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Artificial intelligence algorithms are being adopted to analyze medical data, promising faster interpretation to support doctors’ diagnostics. The next frontier is to bring these powerful algorithms to implantable medical devices. Herein, a closed‐loop solution is proposed, where a cellular neural network is used to detect abnormal wavefronts and wavebrakes in cardiac signals recorded in human tissue is trained to achieve >96% accuracy, >92% precision, >99% specificity, and >93% sensitivity, when floating point precision weights are assumed. Unfortunately, the current hardware technologies for floating point precision are too bulky or energy intensive for compact standalone applications in medical implants. Emerging device technologies, such as memristors, can provide the compact and energy‐efficient hardware fabric to support these efforts and can be reliably embedded with existing sensor and actuator platforms in implantable devices. A distributed design that considers the hardware limitations in terms of overhead and limited bit precision is also discussed. The proposed distributed solution can be easily adapted to other medical technologies that require compact and efficient computing, like wearable devices and lab‐on‐chip platforms. 

Abstract Bioelectronic devices that allow simultaneous accurate monitoring and control of the spatiotemporal patterns of cardiac activity provide an effective means to understand the mechanisms and optimize therapeutic strategies for heart disease. Optogenetics is a promising technology for cardiac research due to its advantages such as cell‐type selectivity and high space‐time resolution, but its efficacy is limited by the insufficient number of modulation channels and lack of simultaneous spatiotemporal mapping capabilities in current implantable cardiac optogenetics tools available for in vivo investigations. Here, soft implantable electro‐optical cardiac devices integrating multilayered highly uniform arrays of transparent microelectrodes and multicolor light‐emitting diodes in thin, flexible platforms are designed for mechanically compliant high‐content high‐precision electrical mapping and single‐/multi‐site optogenetics and electrical stimulation without light‐induced artifacts. Systematic benchtop characterizations, together with ex vivo and in vivo evaluations on healthy and diseased small animal hearts and human cardiac slices demonstrate their functionalities in real‐time spatiotemporal mapping and control of cardiac rhythm and function, with broad applications in basic and ultimately clinical cardiology. 

Abstract Transparent microelectrodes have recently emerged as a promising approach for crosstalk‐free multifunctional electrical and optical biointerfacing. High‐performance flexible platforms that allow seamless integration with soft tissue systems for such applications are urgently needed. Here, silver nanowires (Ag NWs)‐based transparent microelectrode arrays (MEAs) and interconnects are designed to meet this demand. The nanowire networks exhibit a high optical transparency >90.0% at 550 nm, and superior mechanical stability up to 100,000 bending cycles at 5 mm radius. The Ag NWs microelectrodes preserve low normalized electrochemical impedance of 3.4–15 Ω cm²at 1 kHz, and the interconnects demonstrate excellent sheet resistance (R_sh) of 4.1–25 Ω sq⁻¹. In vivo histological analysis reveals that the Ag NWs structures are biocompatible. Studies on Langendorff‐perfused mouse and rat hearts demonstrate that the Ag NWs MEAs enable high‐fidelity real‐time monitoring of heart rhythm during co‐localized optogenetic pacing and optical mapping. This proof‐of‐concept work illustrates that the solution‐processed, transparent, and flexible Ag NWs structures are a promising candidate for the next‐generation of large‐area multifunctional biointerfaces for interrogating complex biological systems in basic and translational research.