Wearable electronic devices for monitoring mastication and swallowing in adults: A scoping review

ABSTRACT

Purpose:  to identify and describe wearable electronic devices used for monitoring mastication and swallowing in adults.

Methods:  two independent researchers searched the PubMed and MEDLINE engines via Ovid®. Primary studies were selected using Rayyan®, with analysis of titles, abstracts, and full texts. The information extracted followed a study protocol.

Literature Review:  243 studies, of which 25 were selected for analysis after applying the inclusion and exclusion criteria, were identified. Data about the participants, devices, sensors, location, and analyses performed, were extracted.

Conclusions:  wearable devices for monitoring mastication have been used primarily in healthy adults, assessing the number of bites, cycles per bite and per meal, and mastication speed, rate, and time. For swallowing, these devices have been applied to both healthy adults and individuals with dysphagia, focusing on detecting swallowing activities and differentiating them from other muscle activities. However, there is a gap in the development of devices that fully integrate the phases of ingestion, processing, and swallowing, with greater clinical support to improve monitoring and application in different health conditions.

Keywords:
Feeding Behavior; Mastication; Deglutition; Wearable Electronic Devices

RESUMO

Objetivo:  identificar e descrever dispositivos eletrônicos vestíveis usados para o monitoramento da mastigação e deglutição em adultos.

Métodos:  a pesquisa foi realizada nos motores PubMed e MedLine via Ovid®, por dois pesquisadores independentes. Foram selecionados estudos primários utilizando o Rayyan®, com análise de títulos, resumos e textos completos. As informações extraídas seguiram um protocolo de estudo.

Revisão da Literatura:  foram identificados 243 estudos, dos quais após a aplicação dos critérios de inclusão e exclusão, 25 foram selecionados para análise. Os dados extraídos incluíram informações sobre participantes, dispositivos, sensores, localização e análises realizadas.

Conclusões:  os dispositivos vestíveis para monitoramento da mastigação foram utilizados principalmente em adultos saudáveis, nos quais se avaliou o número de mordidas, ciclos por mordida e por refeição, além da velocidade, taxa e tempo de mastigação. Para a deglutição, os dispositivos foram aplicados tanto em adultos saudáveis quanto em indivíduos com disfagia, com foco na detecção de atividades de deglutição e na diferenciação de outras atividades musculares. Contudo, há uma lacuna no desenvolvimento de dispositivos que integrem de forma completa as fases de ingestão, processamento e deglutição, com maior suporte clínico para melhorar o monitoramento e a aplicação em diferentes condições de saúde.

Descritores:
Comportamento Alimentar; Mastigação; Deglutição; Dispositivos Eletrônicos Vestíveis

INTRODUCTION

Wearable electronic devices are worn directly on the body, either as implants or accessories¹. The popularization of the Internet and the increased use of mobile devices have generated a new branch of electronic health, widely known as Mobile Health (mHealth), which can be understood as "the provision of medical and/or public health services with technological support of mobile devices such as mobile phones, sensors, and other wearable equipment"².

In this regard, Cisco AppDynamics presented in 2022 the results of a study that explored consumer attitudes and behaviors towards wearable technology. It revealed that 85% of people worldwide believe that wearable technology now has the potential to transform both healthcare and public health services positively. Moreover, 37% of people say they are already using at least one wearable technology device, and up to 73% plan to increase their use of wearable technologies and associated applications in the next 12 months³.

Studies highlight that wearable devices can monitor a wide range of eating and communication signals continuously, comprehensively, and simultaneously. This generates a large volume of data with the potential to enrich the knowledge base used in decision-making, enabling the construction of predictive health and behavior models⁴. Patients with difficulties in transferring adaptive or compensatory behavior patterns learned in the clinic can especially benefit from these resources. Therefore, wearable technologies are a significant advance for health services.

Feeding involves several body systems, with emphasis on the stomatognathic, digestive, and respiratory systems. Mastication and swallowing are crucial processes for the preparation and transport of the bolus from the mouth to the stomach^5,6. One of the challenges faced by health professionals is to obtain information about feeding under usual and real conditions, as well as to monitor the necessary adaptations to ensure that feeding occurs safely and efficiently. Dietary events, including the process from ingestion to swallowing and digestion, play a fundamental role in eating behavior assessment. Monitoring these events can provide a more detailed view of the patient's health status and help plan more personalized and effective clinical interventions⁷.

