A preliminary evaluation of myoelectrical energy distribution of the front neck muscles in pharyngeal phase during normal swallowing

Differentiation of Bolus Texture During Deglutition via High-Density Surface Electromyography: A Pilot Study

OBJECTIVE

Swallowing is a complex neuromuscular task. There is limited spatiotemporal data on normative surface electromyographic signal during swallow, particularly across standard textures. We hypothesize the pattern of electromyographic signal of the anterior neck varies cranio-caudally, that laterality can be evaluated, and categorization of bolus texture can be differentiated by high-density surface electromyography (HDsEMG) through signal analysis.

METHODS

An HDsEMG grid of 20 electrodes captured electromyographic activity in eight healthy adult subjects across 240 total swallows. Participants swallowed five standard textures: saliva, thin liquid, puree, mixed consistency, and dry solid. Data were bandpass filtered, underwent functional alignment of signal, and then placed into binary classifier receiver operating characteristic (ROC) curves. Muscular activity was visualized by creating two-dimensional EMG heat maps.

RESULTS

Signal analysis results demonstrated a positive correlation between signal amplitude and bolus texture. Greater differences of amplitude in the cranial most region of the array when compared to the caudal most region were noted in all subjects. Lateral comparison of the array revealed symmetric power levels across all subjects and textures. ROC curves demonstrated the ability to correctly classify textures within subjects in 6 of 10 texture comparisons.

CONCLUSION

This pilot study suggests that utilizing HDsEMG during deglutition can noninvasively differentiate swallows of varying texture noninvasively. This may prove useful in future diagnostic and behavioral swallow applications.

LEVEL OF EVIDENCE

4 Laryngoscope, 133:2695-2703, 2023.

A robust HD-sEMG sensor suitable for convenient acquisition of muscle activity in clinical post-stroke dysphagia

Objective.A flexible high-density surface electromyography (HD-sEMG) sensor combined with an adaptive algorithm was used to collect and analyze the swallowing activities of patients with Post-stroke dysphagia.Approach.The electrode frame, modified electrode, and bonded substrate of the sensor were fabricated using a flexible printed circuit process, controlled drop coating, and molding, respectively. The adaptation algorithm was achieved by using Laplace and Teager-Kaiser energy operators to extract active segments, a cross-correlation coefficient matrix (CCCM) to evaluate synergy, and multi-frame real-time dynamic root mean square (RMS) to visualize spatiotemporal information to screen lesions and level of dysphagia. Finally, support vector machines (SVM) were adopted to explore the classification accuracy of sex, age, and lesion location with small sample sizes.Main results.The sensor not only has a basic low contact impedance (0.262 kΩ) and high signal-to-noise ratio (37.284 ± 1.088 dB) but also achieves other characteristics suitable for clinical applications, such as flexibility (747.67 kPa) and durability (1000 times) balance, simple operation (including initial, repeated, and replacement use), and low cost ($ 15.2). The three conclusions are as follows. CCCM can be used as a criterion for judging the unbalanced muscle region of the patient's neck and can accurately locate unbalanced muscles. The RMS cloud map provides the time consumption, swallowing times, and unbalanced areas. When the lesion location involves the left and right hemispheres simultaneously, it can be used as an evidence of relatively severely unbalanced areas. The classification accuracy of SVM in terms of sex, age, and lesion location was as high as 100%.Significance.The HD-sEMG sensor in this study and the adaptation algorithm will contribute to the establishment of a larger-scale database in the future to establish more detailed and accurate quantitative standards, which will be the basis for developing more optimized screening mechanisms and rehabilitation assessment methods.

Quantification of the Swallowing Mechanism Through Muscle Synergy Analysis

Decreased swallowing function increases the risk of choking and aspiration pneumonia. Videofluoroscopy and computed tomography allow for detailed observation of the swallowing movements but have radiation risks. Therefore, we developed a method using surface electromyography (sEMG) to noninvasively assess swallowing function without radiation exposure. A 44-channel flexible sEMG sensor was used to measure the sEMG signals of the hyoid muscles during swallowing in 14 healthy young adult and 14 elderly subjects. Muscle synergy analysis was performed to extract the muscle synergies from the sEMG signals, and the three synergies were extracted from the hyoid muscle activities during the swallowing experiments. The experimental results showed that the three synergies represent the oral, early pharyngeal, and late pharyngeal swallowing phases and that swallowing strength is tuned by the strength of the muscle activities, whereas swallowing volume is controlled by adjusting muscle activation timing. In addition, the timing of the swallowing reflex is slower in elderly individuals. The results confirm that the proposed approach successfully quantifies swallowing function from sEMG signals, mapping the signals to the swallowing phases.

Using Muscle Synergy to Evaluate the Neck Muscular Activities during Normal Swallowing

Swallowing is an extremely complex motion controlled by multiple muscles on the front neck region. Normal swallowing is dependent on orderly activation and co-coordination of the associated neck muscles, known as muscle synergy. However, evidence for muscle synergy during normal swallowing is rarely investigated. In this study, we studied the muscle synergy associated with swallowing saliva based on high-density (HD) surface electromyography (sEMG) signals acquired from four healthy subjects. The non-negative matrix factorization algorithm was applied to reconstruct the muscle activation patterns, and the values of variance accounted for (VAF) coefficients were computed to determine the number of muscle synergies. The results showed that the VAF values raised with the increase in the number of synergies on both the left and right sides of the neck. And the variation tendency of the VAF values was almost similar between the left and right area with a significant correlation ($\text{r}=0.9902 \pm 0.0046$, $\mathrm {p}<0.05)$. Furthermore, it was observed that an average of 5 muscle synergies was the minimum number required to sufficiently reconstruct the spatial characteristics of the synergism between both sides of the neck. These results suggest that the muscle synergy approach could serve as a promising candidate to evaluate the muscular co-contractions during swallowing, and it might be a useful method for dysphagia monitoring and diagnoses.

Evaluation of normal swallowing functions by using dynamic high-density surface electromyography maps

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

A pilot study on the evaluation of normal phonating function based on high-density sEMG topographic maps

Phonation is controlled by complex synergism of muscles over the front neck region. Proper evaluation of the muscular activities in this region would not only help to estimate phonation function, but may also provide characteristics to diagnose dysphonia. While surface electromyography (sEMG) technique has been used to study the physiological aspects of phonation in previous studies, it remains unclear if the phonating function could be dynamically characterized by the sEMG signals of the neck muscles associated with phonation. In this study, almost 80 channels of high-density (HD) sEMG signals were acquired from four healthy subjects when the vowel /a/ was phonated across different pitches by them. The root mean square (RMS) of the HD sEMG signals was computed within a series of segmented analysis windows and used to construct dynamic sEMG topographic maps. And the RMS maps represented the energy distribution of the front neck muscles, which would provide both the temporal and spatial information in accordance with the physiological and biomechanical principles of phonation. Our pilot results from the sEMG topographic maps across different pitch levels showed that the muscular activities consistently increased with the enhancement of the pitch levels. This pilot study suggests that HD sEMG might be a potential tool to visualize the distribution of the muscular activities and observe the coordination of muscular contractions during phonation. Also, it might pave way for proper screening and diagnosis of dysphonia as well as its associated pathologies.