Semi-automated Detection of the Timing of Respiratory Muscle Activity: Validation and First Application

Abstract

Background: Respiratory muscle electromyography (EMG) can identify whether a muscle is activated, its activation amplitude, and timing. Most studies have focused on the activation amplitude, while differences in timing and duration of activity have been less investigated. Detection of the timing of respiratory muscle activity is typically based on the visual inspection of the EMG signal. This method is time-consuming and prone to subjective interpretation. Aims: Our main objective was to develop and validate a method to assess the respective timing of different respiratory muscle activity in an objective and semi-automated manner. Method: Seven healthy adults performed an inspiratory threshold loading (ITL) test at 50% of their maximum inspiratory pressure until task failure. Surface EMG recordings of the costal diaphragm/intercostals, scalene, parasternal intercostals, and sternocleidomastoid were obtained during ITL. We developed a semi-automated algorithm to detect the onset (EMG, onset) and offset (EMG, offset) of each muscle's EMG activity breath-by-breath with millisecond accuracy and compared its performance with manual evaluations from two independent assessors. For each muscle, the Intraclass Coefficient correlation (ICC) of the EMG, onset detection was determined between the two assessors and between the algorithm and each assessor. Additionally, we explored muscle differences in the EMG, onset, and EMG, offset timing, and duration of activity throughout the ITL. Results: More than 2000 EMG, onset s were analyzed for algorithm validation. ICCs ranged from 0.75-0.90 between assessor 1 and 2, 0.68-0.96 between assessor 1 and the algorithm, and 0.75-0.91 between assessor 2 and the algorithm (p < 0.01 for all). The lowest ICC was shown for the diaphragm/intercostal and the highest for the parasternal intercostal (0.68 and 0.96, respectively). During ITL, diaphragm/intercostal EMG, onset occurred later during the inspiratory cycle and its activity duration was shorter than the scalene, parasternal intercostal, and sternocleidomastoid (p < 0.01). EMG, offset occurred synchronously across all muscles (p ≥ 0.98). EMG, onset, and EMG, offset timing, and activity duration was consistent throughout the ITL for all muscles (p > 0.63). Conclusion: We developed an algorithm to detect EMG, onset of several respiratory muscles with millisecond accuracy that is time-efficient and validated against manual measures. Compared to the inherent bias of manual measures, the algorithm enhances objectivity and provides a strong standard for determining the respiratory muscle EMG, onset.

Keywords: electromyography; neck muscles; respiratory muscles; surface electromyography; ventilatory muscles.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2022 Rodrigues, Janssens, Langer, Matsumura, Rozenberg, Brochard and Reid.

Figures

Figure 1

Representative breath showing the detection of the onset and offset of the electromyography activity for the diaphragm/intercostal, parasternal intercostal, sternocleidomastoid and scalene. RMS, root mean square of the electromyography; SCM, sternocleidomastoid. Red lines indicate when the algorithm detected the onset of the electromyography activity for each muscle. Dashed red lines indicate when the algorithm detected the offset of the electromyography activity for each muscle. Green line indicates when the algorithm detected the onset of the inspiratory flow. Dashed green line indicate when the algorithm detected the offset of the inspiratory flow (Sinderby et al., 2013; Estrada et al., 2019).

Figure 2

Example of the detection of the onset of the EMG activity by the manual method. The figure shows the software layout viewed by the assessors when performing the manual analysis. The red arrow indicates where the assessor judged the onset of the diaphragm/intercostals EMG onset occurred. The black arrow indicates the time in seconds (provided by the software) when the assessor indicated the diaphragm/intercostal EMG onset occurred. The assessor would type the seconds indicated by the software in a Excel file with a millisecond accuracy. This processed was repeated breath-by-breath for each muscle. EMG RMS, root mean square of the EMG signal; DIA/IC, diaphragm/intercostal; PI, parasternal intercostal; SCM, sternocleidomastoid.

Figure 3

Example of one breath where the diaphragm/intercostal EMG onset was judged not clear by the assessor (indicated by the red arrow) and thus typed as “NA” in the Excel file. The figure shows the software layout viewed by the assessor when performing the manual analysis. The black line indicates where the algorithm identified the beginning of the EMG onset. EMG RMS: root mean square of the EMG signal; DIA/IC, diaphragm/intercostal; PI, parasternal intercostal; SCM, sternocleidomastoid.

Figure 4

Bland-Altman plots and ICC’s values for the breath-by-breath detection of dP of EMG, onset by assessor 1 and 2 for the diaphragm/intercostal (A), parasternal intercostal (B), scalene (C) and, sternocleidomastoid (D). AVG: average bias between the results from both assessors. UL and LL: 95% confidence interval of the difference between the results from both assessors. n: number of EMG, onset analyzed. dP: phased difference between the onset of the electrical activity of the muscle and the start of the inspiration calculated (see text for further details).

Figure 5

Bland and Altman plots and ICC’s values for the breath-by-breath detection of dP of EMG, onset by assessor 1, and the algorithm for the diaphragm/intercostal (A), parasternal intercostal (B), scalene (C), and sternocleidomastoid (D). AVG: average bias between the results from both assessors. UL and LL: 95% confidence interval of the difference between the results from both assessors. n: number of EMG, onset analyzed. dP: phased difference between the onset of the electrical activity of the muscle and the start of the inspiration calculated (see text for further details).

Figure 6

Changes in ventilatory variables during the inspiratory threshold loading. Ttot, total time of the respiratory cycle (A), Ti, inspiratory time (B), peak flow, peak inspiratory flow (C), vt, tidal volume (D), and Pm, mouth pressure (E). Data are depicted as mean ± SE. *p < 0.05 vs. task failure; §p < 0.05 vs. minutes 14 and 16; ¥p < 0.05 vs. minute 18.

Figure 7

Timing of the diaphragm/intercostal, parasternal intercostal, scalene, and sternocleidomastoid activity during the inspiratory threshold loading. Upper panels are expressed as a percentage of inspiratory time onset based on the flow signal (%Ti) whereas lower panels are expressed in seconds from inspiratory flow onset (A) and (D) – EMG, onset; (B) and (E) – EMG, offset; (C) and (F) – Duration of activation. *p < 0.01 for the diaphragm/intercostal vs. parasternal intercostal, scalene and sternocleidomastoid. ¥p < 0.03 for the diaphragm/intercostals vs. parasternal intercostal and scalene.

Figure 8

Timing of the diaphragm/intercostal, parasternal intercostal, scalene, and sternocleidomastoid activity during the inspiratory threshold loading. Upper panels are expressed as a percentage of inspiratory time onset based on the pressure signal (%Ti by pressure) whereas lower panels are expressed in seconds from inspiratory onset based on the pressure signal (A) and (D) – EMG, onset; (B) and (E) – EMG, offset; (C) and (F) – Duration of activation. *p < 0.01 for the diaphragm/intercostal vs. parasternal intercostal, scalene and sternocleidomastoid.

Figure 9

Density plots and boxplots for onset of the electromyography activity in percentage of the inspiratory time of the diaphragm/intercostal (A), parasternal intercostal (B), scalene (C), and sternocleidomastoid (D).