Swallow Detection with Acoustics and Accelerometric-Based Wearable Technology: A Scoping Review

• Published in: International journal of environmental research and public health Vol. 20; no. 1; p. 170
• Main Authors: So, Bryan Pak-Hei, Chan, Tim Tin-Chun, Liu, Liangchao, Yip, Calvin Chi-Kong, Lim, Hyo-Jung, Lam, Wing-Kai, Wong, Duo Wai-Chi, Cheung, Daphne Sze Ki, Cheung, James Chung-Wai
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 22-12-2022; MDPI
• Subjects: Accelerometers; Accuracy; Acoustics; Alzheimer's disease; Auscultation; Deglutition; Deglutition Disorders - diagnosis; Deglutition Disorders - etiology; Dehydration; Dysphagia; Endoscopy; Food; Heterogeneity; Human subjects; Humans; Keywords; Malnutrition; Measurement techniques; Older people; Parkinson's disease; Review; Reviews; Saliva; Sensors; Sound; Standardization; Stroke; Swallowing; Wearable computers; Wearable technology; Yawning behavior; dysphagia; mHealth; eating disorder; deglutition disorder; otorhinolaryngology
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph20010170

Swallowing disorders, especially dysphagia, might lead to malnutrition and dehydration and could potentially lead to fatal aspiration. Benchmark swallowing assessments, such as videofluoroscopy or endoscopy, are expensive and invasive. Wearable technologies using acoustics and accelerometric sensors could offer opportunities for accessible and home-based long-term assessment. Identifying valid swallow events is the first step before enabling the technology for clinical applications. The objective of this review is to summarize the evidence of using acoustics-based and accelerometric-based wearable technology for swallow detection, in addition to their configurations, modeling, and assessment protocols. Two authors independently searched electronic databases, including PubMed, Web of Science, and CINAHL. Eleven (n = 11) articles were eligible for review. In addition to swallowing events, non-swallowing events were also recognized by dry (saliva) swallowing, reading, yawning, etc., while some attempted to classify the types of swallowed foods. Only about half of the studies reported that the device attained an accuracy level of >90%, while a few studies reported poor performance with an accuracy of <60%. The reviewed articles were at high risk of bias because of the small sample size and imbalanced class size problem. There was high heterogeneity in assessment protocol that calls for standardization for swallowing, dry-swallowing and non-swallowing tasks. There is a need to improve the current wearable technology and the credibility of relevant research for accurate swallowing detection before translating into clinical screening for dysphagia and other swallowing disorders.