Swallowing is a continuous process with substantive interdependencies among different muscles, and it plays a significant role in our daily life. The aim of this study was to propose a novel technique based on high-density surface electromyography (HD sEMG) for the evaluation of normal swallowing functions. A total of 96 electrodes were placed on the front neck to acquire myoelectric signals from 12 healthy subjects while they were performing different swallowing tasks. HD sEMG energy maps were constructed based on the root mean square values to visualize muscular activities during swallowing. The effects of different volumes, viscosities, and head postures on the normal swallowing process were systemically investigated by using the energy maps. The results showed that the HD sEMG energy maps could provide detailed spatial and temporal properties of the muscle electrical activity, and visualize the muscle contractions that closely related to the swallowing function. The energy maps also showed that the swallowing time and effort was also explicitly affected by the volume and viscosity of the bolus. The concentration of the muscular activities shifted to the opposite side when the subjects turned their head to either side. The proposed method could provide an alternative method to physiologically evaluate the dynamic characteristics of normal swallowing and had the advantage of providing a full picture of how different muscle activities cooperate in time and location. The findings from this study suggested that the HD sEMG technique might be a useful tool for fast screening and objective assessment of swallowing disorders or dysphagia.

Biopotential signals are mainly characterized by low amplitude and thus often distorted by extraneous interferences, such as power line interference in the recording environment and movement artifacts during the acquisition process. With the presence of such large-amplitude interferences, subsequent processing and analysis of the acquired signals becomes quite a challenging task that has been reported by many previous studies. A number of software-based filtering techniques have been proposed, with most of them being able to minimize the interferences but at the expense of distorting the useful components of the target signal. Therefore, this study proposes a hardware-based method that utilizes a shielded drive circuit to eliminate extraneous interferences on biopotential signal recordings, while also preserving all useful components of the target signal. The performance of the proposed method was evaluated by comparing the results with conventional hardware and software filtering methods in three different biopotential signal recording experiments (electrocardiogram (ECG), electro-oculogram (EOG), and electromyography (EMG)) on an ADS1299EEG-FE platform. The results showed that the proposed method could effectively suppress power line interference as well as its harmonic components, and it could also significantly eliminate the influence of unwanted electrode lead jitter interference. Findings from this study suggest that the proposed method may provide potential insight into high quality acquisition of different biopotential signals to greatly ease subsequent processing in various biomedical applications.

The constantly rising number of limb stroke survivors and amputees has motivated the development of intelligent prosthetic/rehabilitation devices for their arm function restoration. The device often integrates a pattern recognition (PR) algorithm that decodes amputees’ limb movement intent from electromyogram (EMG) signals, characterized by neural information and symmetric distribution. However, the control performance of the prostheses mostly rely on the interrelations among multiple dynamic factors of feature set, windowing parameters, and signal conditioning that have rarely been jointly investigated to date. This study systematically investigated the interaction effects of these dynamic factors on the performance of EMG-PR system towards constructing optimal parameters for accurately robust movement intent decoding in the context of prosthetic control. In this regard, the interaction effects of various features across window lengths (50 ms~300 ms), increments (50 ms~125 ms), robustness to external interferences and sensor channels (2 ch~6 ch), were examined using EMG signals obtained from twelve subjects through a symmetrical movement elicitation protocol. Compared to single features, multiple features consistently achieved minimum decoding error below 10% across optimal windowing parameters of 250 ms/100 ms. Also, the multiple features showed high robustness to additive noise with obvious trade-offs between accuracy and computation time. Consequently, our findings may provide proper insight for appropriate parameter selection in the context of robust PR-based control strategy for intelligent rehabilitation device.

Objective . The auditory brainstem response (ABR) audiometry is a means of assessing the functional status of the auditory neural pathway in the clinic. The conventional click ABR test lacks good neural synchrony and it mainly evaluates high-frequency hearing while the common tone-burst ABR test only detects hearing loss of a certain frequency at a time. Additionally, the existing chirp stimuli are designed based on average data of cochlear characteristics, ignoring individual differences amongst subjects. Approach . Therefore, this study designed a new stimulus approach based on a sweep-tone concept with a time variant and spectrum characteristics that could be customized based on an individual’s cochlear characteristics. To validate the efficiency of the proposed method, we compared its performance with the click and tone-bursts using ABR recordings from 11 normal-hearing adults. Main results . Experimental results showed that the proposed sweep-tone ABR achieved a higher amplitude compared with those elicited by the click and tone-bursts. When the stimulus level or rate was varied, the sweep-tone ABR consistently elicited a larger response than the corresponding click ABR. Moreover, the sweep-tone ABR appeared earlier than the click ABR under the same conditions. Specifically, the mean wave V peak-to-peak amplitude of the sweep-tone ABR was 1.3 times that of the click ABR at 70 dB nHL (normal hearing level) and a rate of 20 s ⁻¹ , in which the former saved 40% of test time. Significance . In summary, the proposed sweep-tone approach is found to be more efficient than the traditional click and tone-burst in eliciting ABR.