Multimodal Wearable Device for Continuous Swallowing Monitoring

Background

The fields of medical diagnostics and speech-language pathology require precise physiological monitoring of the anterior neck to evaluate complex biomechanical functions. Speech and swallowing rely on highly coordinated neuromuscular, acoustic, and structural activities within the throat. Disruptions to these processes—such as dysphagia—can lead to severe health complications, including malnutrition, dehydration, and aspiration pneumonia. Consequently, there is a critical medical need for diagnostic tools capable of accurately detecting, monitoring, and tracking the rehabilitation progress of speech and swallowing impairments over time to ensure timely interventions and improve patient outcomes.

However, current clinical approaches for assessing throat physiology and swallowing disorders suffer from significant limitations. Gold-standard diagnostic procedures, such as videofluoroscopy and fiberoptic endoscopic evaluation, are inherently episodic, offering only brief snapshots of patient function rather than continuous, longitudinal tracking. Furthermore, these methods are invasive, expensive, and restricted to specialized clinical environments, making routine or home-based screening inaccessible for many patients. Meanwhile, existing non-invasive monitoring attempts often struggle to accommodate diverse neck anatomies comfortably and fail to account for vascular motion artifacts, which severely degrades signal integrity and prevents the comprehensive, simultaneous assessment of the multiple physiological modalities involved in swallowing.

Technology

This technology is a non-invasive, wearable physiological monitoring system designed to assess the anterior neck region for speech and swallowing disorders like dysphagia. Housed in an ergonomic, adjustable neckband, the hardware utilizes a modular, three-printed circuit board architecture with sensor clusters positioned at the center, left, and right sides of the throat. These clusters integrate multiple complementary sensing modalities, including a tri-axial accelerometer, a piezoelectric vibration sensor, surface electromyography electrodes, a microphone, a photoplethysmography sensor, and a thermal sensor. An embedded microcontroller synchronously collects and wirelessly transmits this data to an external computing unit. There, a specialized software framework applies band-pass filtering and a Short-Time Energy algorithm to isolate swallowing episodes and extract critical biomechanical features across all sensor channels.

This solution is highly differentiated because it replaces episodic, expensive, and clinic-bound gold-standard assessments—such as videofluoroscopy and fiberoptic endoscopy—with a continuous, low-cost, home-based screening alternative. Unlike single-modality devices, its synchronized, multimodal architecture provides a comprehensive biomechanical and physiological profile of the throat, simultaneously tracking muscle activation, laryngeal motion, vocalizations, and cardiovascular metrics. Crucially, the integrated photoplethysmography sensor identifies vascular motion noise, allowing the system to filter out motion artifacts and maintain exceptional signal integrity. Furthermore, the modular circuit board layout ensures consistent skin contact and high signal quality across diverse neck anatomies. Validated with high accuracy against clinical reference standards and facing no known market competitors, this wearable platform offers a unique tool for remote health monitoring and speech-language pathology.

Benefits

• Enables non-invasive, continuous monitoring of speech and swallowing disorders outside of specialized clinical environments
• Provides a low-cost, home-based screening alternative to expensive, episodic clinical procedures like videofluoroscopy and endoscopy
• Delivers comprehensive physiological and biomechanical assessment by integrating multiple synchronized sensing modalities, including motion, muscle activity, acoustics, vibration, heart rate, and temperature
• Enhances user comfort and adapts to diverse neck anatomies through an adjustable, ergonomic, and modular circuit board architecture
• Ensures high signal integrity and accurate event detection by utilizing photoplethysmography data to identify and filter out vascular motion artifacts
• Facilitates real-time data visualization, storage, and remote clinical tracking via wireless data transmission

Applications

• Home-based dysphagia screening and monitoring
• Speech therapy progress tracking
• Post-stroke swallowing rehabilitation assessment
• Neuromuscular speech disorder diagnostics
• Continuous outpatient laryngeal health monitoring

Additional info

Dr. Amirtahà Taebi is an Assistant Professor with the Department of Bioengineering at Lehigh University. His work focuses on developing AI-powered sensing technologies, wearable and contactless monitoring systems, and digital twin modeling to advance noninvasive cardiovascular diagnostics. His research has been supported by local, state, and federal agencies, including the NSF, NIH, and Mississippi Institutions of Higher Learning.