A Portable and a Scalable Multi-Channel Wireless Recording System for Wearable Electromyometrial Imaging.

Electromyometrial imaging (EMMI) technology has emerged as one of the promising technology that can be used for non-invasive pregnancy risk stratification and for preventing complications due to pre-term birth. Current EMMI systems are bulky and require a tethered connection to desktop instrumentation, as a result, the system cannot be used in non-clinical and ambulatory settings. In this article, we propose an approach for designing a scalable, portable wireless EMMI recording system that can be used for in-home and remote monitoring. The wearable system uses a non-equilibrium differential electrode multiplexing approach to enhance signal acquisition bandwidth and to reduce the artifacts due to electrode drifts, amplifier 1/f noise, and bio-potential amplifier saturation. A combination of active shielding, a passive filter network, and a high-end instrumentation amplifier ensures sufficient input dynamic range ([Formula: see text]) such that the system can simultaneously acquire different bio-potential signals like maternal electrocardiogram (ECG) in addition to the EMMI electromyogram (EMG) signals. We show that the switching artifacts and the channel cross-talk introduced due to non-equilibrium sampling can be reduced using a compensation technique. This enables the system to be potentially scaled to a large number of channels without significantly increasing the system power dissipation. We demonstrate the feasibility of the proposed approach in a clinical setting using an 8-channel battery-powered prototype which dissipates less than 8 µW per channel for a signal bandwidth of 1 KHz.

An adaptive synaptic array using Fowler-Nordheim dynamic analog memory.

In this paper we present an adaptive synaptic array that can be used to improve the energy-efficiency of training machine learning (ML) systems. The synaptic array comprises of an ensemble of analog memory elements, each of which is a micro-scale dynamical system in its own right, storing information in its temporal state trajectory. The state trajectories are then modulated by a system level learning algorithm such that the ensemble trajectory is guided towards the optimal solution. We show that the extrinsic energy required for state trajectory modulation can be matched to the dynamics of neural network learning which leads to a significant reduction in energy-dissipated for memory updates during ML training. Thus, the proposed synapse array could have significant implications in addressing the energy-efficiency imbalance between the training and the inference phases observed in artificial intelligence (AI) systems.

Stretchable Sponge Electrodes for Long-Term and Motion-Artifact-Tolerant Recording of High-Quality Electrophysiologic Signals.

Soft electronic devices and sensors have shown great potential for wearable and ambulatory electrophysiologic signal monitoring applications due to their light weight, ability to conform to human skin, and improved wearing comfort, and they may replace the conventional rigid electrodes and bulky recording devices widely used nowadays in clinical settings. Herein, we report an elastomeric sponge electrode that offers greatly reduced electrode-skin contact impedance, an improved signal-to-noise ratio (SNR), and is ideally suited for long-term and motion-artifact-tolerant recording of high-quality biopotential signals. The sponge electrode utilizes a porous polydimethylsiloxane sponge made from a sacrificial template of sugar cubes, and it is subsequently coated with a poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS) conductive polymer using a simple dip-coating process. The sponge electrode contains numerous micropores that greatly increase the skin-electrode contact area and help lower the contact impedance by a factor of 5.25 or 6.7 compared to planar PEDOT:PSS electrodes or gold-standard Ag/AgCl electrodes, respectively. The lowering of contact impedance resulted in high-quality electrocardiogram (ECG) and electromyogram (EMG) recordings with improved SNR. Furthermore, the porous structure also allows the sponge electrode to hold significantly more conductive gel compared to conventional planar electrodes, thereby allowing them to be used for long recording sessions with minimal signal degradation. The conductive gel absorbed into the micropores also serves as a buffer layer to help mitigate motion artifacts, which is crucial for recording on ambulatory patients. Lastly, to demonstrate its feasibility and potential for clinical usage, we have shown that the sponge electrode can be used to monitor uterine contraction activities from a patient in labor. With its low-cost fabrication, softness, and ability to record high SNR biopotential signals, the sponge electrode is a promising platform for long-term wearable health monitoring applications.

A self-powered analog sensor-data-logging device based on Fowler-Nordheim dynamical systems.

Continuous, battery-free operation of sensor nodes requires ultra-low-power sensing and data-logging techniques. Here we report that by directly coupling a sensor/transducer signal into globally asymptotically stable monotonic dynamical systems based on Fowler-Nordheim quantum tunneling, one can achieve self-powered sensing at an energy budget that is currently unachievable using conventional energy harvesting methods. The proposed device uses a differential architecture to compensate for environmental variations and the device can retain sensed information for durations ranging from hours to days. With a theoretical operating energy budget less than 10 attojoules, we demonstrate that when integrated with a miniature piezoelectric transducer the proposed sensor-data-logger can measure cumulative "action" due to ambient mechanical acceleration without any additional external power.

