Crosby, T. | Search bioRxiv

bioRxiv2023

Perilaryngeal Functional Muscle Network in Patients with Vocal Hyperfunction - A Case Study

Patients with both phonotraumatic and non-phonotraumatic dysphonia commonly present with vocal hyperfunction, defined as excessive perilaryngeal muscle activity and characterized by muscular pain and strain in the neck, increased vocal effort, and vocal fatigue. The inability to reliably measure vocal hyperfunction is a barrier to adequate evaluation and treatment of hyperfunctional voice disorders. We have recently demonstrated that the perilaryngeal functional muscle network can be a novel sensitive neurophysiological window to vocal performance in vocally healthy subjects. In this paper, for the first time, we evaluate the performance and symmetry of functional perilaryngeal muscle networks in three patients with voice disorders. Surface electromyography signals were recorded from twelve sensors (six on each side of the neck) using the wireless Trigno sEMG system (Delsys Inc., Natick, MA). Patient 1 was diagnosed with primary muscle tension dysphonia, Patient 2 was diagnosed with unilateral vocal fold paresis, and Patient 3 was diagnosed with age-related glottal insufficiency. This paper reports altered functional connectivity and asymmetric muscle network scan behavior in all three patients when compared with a cohort of eight healthy subjects. Our approach quantifies synergistic network activity to interrogate coordination of perilaryngeal and surrounding muscles during voicing and potential discoordination of the muscle network for dysphonic conditions. Asymmetry in muscle networks is proposed here as a biomarker for monitoring vocal hyperfunction.

bioengineering↗

bioRxiv2021

Characterization of Cervical-Cranial Muscle Network in Correlation with Vocal Features

Objective evaluation of physiological responses using non-invasive methods has attracted great interest regarding the assessment of vocal performance and disorders. This paper, for the first time, demonstrates that the topographical features of the cervical-cranial intermuscular coherence network generated using surface electromyography (sEMG) have a strong potential for detecting subtle changes in vocal performance. For this purpose, in this paper, 12 sEMG signals were collected from six cervical and cranial muscles bilaterally. Data were collected from four subjects without a history of a voice disorder performing a series of vocal tasks. The vocal tasks were varied phonation (an /a/ sustained for the maximal duration with combinations of two levels of loudness and two levels of pitch), a pitch glide from low to high, singing a familiar song, spontaneous speech, and reading with different loudness levels. The varied phonation tasks showed the median degree, and weighted clustering coefficient of the coherence-based intermuscular network ascends monotonically, with a high effect size (|rrb| = 0.52). The set of tasks, including pitch glide, singing, and speech, was significantly distinguishable using the network features as both degree and weighted clustering coefficient had a very high effect size (|rrb| > 0.83) across these tasks. Also, pitch glide has the highest degree and weighted clustering coefficient among all tasks (degree > 0.6, weighted clustering coefficient > 0.6). Spectrotemporal features performed far less effective than the proposed functional muscle network metrics to differentiate the vocal tasks. The highest effect size for spectrotemporal features was only |rrb| = 0.19. In this paper, for the first time, the power of a cervical-cranial muscle network has been demonstrated as a neurophysiological window to vocal performance. The results also shed light on the tasks with the highest network involvement, which may be potentially used in monitoring vocal disorders and tracking rehabilitation progress.

neuroscience↗