As single-photon imaging becomes progressively more commonplace in sensing applications such as low-light-level imaging, three-dimensional profiling, and fluorescence imaging, there exist a number of fields where multispectral information can also be exploited, e.g., in environmental monitoring and target identification. We have fabricated a high-transmittance mosaic filter array, where each optical filter was composed of a plasmonic metasurface fabricated in a single lithographic step. This plasmonic metasurface design utilized an array of elliptical and circular nanoholes, which produced enhanced optical coupling between multiple plasmonic interactions. The resulting metasurfaces produced narrow bandpass filters for blue, green, and red light with peak transmission efficiencies of 79%, 75%, and 68%, respectively. After the three metasurface filter designs were arranged in a 64 × 64 format random mosaic pattern, this mosaic filter was directly integrated onto a CMOS single-photon avalanche diode detector array. Color images were then reconstructed at light levels as low as approximately 5 photons per pixel, on average, via the simultaneous acquisition of low-photon multispectral data using both three-color active laser illumination and a broadband white-light illumination source.

Precision metabolomics and quantification for cost-effective rapid diagnosis of disease are the key goals in personalized medicine and point-of-care testing. At present, patients are subjected to multiple test procedures requiring large laboratory equipment. Microelectronics has already made modern computing and communications possible by integration of complex functions within a single chip. As More than Moore technology increases in importance, integrated circuits for densely patterned sensor chips have grown in significance. Here, we present a versatile single complementary metal-oxide-semiconductor chip forming a platform to address personalized needs through on-chip multimodal optical and electrochemical detection that will reduce the number of tests that patients must take. The chip integrates interleaved sensing subsystems for quadruple-mode colorimetric, chemiluminescent, surface plasmon resonance, and hydrogen ion measurements. These subsystems include a photodiode array and a single photon avalanche diode array with some elements functionalized to introduce a surface plasmon resonance mode. The chip also includes an array of ion sensitive field-effect transistors. The sensor arrays are distributed uniformly over an active area on the chip surface in a scalable and modular design. Bio-functionalization of the physical sensors yields a highly selective simultaneous multiple-assay platform in a disposable format. We demonstrate its versatile capabilities through quantified bio-assays performed on-chip for glucose, cholesterol, urea, and urate, each within their naturally occurring physiological range.

There is a global unmet need for rapid and cost-effective prognostic and diagnostic tools that can be used at the bedside or in the doctor’s office to reduce the impact of serious disease. Many cancers are diagnosed late, leading to costly treatment and reduced life expectancy. With prostate cancer, the absence of a reliable test has inhibited the adoption of screening programs. We report a microelectronic point-of-care metabolite biomarker measurement platform and use it for prostate cancer detection. The platform, using an array of photodetectors configured to operate with targeted, multiplexed, colorimetric assays confined in monolithically integrated passive microfluidic channels, completes a combined assay of 4 metabolites in a drop of human plasma in under 2 min. A preliminary clinical study using l-amino acids, glutamate, choline, and sarcosine was used to train a cross-validated random forest algorithm. The system demonstrated sensitivity to prostate cancer of 94% with a specificity of 70% and an area under the curve of 0.78. The technology can implement many similar assay panels and hence has the potential to revolutionize low-cost, rapid, point-of-care testing.

Abnormal gait and postural instability are common disorders in people affected by Parkinson's disease (PD). This paper proposes an embedded cyber-physical system for the identification and the real-time extraction of highly selective diagnostic indexes for PD patients. A noninvasive wearable and wireless architecture for both gait analysis and postural instability detection has been proposed and implemented on a programmable hardware. The combined analysis of electroencephalography and electromyography allows studying the motor cortex activity through the movement-related potentials, determining a novel set of indexes that could be used for the PD diagnosis and classification. In a future perspective of an application-specific integrated circuit implementation, the real-time data processing has been fully realized on the Altera Cyclone V field-programmable gate array (FPGA), without interactions with embedded processor architecture. Referring to an Altera Cyclone V SE 5CSEMA5F31C6N device, the whole implemented architecture exploits 90% of the available FPGA adaptive logic modules, 74% of the manageable registers, and 10.3% of the total memory, as well as 29.7% wires utilization. Furthermore, the system is able to provide the outputs in about 57 ms with a dynamically power dissipation of 89 mW. The platform has been tested in vivo on two Parkinson's patients and two healthy subjects (control group) covering three typical diagnostic scenarios: PD versus controls, drug treatment evaluation, and involuntary movements detection.

Edible electronics and robotics are emerging areas intimately bridging food science and engineering to deliver technology using food‐derived materials. Edible devices offer unprecedented opportunities thanks to features such as bioresorbability, nutritional value, associated taste, minimal toxicity, and sustainability. However, several challenges need to be addressed to bring edible devices closer to reality. Although prototypal edible sensors are available, rotation sensors—an essential component for orientation perception—are still missing. Integrating sensors, actuators, and structural components into an edible system also remains a challenge due to the lack of processes and standardization. Here the first edible tilt sensor is presented. Starting from a commercial nonedible bistable tilt sensor, each material is replaced with edible equivalents using simple and straightforward fabrication approaches. Its functionality is validated in the first implementation of an autonomous and partly edible rolling robot, which has a nutritional value of 807.5 kcal and integrates gelatin actuators, an array of tilt sensors, and an edible wheeled frame. The robot works in closed loop, perceiving its orientation and input for actuation from the sensors. These findings may pave the way to novel edible technologies, from drug delivery for wild animals to health applications.