发声
肌电图
休息(音乐)
生物医学工程
医学
听力学
物理医学与康复
心脏病学
作者
David J. Bracken,Gladys Ornelas,Todd P. Coleman,Philip A. Weissbrod
出处
期刊:Laryngoscope
[Wiley]
日期:2019-01-21
卷期号:129 (10): 2347-2353
被引量:19
摘要
Objectives/Hypothesis Laryngeal muscle activation is a complex and dynamic process. Current evaluation methods include needle and surface electromyography (sEMG). Limitations of needle electromyography include patient discomfort, interpretive complexity, and limited duration of recording. sEMG demonstrates interpretive challenges given loss of spatial selectivity. Application of high‐density sEMG (HD sEMG) arrays were evaluated for potential to compensate for spatial selectivity loss while retaining benefits of noninvasive monitoring. Study Design Basic science. Methods Ten adults performed phonatory tasks while a 20‐channel array recorded spatiotemporal data of the anterior neck. Data were processed to provide average spectral power of each electrode. Comparison was made between rest, low‐, and high‐pitch phonation. Two‐dimensional (2D) spectral energy maps were created to evaluate use in gross identification of muscle location. Results Three phonatory tasks yielded spectral power measures across the HD sEMG array. Each electrode within the array demonstrated unique power values across all subjects ( P < .001). Comparison of each electrode to itself across phonatory tasks yielded differences in all subjects during rest versus low versus high, rest versus low, and rest versus high and in 9/10 subjects ( P < .001) for low versus high phonation. Symmetry of HD sEMG signal was noted. Review of 2D coronal energy maps allowed for gross identification of cricothyroid muscle amidst anterior strap musculature. Conclusions HD sEMG can be used to identify differences in anterior neck muscle activity between rest, low‐, and high‐pitch phonation. HD sEMG of the anterior neck holds potential to enhance diagnostic and therapeutic monitoring for pathologies of laryngeal function. Level of Evidence NA Laryngoscope , 129:2347–2353, 2019
科研通智能强力驱动
Strongly Powered by AbleSci AI