However, currently available wearable electronic devices for monitoring mastication and swallowing are scarce and mostly in the development phase⁸. This leads to unstandardized technical characteristics, monitoring methods, and variables measured by these devices, posing a significant obstacle to their use in clinical settings. Given this gap, it is essential to investigate which devices have been developed and are currently used, as well as their technical characteristics, the variables they monitor, and their potential for clinical application. Furthermore, the detailed characterization of these devices will contribute to the development of new, more efficient wearable technologies adapted to clinical needs⁷.

A scoping literature review was proposed to increase knowledge about wearable electronic devices used to monitor mastication and swallowing in adults. These relatively recent reviews seek to answer broad research questions and identify, select, and update the available evidence in specific areas⁹. Thus, this scoping review aimed to identify and describe the characteristics of wearable electronic devices for monitoring mastication and swallowing in adults.

METHODS

Protocol

This scoping review protocol followed the general guidelines proposed by the Joanna Briggs Institute (JBI) for scoping reviews¹⁰, and its results were organized and presented according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines¹¹, which also served as a basis for writing this article.

Studies were included based on the Population, Concept, and Context (PCC) strategy, as follows: a) Population: adults aged 19 years or older; b) Concept: wearable electronic devices; c) Context: monitoring mastication and swallowing.

Based on these criteria, the following research question was established: “What are the wearable electronic devices designed to monitor mastication and swallowing in adults and what are their characteristics?”.

Eligibility criteria

This review included studies that described the use of wearable electronic devices for monitoring mastication and swallowing in adults aged 19 years and older, regardless of disorders in these functions. It considered quantitative experimental, quasi-experimental, observational, descriptive, exploratory, correlational, and case analysis studies, published in Spanish, English, and Portuguese, with no restrictions on the date of publication.

The exclusion criteria were studies with children and adolescents under 18 years and 11 months old, qualitative studies, secondary reviews, conference presentations, authors' opinions, and publications not presenting empirical data relevant to monitoring mastication and swallowing electronically.

Sources of information

The searches were conducted in March 2024 on PubMed-MEDLINE engines using Ovid®.

Search strategy

The search used the terms listed in Table 1, as suggested by Ovid® for controlled language and natural language.

Table 1
Search strategy

#	Ovid results (PubMed-MEDLINE)
1	Adult/ or adult.mp. or Young Adult/
2	middle age.mp. or Middle Aged/
3	1 or 2
4	Feeding Behavior/ or Mastication/ or chew.mp.
5	Deglutition Disorders/ or swallow.mp. or Swallows/ or Deglutition/
6	4 or 5
7	Biosensing Techniques/ or Wearable Electronic Devices.mp. or Monitoring, Physiologic/ or Monitoring, Ambulatory/ or Wearable Electronic Devices/ or Electronics, Medical/ or "Electrical Equipment and Supplies"/
8	Technology.mp. or Biomedical Technology/ or Technology Assessment, Biomedical/ or Food Technology/ or Eye-Tracking Technology/ or Remote Sensing Technology/ or Technology, Dental/ or "National Center for Health Care Technology, U.S."/ or Technology, Radiologic/ or Technology/
9	7 or 8
10	3 and 6 and 9

Study selection

Two independent researchers selected studies by using Rayyan® software for sequential analysis, starting with titles and abstracts, and then by reading the full text of all potentially relevant studies. Data were extracted using a form developed by the authors, based on consensus among the researchers regarding the included studies.

Data analysis

The extracted data were analyzed in two stages. The first one approached general aspects of the included studies, such as their author(s), year of publication, country of study, and the population studied, including the participants’ age range, sex, and health status. This information provided an overview of the distribution of experimental and control groups and the demographic and medical characteristics of the participants.

The second stage analyzed the characteristics of the wearable electronic devices used in the studies, including the name of the device, the types of sensors used, their location on the body, and the variables monitored.

LITERATURE REVIEW

Selection of sources of evidence

After eliminating duplicates, 243 records were identified. From reading the titles and abstracts, 56 studies were selected, and after reading the full text, 25 studies were chosen. All these were selected because they met the criteria for subsequent analysis (Figure 1).

Figure 1
Source selection flowchart

Characteristics of sources of evidence

The characteristics of the included studies and participants are presented in Table 2.