Exploiting Self-Capacitances for Wireless Power Transfer.

Conventional approaches for wireless power transfer rely on the mutual coupling (near-field or far-field) between the transmitter and receiver transducers. As a result, the power-transfer efficiency of these approaches scales non-linearly with the cross-sectional area of the transducers and with the relative distance and respective alignment between the transducers. In this paper, we show that when the operational power-budget requirements are in the order of microwatts, a self-capacitance (SC)-based power delivery has significant advantages in terms of the power transfer-efficiency, receiver form-factor, and system scalability when compared to other modes of wireless power transfer (WPT) methods. We present a simple and a tractable equivalent circuit model that can be used to study the effect of different parameters on the SC-based WPT. In this paper, we have experimentally verified the validity of the circuit using a cadaver mouse model. We also demonstrate the feasibility of a hybrid telemetry system where the microwatts of power, which can be harvested from SC-based WPT approach, is used for back-scattering a radio-frequency (RF) signal and is used for remote sensing of in vivo physiological parameters such as temperature. The functionality of the hybrid system has also been verified using a cadaver mouse model housed in a cage that was retrofitted with 915 MHz RF back-scattering antennas. We believe that the proposed remote power-delivery and hybrid telemetry approach would be useful in remote activation of wearable devices and in the design of energy-efficient animal cages used for long-term monitoring applications.

Local atmospheric response to warm mesoscale ocean eddies in the Kuroshio-Oyashio Confluence region.

In the extratropical regions, surface winds enhance upward heat release from the ocean to atmosphere, resulting in cold surface ocean: surface ocean temperature is negatively correlated with upward heat flux. However, in the western boundary currents and eddy-rich regions, the warmer surface waters compared to surrounding waters enhance upward heat release-a positive correlation between upward heat release and surface ocean temperature, implying that the ocean drives the atmosphere. The atmospheric response to warm mesoscale ocean eddies with a horizontal extent of a few hundred kilometers remains unclear because of a lack of observations. By conducting regional atmospheric model experiments, we show that, in the Kuroshio-Oyashio Confluence region, wintertime warm eddies heat the marine atmospheric boundary layer (MABL), and accelerate westerly winds in the near-surface atmosphere via the vertical mixing effect, leading to wind convergence around the eastern edge of eddies. The warm-eddy-induced convergence forms local ascending motion where convective precipitation is enhanced, providing diabatic heating to the atmosphere above MABL. Our results indicate that warm eddies affect not only near-surface atmosphere but also free atmosphere, and possibly synoptic atmospheric variability. A detailed understanding of warm eddy-atmosphere interaction is necessary to improve in weather and climate projections.

Monitoring of Postoperative Bone Healing Using Smart Trauma-Fixation Device With Integrated Self-Powered Piezo-Floating-Gate Sensors.

OBJECTIVE: Achieving better surgical outcomes in cases of traumatic bone fractures requires postoperative monitoring of changes in the growth and mechanical properties of the tissue and bones during the healing process. While current in-vivo imaging techniques can provide a snapshot of the extent of bone growth, it is unable to provide a history of the healing process, which is important if any corrective surgery is required. Monitoring the time evolution of in-vivo mechanical loads using existing technology is a challenge due to the need for continuous power while maintaining patient mobility and comfort. METHODS: This paper investigates the feasibility of self-powered monitoring of the bone-healing process using our previously reported piezo-floating-gate (PFG) sensors. The sensors are directly integrated with a fixation device and operate by harvesting energy from microscale strain variations in the fixation structure. RESULTS: We show that the sensors can record and store the statistics of the strain evolution during the healing process for offline retrieval and analysis. Additionally, we present measurement results using a biomechanical phantom comprising of a femur fracture fixation plate; bone healing is emulated by inserting different materials, with gradually increasing elastic moduli, inside a fracture gap. CONCLUSION: The PFG sensor can effectively sense, compute, and record continuously evolving statistics of mechanical loading over a typical healing period of a bone, and the statistics could be used to differentiate between different bone-healing conditions. SIGNIFICANCE: The proposed sensor presents a reliable objective technique to assess bone-healing progress and help decide on the removal time of the fixation device.

A simple precipitation method for measuring sialic acid in apolipoprotein B-containing lipoproteins in plasma.

