Time-division multiplexing for cable reduction in ultrasound imaging catheters

In ultrasound imaging catheter applications, gathering the data from multi-element transducer arrays is difficult as there is a restriction on cable count due to the diameter of the catheter. In such applications, CMUT-on-CMOS technology allows for 2D arrays with many elements to be designed and bonded directly onto CMOS circuitry. This allows for complex electronics to be placed at the tip of the catheter which leads to the possibility to include electronic multiplexing techniques to greatly reduce the cable count required for a large element array. Current approaches to cable reduction tend to rely on area and power hungry circuits to function, making them unsuitable for use in catheters. Furthermore the length requirement for catheters and lack of power available to on-chip cable drivers leads to limited signal strength at the receiver end. In this paper an alternative approach using Analogue Time Division Multiplexing (TDM) is presented, which addresses the cable restrictions of the catheter and, using a novel digital demultiplexing technique, allows for a reduction in the number of analogue signal processing stages required

Direct Digital Demultiplexing of Analog TDM Signals for Cable Reduction in Ultrasound Imaging Catheters.

In real-time catheter based 3D ultrasound imaging applications, gathering data from the transducer arrays is difficult as there is a restriction on cable count due to the diameter of the catheter. Although area and power hungry multiplexing circuits integrated at the catheter tip are used in some applications, these are unsuitable for use in small sized catheters for applications like intracardiac imaging. Furthermore, the length requirement for catheters and limited power available to on-chip cable drivers leads to limited signal strength at the receiver end. In this paper an alternative approach using Analog Time Division Multiplexing (TDM) is presented which addresses the cable restrictions of ultrasound catheters. A novel digital demultiplexing technique is also described which allows for a reduction in the number of analog signal processing stages required. The TDM and digital demultiplexing schemes are demonstrated for an intracardiac imaging system that would operate in the 4 MHz to 11 MHz range. A TDM integrated circuit (IC) with 8:1 multiplexer is interfaced with a fast ADC through a micro-coaxial catheter cable bundle, and processed with an FPGA RTL simulation. Input signals to the TDM IC are recovered with -40 dB crosstalk between channels on the same micro-coax, showing the feasibility of this system for ultrasound imaging applications

Future of smart cardiovascular implants

Cardiovascular disease remains the leading cause of death in Western society. Recent technological advances have opened the opportunity of developing new and innovative smart stent devices that have advanced electrical properties that can improve diagnosis and even treatment of previously intractable conditions, such as central line access failure, atherosclerosis and reporting on vascular grafts for renal dialysis. Here we review the latest advances in the field of cardiovascular medical implants, providing a broad overview of the application of their use in the context of cardiovascular disease rather than an in-depth analysis of the current state of the art. We cover their powering, communication and the challenges faced in their fabrication. We focus specifically on those devices required to maintain vascular access such as ones used to treat arterial disease, a major source of heart attacks and strokes. We look forward to advances in these technologies in the future and their implementation to improve the human condition

IEEE Access Special Section Editorial: Wearable and Implantable Devices and Systems

© 2013 IEEE. Circuit techniques, sensors, antennas and communications systems are envisioned to help build new technologies over the next several years. Advances in the development and implementation of such technologies have already shown us their unique potential in realizing next-generation sensing systems. Applications include wearable consumer electronics, healthcare monitoring systems, and soft robotics, as well as wireless implants. There have been some interesting developments in the areas of circuits and systems, involving studies related to low-power electronics, wireless sensor networks, wearable circuit behaviour, security, real-time monitoring, connectivity of sensors, and Internet of Things (IoT). The direction for the current technology is electronics systems on large area electronics, integrated implantable systems and wearable sensors. So far, the research in the field has focused on materials, new processing techniques and one-off devices, such as diodes and transistors. However, current technology is not sufficient for future electronics to be useful in new applications; a great demand exists to scale up the research towards circuits and systems. Recent developments indicate that, in addition to fabrication technology, special attention should also be given to design, simulation and modeling of electronics, while keeping sensing system integration, power management, and sensors network under consideration

Learned Kernels for Interpretable and Efficient PPG Signal Quality Assessment and Artifact Segmentation