Table 2
Characteristics of studies and participants

First author	Year	Country	Experimental Group				Control Group
			N	N of W	N of M	Age (years)	Medical Condition	N	Age (years)
Miyamoto12	1996	Japan	30	10	20	30.9 ± 5.8	Healthy	-	-
Pehlivan13	1996	Turkey	21	4	17	62.0	Parkinson’s disease	21	39.4
Tanaka14	2012	Japan	15	7	8	28.6	Healthy	-	-
Päßler15	2013	Germany	51	(?)	(?)	34.8	Healthy	-	-
Fontana16	2014	Argentina; USA	12	6	6	26.7 ± 3.7	Healthy	-	-
Shieh17	2015	Taiwan	19	9	10	24 ± 3; 37 ± 5; 55 ± 4	Healthy	-	-
Wang18	2015	Taiwan	38	10	28	52.0 ± 6.5	Unilateral stroke	59	54.9 ± 8.4
Blechert19	2017	Austria	14	6	8	21.7 ± 2.13	Healthy	-	-
Lee20	2017	USA	4	2	2	21-35	Healthy	-	-
Farooq21	2017	USA	18	3	15	27.7 ± 2.8	Healthy	-	-
Farooq22	2017	USA	10	2	8	29.03 ± 12.2	Healthy	-	-
Papapanagiotou23	2017	Greece; Switzerland; The Netherlands	22	(?)	(?)	22.9	Healthy	-	-
Chung24	2017	Korea	10	(?)	(?)	(?)	(?)	-	-
Taniguchi25	2018	Japan	6	(?)	(?)	28.2	Healthy	-	-
Inoue26	2018	Japan	52	(?)	(?)	75.5 ± 20.5	Smoker	140	54.5 ± 32.5
Ramirez27	2018	USA	14	2	12	43-83	Head and neck cancer	1	24
Zhang28	2018	Germany	10	4	6	25.1 ± 2.1	Healthy	-	-
Shieh29	2019	Taiwan	19	(?)	(?)	37.68 ± 7.13	Smoker	26	38.12 ± 6.45
Kim30	2019	USA; India	1	1	0	70	Parkinson’s disease and dysphagia	1	23
Zhang31	2020	Germany	10	4	6	25.1 ± 2.1	Healthy	-	-
Kantarcigil32	2020	USA	40	16	24	67.5 ± 7.85	Healthy	-	-
Kang33	2022	USA	1	0	1	(?)	Parkinson’s disease and dysphagia	2	29 and 32
Uehara34	2022	Japan	99	49	50	36.4 ± 11.7	Healthy	-	-
Yoshimura35	2022	Japan	365	162	203	36.6 ± 12.1	Healthy	-	-
Maeda36	2023	Japan	17	1	16	30-60	Healthy	-	-

• Captions: N = number; - = not applicable; (?) = not informed; W = women; M = men.

Results from individual sources of evidence

The characteristics of the portable devices are presented in Table 3.