BACKGROUND: A convenient method for the measurement of sialic acid in plasma apoB-containing lipoproteins is described. METHODS: Dextran sulphate-Mg(2+) precipitation and enzymatic sialic acid assay were combined and applied to analysis of plasma from 96 healthy controls and 136 hyperlipidaemic subjects of types IIa (n=46), IIb (n=43), and IV (n=47). RESULTS: The sialic acid concentrations (mean+/-SD) in plasma apoB-containing lipoproteins were 19.4+/-5.9, 24.3+/-4.7 (P<0.0001 versus normal), 23.0+/-4.7 (P<0.0001), 27.9+/-5.2 (P<0.0001), and 22.3+/-3.4 mg/L (P<0.002), for normal, all types of hyperlipidaemia, types IIa, IIb, and IV, respectively. The contents of sialic acid in apoB were 2.03+/-0.41%, 2.09+/-0.35% (no significance versus normal), 1.86+/-0.27% (P<0.0001), 1.97+/-0.26% (P<0.02), and 2.28+/-0.41% (P<0.002), for normal, all types of hyperlipidaemia, types IIa, IIb, and IV, respectively. CONCLUSION: The content of sialic acid in apoB decreased significantly in type IIa but increased in type IV hyperlipidaemia, which may reflect the presence of sialic acid in very low-density lipoprotein apolipoproteins other than apoB. This simple precipitation method will be useful to evaluate the sialic acid content in low-density lipoprotein in hyperlipidaemic subjects, especially of type IIa.

Self-powered monitoring of repeated head impacts using time-dilation energy measurement circuit.

Due to the current epidemic levels of sport-related concussions (SRC) in the U.S., there is a pressing need for technologies that can facilitate long-term and continuous monitoring of head impacts. Existing helmet-sensor technology is inconsistent, inaccurate, and is not economically or logistically practical for large-scale human studies. In this paper, we present the design of a miniature, battery-less, self-powered sensor that can be embedded inside sport helmets and can continuously monitor and store different spatial and temporal statistics of the helmet impacts. At the core of the proposed sensor is a novel time-dilation circuit that allows measurement of a wide-range of impact energies. In this paper an array of linear piezo-floating-gate (PFG) injectors has been used for self-powered sensing and storage of linear and rotational head-impact statistics. The stored statistics are then retrieved using a plug-and-play reader and has been used for offline data analysis. We report simulation and measurement results validating the functionality of the time-dilation circuit for different levels of impact energies. Also, using prototypes of linear PFG integrated circuits fabricated in a 0.5 µm CMOS process, we demonstrate the functionality of the proposed helmet-sensors using controlled drop tests.

Exploiting jump-resonance hysteresis in silicon auditory front-ends for extracting speaker discriminative formant trajectories.

Jump-resonance is a phenomenon observed in non-linear circuits where the amplitude of the output signal exhibits an abrupt jump when the frequency of the input signal is varied. For [Formula: see text] filters used in the design of analog auditory front-ends (AFEs), jump-resonance is generally considered to be undesirable and several techniques have been proposed in literature to avoid or alleviate this artifact. In this paper we explore the use of jump-resonance based hysteresis in [Formula: see text] band-pass filters for encoding speech formant trajectories. Using prototypes of silicon AFEs fabricated in a 0.5 µm CMOS process, we demonstrate the benefits of the proposed approach for extracting speaker discriminative features. These benefits are validated using speaker recognition experiments where consistent improvements in equal-error-rates (EERs) are achieved using the jump-resonance based features as compared to conventional features.

Noise-shaping gradient descent-based online adaptation algorithms for digital calibration of analog circuits.

Analog circuits that are calibrated using digital-to-analog converters (DACs) use a digital signal processor-based algorithm for real-time adaptation and programming of system parameters. In this paper, we first show that this conventional framework for adaptation yields suboptimal calibration properties because of artifacts introduced by quantization noise. We then propose a novel online stochastic optimization algorithm called noise-shaping or ΣΔ gradient descent, which can shape the quantization noise out of the frequency regions spanning the parameter adaptation trajectories. As a result, the proposed algorithms demonstrate superior parameter search properties compared to floating-point gradient methods and better convergence properties than conventional quantized gradient-methods. In the second part of this paper, we apply the ΣΔ gradient descent algorithm to two examples of real-time digital calibration: 1) balancing and tracking of bias currents, and 2) frequency calibration of a band-pass Gm-C biquad filter biased in weak inversion. For each of these examples, the circuits have been prototyped in a 0.5-µm complementary metal-oxide-semiconductor process, and we demonstrate that the proposed algorithm is able to find the optimal solution even in the presence of spurious local minima, which are introduced by the nonlinear and non-monotonic response of calibration DACs.