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March 2, 2026Open Access

Dysphagia detection using near-ear sensors and machine learning

Aditya Mehra Andreas Radeloff Tanja Schultz

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Key Points

The study aims to explore the detection of swallowing disorders using advanced machine learning techniques with near-ear sensors.
Utilized near-ear sensors to monitor swallowing activities.
Applied machine learning algorithms to analyze sensor data.
Compared effectiveness with traditional diagnostic methods.
Found the potential of near-ear sensors to accurately detect dysphagia.
Reported that machine learning approaches improve diagnostic accuracy.
Indicated a significant reduction in reliance on traditional diagnostics.

Implication

This research demonstrates dysphagia detection in individuals with swallowing disorders, suggesting new diagnostic approaches.

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Cite This Study

Mehra et al. (2026) studied this question.

synapsesocial.com/papers/69a7ccc3d48f933b5eed8938 https://doi.org/10.3205/26dga116

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