Table 3
Characteristics of wearable electronic devices

Author (year)	Name of the device	Sensors/Location	Analyses
Miyamoto et al. (1996)12	24-hour EMG system.	Bipolar surface electrode on the masseter muscle.	Total number and duration of bursts exceeding one-quarter of the maximum discharge value during maximum contraction, over 24 hours.
Pehlivan et al. (1996)13	Digital Phagometer.	A piezoelectric sensor between the cricoid cartilage and the thyroid.	Number of spontaneous swallows.
Tanaka et al. (2012)14	Swallowing frequency meter.	Contact microphone on the lateral edge of the trachea, immediately below the cricoid cartilage.	Number of swallowing events.
Päßler et al. (2013)15	Microphone sensor system.	Electret microphones in and above the external auditory canal.	Number of mastication events.
Fontana et al. (2014)16	Automatic ingestion monitor.	Jaw movement sensor under the earlobe, hand gesture sensor on the dominant hand, and accelerometer in a module on the neck.	Food intake in daily life, capturing data on mastication, hand gestures, and body movements.
Shieh et al. (2015)17	-	Force sensor on thyroid cartilage, surface electrode on submental muscle, and nasal cannula-type flow sensor.	Swallowing onset latency, total excursion time, time the pharynx takes to push the bolus into the esophagus; onset latency and duration of EMG signals; and duration of swallowing apnea.
Wang et al. (2015)18	-	Surface electrodes in the submental region, a piezoelectric sensor in the thyroid cartilage, cannula-type nasal flow sensor.	Onset latency, amplitude of the thyroid cartilage excursion signal, total duration of the thyroid cartilage excursion, jitter, and duration of swallowing apnea.
Blechert et al. (2017)19	EMG-based eating detector	Surface electrodes on the bony structure behind one ear.	Food intake in daily life, through mastication.
Lee et al. (2017)20	Skin-friendly electronic system	"Skin-like" surface electrode on the submental muscles.	Swallowing activities analyzed with a data classification algorithm.
Farooq et al. (2017, 2017)21,22	Smart Glasses	Piezoelectric strain sensor in the temporal muscle.	Cumulative number of chews, meal duration, actual eating duration.
Papapanagiotou et al. (2017)23	-	In-ear microphone with photoplethysmography sensor.	Detection of feeding events through mastication.
Chung et al. (2017)24	GlasSense	Load cells in glasses.	Temporal muscle activity during feeding behavior and other related activities.
Taniguchi et al. (2018)25	Earable RCC	Optical distance sensor in the auditory canal.	Mastication count record.
Inoue et al. (2018)26	-	Nasal cannula flow sensor and custom piezoelectric sensor on thyroid cartilage.	Expiratory flow, laryngeal movement, and swallowing sounds analyzed with a machine learning method.
Ramirez et al. (2018)27	Strain Sensor Device	The strain sensor device next to surface electrodes in the submental region.	Classification of sensor voltage signals during swallowing.
Zhang; Amft (2018, 2020)28,29	Automatic ingestion monitor - Smart Eyeglasses	Surface electrodes on both temporal muscles (2 channels).	Mastication cycle and rate.
Shieh et al. (2019)30	Device developed by Shieh et al. (2015).	Sensors developed by Shieh et al. (2015).	Same analysis as Shieh et al. (2015), besides differentiating swallowing patterns and comparing with VFSS.
Kim et al. (2019)31	Sensor Patch System.	Surface electrodes in the submental area, voltage sensor in the laryngeal prominence.	Onset, duration, and end of a swallowing event, and amplitude of EMG signals.
Kantarcigil et al. (2020)32	Sensor Patch System.	Surface electrodes in the submental area, voltage sensor in the laryngeal prominence.	Factors related to the EMG signal during swallowing: signal-to-noise ratio, basal amplitude, normalized mean amplitude, and burst duration.
Kang et al. (2022)33	-	Acoustic mechanical sensor in the suprasternal notch, a nasal cannula, and respiratory inductance plethysmography bands.	Simultaneous measurement of swallowing and breathing cycles.
Uehara et al. (2022)34	Bitescan	An infrared distance sensor and accelerometer on the back of the ear.	Number of chews and bites, number of chews per bite, and mastication speed.
Yoshimura et al. (2022)35	Bitescan	Infrared distance sensor on the back of the right ear.	Number of mastication cycles, mastication rate, and mastication time.
Maeda et al. (2023)36	Wearable Swallowing Assessment Device	Hetero-core fiber optic pressure sensor in laryngeal prominence.	Laryngeal movement during swallowing, considering time.

• Captions: W = women; M = men; EMG = electromyography; - = no information; VFSS = videofluoroscopic swallowing study.

Summary of results and discussion

Mastication

One of the first reported wearable electronic devices for mastication was the 24-hour EMG system, developed in 1996¹², which evaluated 30 healthy adults (30.9 ± 5.8 years) for 24 hours. The device included surface electromyography (EMG) sensors positioned on the masseter muscle to measure muscle electrical activity throughout the monitoring period. This study determined the number and total duration of bursts that exceeded one-quarter of the maximum discharge value during maximal contraction. Most high-amplitude bursts were observed during meals, while low-amplitude bursts were detected throughout the day.

Another group developed the Smart Eyeglasses, which used dual-channel surface EMG sensors on the temple to record muscle activity and detect the mastication cycle and rate. The device was highly accurate in laboratory and free-living situations in two studies with 20 healthy adults (25.1 ± 2.1 years). The feeding detection algorithm identified eating events with > 95% accuracy, recording 44 eating occasions in 122 hours of recording^28,31.

