pitch-rising, with left-right symmetrical distribution for the face/neck. Furthermore, the nRMS increased at a similar rate to the nMF when there were rising pitches, and the two parameters had a significant correlation across different vowel tasks [(a:) (0.88 ± 0.04), (i:) (0.89 ± 0.04), and (ә:) (0.87 ± 0.05)]. These findings suggested the possibility of utilizing muscle contraction patterns as a reference for evaluating pitch-related phonation functions. The proposed method could open a new window for developing a clinical approach for assessing the muscular functions of dysphonia.

Modulation of muscle synergies for multiple forearm movements under variant force and arm position constraints.

OBJECTIVE: To promote clinical applications of muscle-synergy-based neurorehabilitation techniques, this study aims to clarify any potential modulations of both the muscular compositions and temporal activations of forearm muscle synergies for multiple movements under variant force levels and arm positions. APPROACH: Two groups of healthy subjects participated in this study. Electromyography (EMG) signals were collected when they performed four hand and wrist movements under variant constraints-three different force levels for one group and five arm positions for the other. Muscle synergies were extracted from the EMGs, and their robustness across variant force levels and arm positions was separately assessed by evaluating their across-condition structure similarity, cross-validation, and cluster analysis. The synergies' activation coefficients across the variant constraints were also compared, and the coefficients were used to discriminate the different force levels and the arm positions, respectively. MAIN RESULTS: Overall, the muscle synergies were relatively fixed across variant constraints, but they were more robust to variant forces than to changing arm positions. The activations of muscle synergies depended largely on the level of contraction force and could discriminate the force levels very well, but the coefficients corresponding to different arm positions discriminated the positions with lower accuracy. Similar results were found for all types of forearm movement analyzed. SIGNIFICANCE: With our experiment and subject-specific analysis, only slight modulation of the muscular compositions of forearm muscle synergies was found under variant force and arm position constraints. Our results may shed valuable insights to future design of both muscle-synergy-based assistive robots and motor-function assessments.

The Effects of Channel Number on Classification Performance for sEMG-based Speech Recognition.

Speech recognition based on surface electromyography (sEMG) signals is an important research direction with potential applications in life, work and clinical. The number and placement of sEMG electrodes play a critical role in capturing the underlying sEMG activities and in turn, accurately classifying the speaking tasks. The aim of this work was to investigate the effect of the number of channels in speech recognition based on high-density (HD) sEMG. 8 healthy subjects were recruited to perform 11 English speech tasks with sEMG signals were detected from 120 electrodes covering almost the whole neck and face. The classification accuracy was evaluated in the context of a linear discriminant analysis (LDA) with different sets of EMG electrodes. By comparing the classification accuracy, the sequential forward search (SFS) algorithm was adopted to figure out the optimal combination of electrodes which realized the highest classification level. The results showed that smaller number of channels obtained by the SFS method could achieve the classification accuracy of 80%, and another few electrodes were needed to record detail information to achieve the classification accuracy of 85%, 90% and 95%. The numbers were rather smaller than 120. Considering the computation time and reliable accuracy, it is concluded that the SFS method might be helpful for standardizing the number and position of electrodes in speech recognition.

Robustness of Muscle Synergies under Variant Muscle Contraction Force during Forearm Movements.

The Electromyography-based Pattern-Recognition (EMG-PR) framework has been investigated for almost three decades towards developing an intuitive myoelectric prosthesis. To utilize the knowledge of the underlying neurophysiological processes of natural movements, the concept of muscle synergy has been applied in prosthesis control and proved to be of great potential recently. For a muscle-synergy-based myoelectric system, the variation of muscle contraction force is also a confounding factor. This study evaluates the robustness of muscle synergies under a variant force level for forearm movements. Six channels of forearm surface EMG were recorded from six healthy subjects when they performed 4 movements (hand open, hand close, wrist flexion, and wrist extension) using low, moderate, and high force, respectively. Muscle synergies were extracted from the EMG using the alternating nonnegativity constrained least squares and active set (NNLS) algorithm. Three analytic strategies were adopted to examine whether muscle synergies were conserved under different force levels. Our results consistently showed that there exists fixed, robust muscle synergies across force levels. This outcome would provide valuable insights to the implementation of muscle- synergy-based assistive technology for the upper extremity.

Time-frequency Analysis of Electroencephalogram Signals in a Cognitive Decision-making Task.

Choices and decisions involve a series of complex cognitive processes, and the time-frequency analysis of electroencephalogram (EEG) signals can help understand the brain activities in different cognitive tasks. In this study, a decision-making cognitive task of rock-paper-scissors was designed, and the complex decision-making task was divided into three stages (decision planning, confirmation, and feedback). 64 channels of EEG signals were simultaneously recorded using the Neuroscan QuikCap system during the whole task. The average spectral power and phase synchronization values of each frequency band (delta, theta, alpha and beta band) were extracted and compared within and across different stages. The results showed the desire to win or not to lose within the first stage might be accompanied by the increase of alpha and theta components. In the second stage, the spectral power inhibition of alpha wave and phase synchronization increase of delta wave indicated that subjects would improve their attentions when they confirmed their choice. In the third stage, the theta increased effect and alpha decreased effect were related to different feedback. This pilot study suggests that the time-frequency analysis of EEG signals could be a great tool to visualize the brain activities in response to different cognitive tasks.

Comparing Auditory Brainstem Responses evoked by Click and Sweep-Tone in Normal-Hearing Adults.

Auditory brainstem response (ABR) is an objective method via which hearing loss could be detected. ABR induced by click, a broadband signal, is generally considered as the gold standard. However, due to the inherent delay of the cochlear traveling wave, click cannot excite the entire cochlear basement membrane at the same time, leading to the attenuation of the induced ABR waveform. In order to resolve this limitation, a sweep-tone-based stimulus that reconstructs the arrival time of different frequency components with respect to the delay characteristics of cochlear basement membrane was designed and used to induce ABR in this study. Subsequently, we compared the performance of the proposed sweep-tone-induced ABR method and the commonly adopted click induced ABR at different test levels and different stimulus rates. And the obtained results showed that the waveform morphology of sweep-tone-induced ABR was significantly better than that of click induced ABR across different test levels and stimulus rates. Moreover, compared to the click induced ABR at different sweeps, we found that the proposed sweep-tone-induced ABR effectively induced the ABR waveform at a relatively faster rate. Hence, the proposed sweep-tone-induced ABR approach provides a new method to improve the sensitivity of ABR detection in hearing loss.