Electrical Capacitance Tomography of Cell Cultures on a CMOS Microelectrode Array.

Electrical capacitance tomography (ECT) can be used to predict information about the interior volume of an object based on measured capacitance at its boundaries. Here, we present a microscale capacitance tomography system with a spatial resolution of 10 microns using an active CMOS microelectrode array. We introduce a deep learning model for reconstructing 3-D volumes of cell cultures using the boundary capacitance measurements acquired from the sensor array, which is trained using a multi-objective loss function that combines a pixel-wise loss function, a distribution-based loss function, and a region-based loss function to improve model's reconstruction accuracy. The multi-objective loss function enhances the model's reconstruction accuracy by 3.2% compared to training only with a pixel-wise loss function. Compared to baseline computational methods, our model achieves an average of 4.6% improvement on the datasets evaluated. We demonstrate our approach on experimental datasets of bacterial biofilms, showcasing the system's ability to resolve microscopic spatial features of cell cultures in three dimensions. Microscale capacitance tomography can be a low-cost, low-power, label-free tool for 3-D imaging of biological samples.

Tac-Trainer: A Visual Analytics System for IoT-based Racket Sports Training.

Conventional racket sports training highly relies on coaches' knowledge and experience, leading to biases in the guidance. To solve this problem, smart wearable devices based on Internet of Things technology (IoT) have been extensively investigated to support data-driven training. Considerable studies introduced methods to extract valuable information from the sensor data collected by IoT devices. However, the information cannot provide actionable insights for coaches due to the large data volume and high data dimensions. We proposed an IoT + VA framework, Tac-Trainer, to integrate the sensor data, the information, and coaches' knowledge to facilitate racket sports training. Tac-Trainer consists of four components: device configuration, data interpretation, training optimization, and result visualization. These components collect trainees' kinematic data through IoT devices, transform the data into attributes and indicators, generate training suggestions, and provide an interactive visualization interface for exploration, respectively. We further discuss new research opportunities and challenges inspired by our work from two perspectives, VA for IoT and IoT for VA.

Microscale 3-D Capacitance Tomography with a CMOS Sensor Array.

Electrical capacitance tomography (ECT) is a non-optical imaging technique in which a map of the interior permittivity of a volume is estimated by making capacitance measurements at its boundary and solving an inverse problem. While previous ECT demonstrations have often been at centimeter scales, ECT is not limited to macroscopic systems. In this paper, we demonstrate ECT imaging of polymer microspheres and bacterial biofilms using a CMOS microelectrode array, achieving spatial resolution of 10 microns. Additionally, we propose a deep learning architecture and an improved multi-objective training scheme for reconstructing out-of-plane permittivity maps from the sensor measurements. Experimental results show that the proposed approach is able to resolve microscopic 3-D structures, achieving 91.5% prediction accuracy on the microsphere dataset and 82.7% on the biofilm dataset, including an average of 4.6% improvement over baseline computational methods.

Super-Resolution Electrochemical Impedance Imaging With a 512 × 256 CMOS Sensor Array.

Super-resolution imaging is a family of techniques in which multiple lower-resolution images can be merged to produce a single image at higher resolution. While super-resolution is often applied to optical systems, it can also be used with other imaging modalities. Here we demonstrate a 512 × 256 CMOS sensor array for micro-scale super-resolution electrochemical impedance spectroscopy (SR-EIS) imaging. The system is implemented in standard 180 nm CMOS technology with a 10 µm × 10 µm pixel size. The sensor array is designed to measure the mutual capacitance between programmable sets of pixel pairs. Multiple spatially-resolved impedance images can then be computationally combined to generate a super-resolution impedance image. We use finite-element electrostatic simulations to support the proposed measurement approach and discuss straightforward algorithms for super-resolution image reconstruction. We present experimental measurements of sub-cellular permittivity distribution within single green algae cells, showing the sensor's capability to produce microscale impedance images with sub-pixel resolution.

Programmable Electrochemical Stimulation on a Large-Scale CMOS Microelectrode Array.

In this paper we present spatio-temporally controlled electrochemical stimulation of aqueous samples using an integrated CMOS microelectrode array with 131,072 pixels. We demonstrate programmable gold electrodeposition in arbitrary spatial patterns, controllable electrolysis to produce microscale hydrogen bubbles, and spatially targeted electrochemical pH modulation. Dense spatially-addressable electrochemical stimulation is important for a wide range of bioelectronics applications.