This article demonstrates an instrumented mouthguard capable of non-invasively monitoring salivary uric acid (SUA) levels. The enzyme (uricase)-modified screen printed electrode system has been integrated onto a mouthguard platform along with anatomically-miniaturized instrumentation electronics featuring a potentiostat, microcontroller, and a Bluetooth Low Energy (BLE) transceiver. Unlike RFID-based biosensing systems, which require large proximal power sources, the developed platform enables real-time wireless transmission of the sensed information to standard smartphones, laptops, and other consumer electronics for on-demand processing, diagnostics, or storage. The mouthguard biosensor system offers high sensitivity, selectivity, and stability towards uric acid detection in human saliva, covering the concentration ranges for both healthy people and hyperuricemia patients. The new wireless mouthguard biosensor system is able to monitor SUA level in real-time and continuous fashion, and can be readily expanded to an array of sensors for different analytes to enable an attractive wearable monitoring system for diverse health and fitness applications.

There is a need to monitor patients with cancer of the head and neck postradiation therapy, as diminished swallowing activity can result in disuse atrophy and fibrosis of the swallowing muscles. This paper describes a flexible strain sensor comprising palladium nanoislands on single-layer graphene. These piezoresistive sensors were tested on 14 disease-free head and neck cancer patients with various levels of swallowing function: from nondysphagic to severely dysphagic. The patch-like devices detected differences in (1) the consistencies of food boluses when swallowed and (2) dysphagic and nondysphagic swallows. When surface electromyography (sEMG) is obtained simultaneously with strain data, it is also possible to differentiate swallowing vs nonswallowing events. The plots of resistance vs time are correlated to specific events recorded by video X-ray fluoroscopy. Finally, we developed a machine-learning algorithm to automate the identification of bolus type being swallowed by a healthy subject (86.4%. accuracy). The algorithm was also able to discriminate between swallows of the same bolus from either the healthy subject or a dysphagic patient (94.7% accuracy). Taken together, these results may lead to noninvasive and home-based systems for monitoring of swallowing function and improved quality of life.

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Hearing loss is one of the most common conditions affecting older adults worldwide. Frequent complaints from the users of modern hearing aids include poor speech intelligibility in noisy environments and high cost, among other issues. However, the signal processing and audiological research needed to address these problems has long been hampered by proprietary development systems, underpowered embedded processors, and the difficulty of performing tests in real-world acoustical environments. To facilitate existing research in hearing healthcare and enable new investigations beyond what is currently possible, we have developed a modern, open-source hearing research platform, Open Speech Platform (OSP). This paper presents the system design of the complete OSP wearable platform, from hardware through firmware and software to user applications. The platform provides a complete suite of basic and advanced hearing aid features which can be adapted by researchers. It serves web apps directly from a hotspot on the wearable hardware, enabling users and researchers to control the system in real time. In addition, it can simultaneously acquire high-quality electroencephalography (EEG) or other electrophysiological signals closely synchronized to the audio. All of these features are provided in a wearable form factor with enough battery life for hours of operation in the field. INDEX TERMS Hearing aids (HAs), wearable computers, speech processing, field programmable gate arrays (FPGAs), electrophysiology (EEG), system-level design, open source hardware, embedded software, Internet of Things, research initiatives.