A 2017 study¹⁹ used the EMG-based eating detector to verify food intake in the daily lives of 14 healthy adults (21.7 ± 2.1 years). The device used disposable surface electrodes, placed on the bony structure behind each ear. After calibration in the laboratory, participants followed their daily routines while recording meals with a smartphone app. The recordings identified mastication episodes accurately, ruling out movement artifacts and false positive events.

Other wearable electronic devices for mastication have used different types of sensors positioned in various regions of the body. In a 2014 study¹⁶, 12 healthy adults (26.7 ± 3.7 years) were evaluated using the Automatic Ingestion Monitor, consisting of a jaw movement sensor (piezoelectric film element) located under the earlobe, a hand gesture sensor (proximity sensor) in the dominant hand, and an accelerometer integrated into a module worn around the neck. These sensors interact with a smartphone to detect food intake during daily life. The system was validated in a 24-hour study in which participants had no restrictions on daily activities or food intake, achieving an average 89.8% accuracy in detecting food intake.

A 2017 study²¹ with 18 healthy adults (27.7 ± 2.8 years) used a device called Smart Glasses, equipped with a piezoelectric voltage sensor located in the temporal muscle. It determined the cumulative number of chews per meal, the total duration of the meal, and the effective mastication time in seconds. Another study with 10 healthy adults (29.03 ± 12.20 years), carried out in the same year²², used the same device to calculate the number of mastication cycles, providing real-time feedback to help reduce the participants' food intake.

A 2017 study²⁴ used an ocular device called GlasSense on 10 participants. It used load cells installed in the hinges of the glasses to detect temporal muscle activity during eating and other related activities, such as natural head movement, speech, and blinking. Validation of the device demonstrated an average 89% accuracy in detecting different behavioral patterns, reaching 94% for activities such as mastication, head movement, speech, and blinking.

Studies conducted in 2022^34,35 used the Bitescan in samples of 99 and 365 healthy adults, with mean ages of 36.4 ± 11.7 years and 36.6 ± 12.1 years, respectively. The Bitescan is equipped with an infrared distance sensor and an accelerometer, positioned at the back of the ear, and was developed to monitor morphological changes in this region during mastication. It measured the number of chews and bites, the number of chews per bite, the mastication speed, and parameters such as the number of mastication cycles, the mastication rate, and the total mastication time. These data were transmitted via Bluetooth to a smartphone connected to the device, allowing a detailed analysis of mastication behavior.

Finally, some studies have used wearable electronic devices inside the ear canal to monitor chewing. A 2013 study¹⁵ used the Microphone Sensor System, which consists of two electret microphones integrated into a hearing aid: one placed inside the external auditory canal and the other above the external ear. This system detected mastication events automatically throughout a continuous analysis of 51 healthy adults (mean age 34.8 years), based on sounds generated during the mastication process.

A 2018 study²⁵ developed the Earable RCC, which uses an optical distance sensor inserted into the ear canal. It measures changes in the shape of the ear canal caused by jaw movement during mastication and was tested in six healthy adults (mean age 28.2 years). The device achieved an accuracy greater than 95% in counting mastication cycles.

In 2017²³ another study developed an innovative system consisting of an in-ear microphone combined with a photoplethysmography (PPG) sensor. The microphone is positioned inside the external auditory canal, while the PPG transmitters and receivers are positioned on both sides of the ear concha, in which mastication was found to significantly affect blood flow. The device accurately detected mastication events in 22 healthy adults (mean age 22.9 years), with 93.8% accuracy. The system was also connected to a data logger, which stores the audio and PPG signals for later analysis. In addition, the data logger is equipped with a triaxial accelerometer to detect intense physical activities, such as walking or running, avoiding false classification of such activities as mastication events.

In summary, mastication has been analyzed remotely only in healthy adults, through different types of wearable devices using a variety of sensors, such as surface EMG, piezoelectric sensors, mandibular movement sensors, infrared sensors, and microphones. These sensors are positioned in different regions of the body, such as the submental region, masseter, temple, pinna, and auditory canal. Wearable devices provide detailed information on the number of mastication cycles, number of bites, number of chews per bite, mastication speed and rate, and total mastication time, and detect food intake during daily activities. Some devices can also monitor muscle activity and mandibular movement during mastication, analyzing parameters such as amplitude, duration, and frequency of events, offering a comprehensive view of mastication and eating behavior^{12,15,16,19,21-25}.

