ArticleSensors (Basel, Switzerland)2024
Electromyography- and Bioimpedance-Based Detection of Swallow Onset for the Control of Dysphagia Treatment.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Human-AI collaboration for dysphagia rehabilitation from effectiveness to implementation complexity: a systematic review.NPJ digital medicine · 2026Article
- A Machine Learning Pipeline for Automated Bolus Segmentation and Area Measurement in Swallowing Videofluoroscopy Images of an Infant Pig Model.Dysphagia · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.