Electromyography- and Bioimpedance-Based Detection of Swallow Onset for the Control of Dysphagia Treatment

Abstract

Several studies support the benefits of biofeedback and Functional Electrical Stimulation (FES) in dysphagia therapy. Most commonly, adhesive electrodes are placed on the submental region of the neck to conduct Electromyography (EMG) measurements for controlling gamified biofeedback and functional electrical stimulation. Due to the diverse origin of EMG activity at the neck, it can be assumed that EMG measurements alone do not accurately reflect the onset of the pharyngeal swallowing phase (onset of swallowing). To date, no study has addressed the timing and detection performance of swallow onsets on a comprehensive database including dysphagia patients. This study includes EMG and BioImpedance (BI) measurements of 41 dysphagia patients to compare the timing and performance in the Detection of Swallow Onsets (DoSO) using EMG alone versus combined BI and EMG measurements. The latter approach employs a BI-based data segmentation of potential swallow onsets and a machine-learning-based classifier to distinguish swallow onsets from non-swallow events. Swallow onsets labeled by an expert serve as a reference. In addition to the F1 score, the mean and standard deviation of the detection delay regarding reference events have been determined. The EMG-based DoSO achieved an F1 score of 0.289 with a detection delay of 0.018 s ± 0.203 s. In comparison, the BI/EMG-based DoSO achieved an F1 score of 0.546 with a detection delay of 0.033 s ± 0.1 s. Therefore, the BI/EMG-based DoSO has better timing and detection performance compared to the EMG-based DoSO and potentially improves biofeedback and FES in dysphagia therapy.

Keywords: biofeedback; dysphagia; functional electrical stimulation; machine learning; swallow onset detection.

Figure 1

Electrode placement of the four-electrode setup with an additional reference electrode. The current electrodes (red) placed on sternocleidomastoideus close to the ear introduce a sinusoidal current of 50 kHz. The measurement electrodes (green) placed on each side of the larynx measure the voltage over the enclosed tissue. The reference electrode (gray) is used to suppress common-mode disturbances.

Figure 2

BI and EMG measurement of a saliva swallow. The swallow preparation phase (green background) shows some variation in the BI data caused by tongue movements from collecting saliva. The oral swallowing phase (red background) displays a small peak in the BI data, which continuously transitions to the BI swallow valley caused by the larynx elevation during the pharyngeal swallowing phase (blue background). The vertical line defines the time of the swallow onset marked by an expert, shortly after the start of the pharyngeal swallowing phase.

Figure 3

A visualization of the cleaned EMG (EMG), the envelope EMG (eEMG), and the BI of a single swallow for EMG-based swallow onset detection. The black section of the eEMG trace highlights the w samples of eEMG that exceed ${\theta }^{\mathrm{EMG}}$. The red vertical line denotes the manually marked swallow onset, while the black vertical line denotes the time of the detected swallow onset. The light red area marks the period with disabled onset detection that starts at a detected onset.

Figure 4

Left: Visualization of the BI data vectors of swallow onsets (12) and non-swallow events (34) in a healthy subject, shifted to zero at the time zero of potential swallow onsets. Right: Visualization of the tEMG data vectors of swallow onsets and non-swallows shifted to zero at the time zero of potential swallow onsets.

Figure 5

A visualization of EMG data vectors of swallow onsets and non-swallow events in a healthy subject preceding the potential swallow onsets at time zero. The left subplot shows the EMG vectors of 12 swallow onsets (blue), and the right subplot shows the EMG vectors of 34 non-swallow events (green).

Figure 6

Illustration of the overlap $\eta (A,B)$ between two Log-normal probability-density functions $f_B\left(x\right)\sim LogNormal(0,0.6)$ and $f_A\left(x\right)\sim LogNormal(0,0.9)$.

Figure 7

Visualization of sensitivity (green dots), precision (red triangles), and ${\mathrm{F}}_1$ score (blue dots) of BI/EMG-based detection of swallow onsets for individual dysphagia patients. A black line connects the sensitivity and the precision of each patient to visualize the span width between the scores.