Swallowing

Several authors have reported the use of wearable devices to study swallowing function. In 2015, a neck belt (FSR throat belt) connected to a portable Holter was developed to measure swallowing capacity in 19 healthy adults¹⁷. The device consisted of a force-sensing resistor (FSR) fixed to the center of the thyroid cartilage and attached to a belt around the neck. It determined onset latency, total excursion time, and jitter (the period during which the pharynx pushes the bolus towards the esophagus). In addition, they used conventional surface electrodes on the submental muscle to measure onset latency and duration of muscle activity, as well as a nasal cannula placed in front of the nose to calculate the duration of apnea during swallowing, all connected to the same portable Holter.

The same wearable device was used later in a study with 19 adult smokers (37.68 ± 7.13 years) and 26 nonsmoking controls (38.12 ± 6.45 years)²⁹. This study proposed a self-diagnostic program that could quickly and conveniently identify and record the same swallowing events observed in the previous study, besides differentiating swallowing patterns, with virtually no significant delays compared to the videofluoroscopic swallowing study (VFSS). Although the authors described the device as wearable, both studies were conducted in a laboratory setting.

A device called Swallowing Frequency Meter was used in 2012 in 15 healthy adults (mean age 28.6 years)¹⁴. The device consisted of a laryngeal microphone located on the lateral edge of the trachea immediately below the cricoid cartilage, connected to an MP3 recorder. The number of swallowing events was assessed by auditory judgment of the sounds captured and by visual analysis of the waveform. The experiments were performed in a laboratory environment, ensuring controlled conditions for the assessment of swallowing frequency and patterns.

Proper sensors have also been developed for wearable devices. A 2017 pilot study involving four healthy adults (aged 21-35 years) developed a device for swallowing training called the Skin-Friendly Electronic System²⁰. The device consisted of “skin-like” surface electrodes placed on the submental muscles to record muscle activity during swallowing. They were connected to a Bluetooth wireless transmitter, which sent the signals to a real-time analysis system. Swallowing activity was monitored using a classification algorithm based on RMS (Root Mean Square) values ​​and a three-part threshold technique, distinguishing swallowing from other muscle activities. The data were processed in real time to provide feedback to the user and aid in the training and rehabilitation of patients with dysphagia.

Studies conducted in 2019 and 2020^30,32 developed and validated a biofeedback system (Sensor Patch System) to monitor submental muscle activity during swallowing. In a 2019 pilot study³⁰, a healthy 23-year-old adult used the device consisting of two pairs of surface electrodes in the submental area and a voltage cell in the laryngeal prominence, connected to a portable unit attached to the user's clothing, with Bluetooth communication. This system identified the beginning, duration, and end of swallowing events and provided real-time visual feedback to assist in rehabilitation maneuvers, such as effortful swallowing and the Mendelsohn maneuver, being tested in a 70-year-old person with dysphagia and Parkinson's disease³⁰. A 2020 study³² validated the system in a group of 40 healthy adults (67.5 ± 7.85 years), comparing the signals obtained with conventional electrodes and those of the Sensor Patch System. The comparison showed that the surface EMG signals obtained with the new device were equivalent to those obtained with conventional electrodes. It also evaluated the safety, comfort, and efficiency in placing the electrodes, showing that the new device resulted in greater participant satisfaction and fewer adverse skin effects³².

In a 2023 laboratory study³⁶, 17 healthy adults (30-60 years old) were evaluated using a wearable swallowing assessment device, composed of a hetero-core fiber optic pressure sensor, positioned on the skin surface of the laryngeal prominence and fixed by a belt around the neck. Two valleys were found in all subjects’ swallowing waveforms, meaning that the device could detect laryngeal movement during swallowing accurately. The main result of this study was the accurate assessment of swallowing time, showing significant differences between age groups, suggesting a correlation between aging and swallowing functioning.

Other wearable devices have used piezoelectric sensors. A 1996 study¹³ evaluated 21 people with Parkinson's disease (mean age 62.0 years) and 21 healthy controls (39.4 years), using a device called Digital Phagometer. The equipment consisted of a piezoelectric sensor positioned in the region between the cricoid and thyroid cartilages to detect spontaneous swallowing. The data were later analyzed on a computer, comparing the frequency of spontaneous swallowing between the groups. The study revealed that patients with Parkinson's disease had a significantly lower frequency of spontaneous swallowing at rest, whereas voluntary water intake did not differ significantly between the two groups.

