Curved surfaces, complex geometries, and time-dynamic deformations of the heart create challenges in establishing intimate, nonconstraining interfaces between cardiac structures and medical devices or surgical tools, particularly over large areas. We constructed large area designs for diagnostic and therapeutic stretchable sensor and actuator webs that conformally wrap the epicardium, establishing robust contact without sutures, mechanical fixtures, tapes, or surgical adhesives. These multifunctional web devices exploit open, mesh layouts and mount on thin, bio-resorbable sheets of silk to facilitate handling in a way that yields, after dissolution, exceptionally low mechanical moduli and thicknesses. In vivo studies in rabbit and pig animal models demonstrate the effectiveness of these device webs for measuring and spatially mapping temperature, electrophysiological signals, strain, and physical contact in sheet and balloon-based systems that also have the potential to deliver energy to perform localized tissue ablation.flexible electronics | semiconductor nanomaterials | stretchable electronics | implantable biomedical devices | cardiac electrophysiology C ardiac arrhythmias occur in all component structures and 3D regions of the heart, resulting in significant challenges in diagnosis and treatment of precise anatomic targets (1). Many common arrhythmias, including atrial fibrillation and ventricular tachycardia, originate in endocardial substrates and then propagate in the transverse direction to affect epicardial regions (1, 2). Characterizing arrhythmogenic activity at specific regions of the heart is thus critical for establishing the basis for definitive therapies such as cardiac ablation (3). Advanced tools that offer sufficient spatial resolution (<1 mm) and intimate mechanical coupling with myocardial tissue, but without undue constraints on natural motions, would therefore be of great clinical importance (4-6). To date, cardiac ablation procedures have largely relied on point ablation catheters deployed in the endocardial space (1, 5, 7-9). Although successful in the treatment of simple arrhythmias originating in and around the pulmonary veins, these devices are poorly suited for treating complex arrhythmias, such as persistent atrial fibrillation (10-13), that arise from various sites inside the left atrium. Other classes of devices have demonstrated the utility of spatiotemporal voltage mapping using various modes of operation, including noninvasive surface mapping designs (14, 15), epicardial voltage-mapping "socks" (16-20), and endocardial contact and noncontact catheters, with densities approaching 64 electrodes (21-31). These solutions all exploit arrays of passive metal wirebased electrodes integrated on wearable vests and socks (14-20) or catheter systems (21-26) for mapping of complex arrhythmias. Building such mesh structures requires manual assembly and is only possible because the individual wires are millimeter scale in diameter and thus sufficiently large to be threaded to form a mesh.Fo...

In this paper, we present a three-dimensional graphene foam made of few layers of CVD grown graphene as a scaffold for growing cardiac cells and recording their electrical activity. Our results show that graphene foam not only provides an excellent extra-cellular matrix (ECM) for the culture of such electrogenic cells but also enables recording of its extracellular electrical activity in-situ. Recording is possible due to graphene's excellent conductivity. In this paper, we present our results on the fabrication of the graphene scaffold and initial studies on the culture of cardiac cell lines such as HL-1 and recording of their real-time electrical activity.

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Computer vision algorithms are often limited in their application by the large amount of data that must be processed. Mammalian vision systems mitigate this high bandwidth requirement by prioritizing certain regions of the visual field with neural circuits that select the most salient regions. This work introduces a novel and computationally efficient visual saliency algorithm for performing this neuromorphic attention-based data reduction. The proposed algorithm has the added advantage that it is compatible with an analog CMOS design while still achieving comparable performance to existing state-of-the-art saliency algorithms. This compatibility allows for direct integration with the analog-to-digital conversion circuitry present in CMOS image sensors. This integration leads to power savings in the converter by quantizing only the salient pixels. Further system-level power savings are gained by reducing the amount of data that must be transmitted and processed in the digital domain. The analog CMOS compatible formulation relies on a pulse width (i.e., time mode) encoding of the pixel data that is compatible with pulse-mode imagers and slope based converters often used in imager designs. This letter begins by discussing this time-mode encoding for implementing neuromorphic architectures. Next, the proposed algorithm is derived. Hardware-oriented optimizations and modifications to this algorithm are proposed and discussed. Next, a metric for quantifying saliency accuracy is proposed, and simulation results of this metric are presented. Finally, an analog synthesis approach for a time-mode architecture is outlined, and postsynthesis transistor-level simulations that demonstrate functionality of an implementation in a modern CMOS process are discussed.