WEARABLE SWALLOW SENSOR FOR LARYNGEAL MOVEMENTS MONITORING

Abstract

With the development of modern medical science, oropharyngeal swallowing disorders (dysphagia) have been gaining increasing attention as a common symptom of neurological impairment such as Parkinson’s disease. Current diagnosis and monitoring techniques including videofluoroscopy and endoscopy can be effective, but they are only available at hospitals and require experienced pathologists, as well as expensive equipment. To address this problem, wearable healthcare devices can be an ideal solution. However, sophisticated design, fragile structure and expensive materials also make the currently available devices destined for bad durability and comparatively high cost. On the other hand, the fabrication of the sensors usually introduces hazardous chemicals, leaving the safety issue questionable. The design of affordable, fully biocompatible and easy-to-operate devices is thus in demand. In this research, flexible non-invasive swallow sensors were developed based on pressure measurement and strain measurement respectively. The pressure-based swallow sensor used a micro-patterned piezoresistive sensor based on graphene to detect the pressure change due to throat movement. Optimization of the adhesive layer was conducted to achieve better device durability. Two kinds of strain-based swallow sensors were fabricated using Gallium–Indium eutectic and carbon black respectively. As compared with the Gallium–Indium eutectic based sensor, carbon black based sensor was easier to fabricate with one-step printing and showed higher sensitivity to muscle movement. Different patterns of the carbon black sensor were designed to explore the optimal measuring position and the potential of multi-point monitoring. Testing of the sensors was carried out on both male and female subjects. The results were analyzed based on different measuring mechanisms, different sensing region patterns and different positions. All of the sensors can distinguish different throat movements via signal waveforms, revealing their potential to be used as a promising candidate for future healthcare devices.