A 2015 study¹⁸ used a set of sensors to assess swallowing in 38 patients with unilateral stroke (52.0 ± 6.5 years) and 59 healthy controls (54.9 ± 8.4 years). The system consisted of EMG electrodes positioned in the submental region to measure muscle activity, a piezoelectric sensor located at the level of the thyroid cartilage to monitor laryngeal movement, and a cannula-type nasal flow sensor to assess the respiratory pattern during swallowing. With these sensors, the researchers determined the onset latency, the amplitude of the thyroid cartilage excursion signal, the total duration of laryngeal excursion, the laryngeal excursion jitter, and the duration of swallowing apnea. These parameters allowed them to differentiate swallowing patterns between stroke patients and controls, providing important data for understanding swallowing difficulties after stroke.

The review identified a 2018 study²⁷ that used the Strain Sensor Device to evaluate 14 people with head and neck cancer (43-83 years old) and one control participant (24 years old). The device consisted of a strain sensor with piezoresistive response and surface electrodes positioned in the submental region. The study used the device and machine learning algorithms to classify the strain signals captured by the sensor, according to the type of bolus swallowed and the subject’s condition, differentiating healthy from dysphagic individuals.

A study published in 2018²⁶ evaluated 52 individuals with dysphagia (75.5 ± 20.5 years) and 140 controls (54.5 ± 32 years) using a cannula-type nasal flow sensor and a custom piezoelectric sensor positioned over the thyroid cartilage. With these sensors, they determined expiratory flow, laryngeal movement, and swallowing sounds. The data were processed by a Support Vector Machine (SVM) using linear predictive coding (LPC) to extract features from the signals and classify the records as belonging to healthy individuals or patients with dysphagia. The method had 82.4% sensitivity and 86% specificity, proving to be effective in screening swallowing function and detecting unsafe swallows, such as laryngeal penetrations and aspirations.

The use of a device consisting of an acoustic mechanical sensor positioned in the suprasternal notch was described in 2022, specifically designed to monitor swallowing and breathing³³. The system was tested in a person with dysphagia and Parkinson's disease and two healthy controls (aged 29 and 32). They also used a nasal cannula and respiratory inductance plethysmography bands to measure swallowing and breathing cycles simultaneously. The study aimed to evaluate the coordination between swallowing and breathing, providing continuous data to analyze the synchrony between these essential functions in patients with dysphagia.

In summary, swallowing has been studied with wearable devices that employ various sensors, such as force sensors, surface EMG, piezoelectric, nasal flow, and strain sensors, positioned in areas such as the submental region, thyroid cartilage, and suprasternal notch. These devices measure parameters such as onset latency, duration of laryngeal excursion, amplitude of muscle signals, and swallowing apnea. Some studies used machine learning to classify the signals between healthy and dysphagic individuals. Techniques vary between sound analysis and monitoring laryngeal movement and muscle activity. Although some devices are adapted for daily use, many studies are still restricted to the laboratory environment. The majority was carried out in healthy adults, with a few including patients with dysphagia^{13,14,17,18,20,26,27,30,32,33,36}.

It is important to emphasize that the wearable electronic devices analyzed in this study do not cover all the mastication and swallowing characteristics evaluated in clinical and instrumental examinations. In this regard, a device intended for domestic use in daily life situations only has real value if the data collected are compatible with those obtained in evaluations carried out by specialized professionals²⁷.

In this sense, objective (instrumental) and subjective (clinical) methods predominate in masticatory function assessment. Surface EMG stands out among the instrumental methods, as it measures the time and intensity of muscle contractions with high specificity³⁷, as well as electrognathography, which evaluates mandibular movements during mastication³⁸. They also use methods of processing chewed materials, such as fractional sieving, spectrophotometry, and optical scanning, enabling a detailed analysis of the properties of the food bolus³⁹. Clinical assessments use protocols such as the Orofacial Myofunctional Evaluation Protocol with Scores⁴⁰ and the Mouth-Gastric-Respiratory Motor Function Protocol⁴¹, which evaluate the morphology and biomechanics of the structures involved in mastication. They provide information on mandibular movement, occlusion, dentition, and functioning of orofacial structures, using photographic and videographic records to document masticatory patterns^40,41.

