Search

There is a need for flexible chemical sensors for the ecological and physiological research of avian species such as house sparrows (Passer domesticus). Current methods in this field are invasive and require multiple physical interactions with the birds. Emerging research in flexible bioelectronics can enable realization of implantable devices that are mechanically compliant with the underlying tissues for continuous real-time sensing in situ. However, challenges still remain in forming an intimate flexible interface. One of the promising flexible bioelectronic platforms for tissue-embedded sensing is based on functionalizing surgical sutures or threads. Threads have three-dimensional flexibility, high surface-area-to-volume ratio, inherent wicking properties, and are easily functionalizable using reel-to-reel dip coating. Threads are ideal as they are lightweight, therefore, would not interfere with flight motion and would only require minimal interaction with the bird. However, the challenge remains in achieving a highly conductive yet flexible electrode for electrochemical sensing using materials such as gold. In this study, we address this issue through novel gold deposition directly on thread substrate followed by enzyme immobilization to realize flexible electrochemical glucose biosensors on medical-grade sutures. These sensors were calibrated and tested in a range that is wide enough to include the expected range of glucose concentration in house sparrows (0–8.55 mM). Glucose monitoring in house sparrows will provide insights into energy metabolism and regulation during stress responses. In addition, the stability, repeatability, and selectivity of the sensor were tested with final validation in a real bird. Our innovative gold-coated, thread-based flexible electrochemical glucose sensor can also be used in other small and large animals. This can also be extended to monitoring other metabolites in future. [ABSTRACT FROM AUTHOR]

The design and implementation of a portable fluorescence-based vapor sensing system are described. The system incorporates previously developed microsensor array technology into a compact, low-power device capable of collecting and delivering ambient vapor samples to the array while monitoring and recording the fluorescent responses of the sensors. The sensors respond differentially when exposed to a sample vapor and, when processed using a support vector machine (SVM) pattern recognition algorithm, are shown to discriminate between three classes of petroleum distillates. The system was characterized using sample vapors prepared under several different conditions in three sensing scenarios. The first scenario demonstrates the basic operational capability of the device in the field by presenting high concentration vapors to the array. The second scenario introduces the potential for a greater degree of variability in both sample vapor concentration and composition in an effort to emulate real-world sensing conditions. The third scenario uses an on-board trained pattern recognition algorithm to identify unknown vapors as their responses are collected. The device demonstrated high classification accuracy throughout the field tests and is capable of improving its classification accuracy when challenged with samples presented under variable ambient conditions by enhancing the signal-to-noise ratio of the array response.