Photoplethysmography (PPG) provides a low-cost, non-invasive method to continuously monitor various cardiovascular parameters. PPG signals are generated by wearable devices and frequently contain large artifacts caused by external factors, such as motion of the human subject. In order to ensure robust and accurate extraction of physiological parameters, corrupted areas of the signal need to be identified and handled appropriately. Previous methodology relied either on handcrafted feature detectors or signal metrics which yield sub-optimal performance, or relied on machine learning techniques such as deep neural networks (DNN) which lack interpretability and are computationally and memory intensive. In this work, we present a novel method to learn a small set of interpretable convolutional kernels that has performance similar to -- and often better than -- the state-of-the-art DNN approach with several orders of magnitude fewer parameters. This work allows for efficient, robust, and interpretable signal quality assessment and artifact segmentation on low-power devices.Comment: 16 pages, 6 figure

Processing and analysis of multichannel extracellular neuronal signals: state-of-the-art and challenges

In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dys)functions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed). This poses an important and challenging problem of inferring conclusions from the large amounts of acquired data. Thus, automated signal processing and analysis tools are becoming a key component in neuroscience research, facilitating extraction of relevant information from neuronal recordings in a reasonable time. The purpose of this review is to introduce the reader to the current state-of-the-art of open-source packages for (semi)automated processing and analysis of multichannel extracellular neuronal signals (i.e., neuronal spikes, local field potentials, electroencephalogram, etc.), and the existing Neuroinformatics infrastructure for tool and data sharing. The review is concluded by pinpointing some major challenges that are being faced, which include the development of novel benchmarking techniques, cloud-based distributed processing and analysis tools, as well as defining novel means to share and standardize data

A low-noise transimpedance amplifier for BLM-based ion channel recording

High-throughput screening (HTS) using ion channel recording is a powerful drug discovery technique in pharmacology. Ion channel recording with planar bilayer lipid membranes (BLM) is scalable and has very high sensitivity. A HTS system based on BLM ion channel recording faces three main challenges: (i) design of scalable microfluidic devices; (ii) design of compact ultra-low-noise transimpedance amplifiers able to detect currents in the pA range with bandwidth >10 kHz; (iii) design of compact, robust and scalable systems that integrate these two elements. This paper presents a low-noise transimpedance amplifier with integrated A/D conversion realized in CMOS 0.35 µm technology. The CMOS amplifier acquires currents in the range ±200 pA and ±20 nA, with 100 kHz bandwidth while dissipating 41 mW. An integrated digital offset compensation loop balances any voltage offsets from Ag/AgCl electrodes. The measured open-input input-referred noise current is as low as 4 fA/Root Hz at ±200 pA range. The current amplifier is embedded in an integrated platform, together with a microfluidic device, for current recording from ion channels. Gramicidin-A, alpha-haemolysin and KcsA potassium channels have been used to prove both the platform and the current-to-digital converter

Detecting Soldiers' Fatigue Using Eye-Tracking Glasses: Practical Field Applications and Research Opportunities.

Objectively determining soldiers' fatigue levels could help prevent injuries or accidents resulting from inattention or decreased alertness. Eye-tracking technologies, such as optical eye tracking (OET) and electrooculography (EOG), are often used to monitor fatigue. Eyeblinks-especially blink frequency and blink duration-are known as easily observable and valid biomarkers of fatigue. Currently, various eye trackers (i.e., eye-tracking glasses) are available on the market using either OET or EOG technologies. These wearable eye trackers offer several advantages, including unobtrusive functionality, practicality, and low costs. However, several challenges and limitations must be considered when implementing these technologies in the field to monitor fatigue levels. This review investigates the feasibility of eye tracking in the field focusing on the practical applications in military operational environments.; This paper summarizes the existing literature about eyeblink dynamics and available wearable eye-tracking technologies, exposing challenges and limitations, as well as discussing practical recommendations on how to improve the feasibility of eye tracking in the field.; So far, no eye-tracking glasses can be recommended for use in a demanding work environment. First, eyeblink dynamics are influenced by multiple factors; therefore, environments, situations, and individual behavior must be taken into account. Second, the glasses' placement, sunlight, facial or body movements, vibrations, and sweat can drastically decrease measurement accuracy. The placement of the eye cameras for the OET and the placement of the electrodes for the EOG must be chosen consciously, the sampling rate must be minimal 200 Hz, and software and hardware must be robust to resist any factors influencing eye tracking.; Monitoring physiological and psychological readiness of soldiers, as well as other civil professionals that face higher risks when their attention is impaired or reduced, is necessary. However, improvements to eye-tracking devices' hardware, calibration method, sampling rate, and algorithm are needed in order to accurately monitor fatigue levels in the field