Swallowing function is assessed by instrumental methods - e.g., the VFSS and the flexible endoscopic evaluation of swallowing⁴² - and clinical methods - e.g., the Volume-Viscosity Swallowing Test (V-VST)⁴³, the Functional Oral Intake Scale (FOIS)⁴⁴, and the Speech-Language-Hearing Dysphagia Risk Evaluation Protocol (PARD)⁴⁵. Some instruments, such as the McGill Ingestive Skills Assessment (MISA)⁴⁶, assess ingestion skills, while others assess the patient’s dysphagia-related quality of life and functional status⁴⁷. Moreover, tests address the integrity of the cranial nerves and anatomy and the orofacial physiology⁴⁸.

However, few of the studies reviewed in this analysis integrate these instrumental and clinical assessments into the development and validation of their devices. Such methods must be incorporated to ensure that data collected in home settings are compatible with those obtained by professionals. It is important to emphasize that wearable devices should be seen as complementary tools, providing additional data to enrich the assessments performed by specialized professionals, rather than replacing them.

On the other hand, the food intake sequence has been described with central phases of ingestion, processing (mastication), and swallowing⁷. Several periods of this sequence are performed in a meal to process a portion of food and prepare it for digestion. One or more eating activities can be identified in each phase, such as intake, mastication, and swallowing. Each activity occurs in a specific location, such as the arm, head, or neck, allowing the use of several sensors to monitor the anatomical structures and associated physiological processes. However, the devices found in this review do not consider the integrated monitoring of mastication and swallowing in a single device, regardless of its clinically recognized importance.

Thus, the development of new low-cost, reusable devices capable of monitoring the ingestion, mastication, and swallowing phases in an integrated manner could offer more comprehensive support aligned with the practice of health professionals who treat oral feeding efficiency and safety disorders in adults with various health conditions. Speech-language-hearing pathologists are the professionals responsible for intervening in adults and older adults with mastication and swallowing disorders⁴⁹, which makes their participation in the development and validation of this type of device essential.

Limitations

One of the main limitations of this scoping review was the restricted selection of databases, limited to PubMed and MEDLINE, which may have excluded relevant studies available in other databases. This approach may have reduced the diversity of research included in the analysis. In addition, limiting the language of publication to Spanish, English, and Portuguese may have excluded important research published in other languages, affecting the representativeness of the findings.

Lastly, another important limitation was not having considered wearable devices associated with the food intake phase, which could have covered all the central phases of a dietary event.

CONCLUSION

This scoping review showed that wearable electronic devices designed for monitoring mastication in adults use sensors such as surface EMG, piezoelectric sensors, infrared sensors, and in-ear sensors. They are mainly positioned in the submental region, masseter, temple, pinna, and auditory canal to monitor mastication cycles, number of bites, and parameters such as mastication rate and speed.

Regarding swallowing, the identified wearable devices use sensors such as surface EMG, piezoelectric sensors and microphones on the thyroid cartilage, submental region, and suprasternal notch. These devices monitor parameters such as pharyngeal phase onset latency, muscle signal amplitude, swallowing duration, and swallowing apnea.

The wearable devices analyzed are mainly applied to healthy adults and provide data on mastication and swallowing in both clinical settings and everyday life. However, new devices that integrate the ingestion, processing, and swallowing phases with greater support from health professionals still need to be developed and validated to improve comprehensive and effective monitoring of these functions in various health conditions.

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• A study conducted at the Speech-Language-Hearing Department at the School of Dentistry of Bauru - Universidade de São Paulo, Bauru, São Paulo, Brazil.
• Financial support: Nothing to declare
• Data sharing statement
  This study is a literature review, therefore, it did not include human participants or collect primary data. All information analyzed is publicly available in the referenced sources. There is no additional data to be shared.

Edited by

• Chief Editor
  Hilton Justino da Silva

• Area Editor
  Kelly da Silva

Data availability

This study is a literature review, therefore, it did not include human participants or collect primary data. All information analyzed is publicly available in the referenced sources. There is no additional data to be shared.

Publication Dates

• Publication in this collection
  07 Nov 2025
• Date of issue
  2025

History

• Received
  25 May 2024
• Reviewed
  09 Oct 2024
• Accepted
  04 May 2025