Reliable Signal Acquisition Research Articles

A MOFs‐Derived Hydroxyl‐Functionalized Hybrid Nanoporous Carbon Incorporated Laser‐Scribed Graphene‐Based Multimodal Skin Patch for Perspiration Analysis and Electrocardiogram Monitoring

AbstractAlthough metal‐organic framework (MOF)‐derived nanoporous C (NPC) materials offer several advantages for electrochemical sensor applications, surface functionalization and porosity tuning can affect sensor performance. This study presents the development of a skin patch for perspiration and electrocardiogram (ECG) monitoring, leveraging the unique properties of MOF‐on‐MOF‐derived surface‐functionalized hybrid nanoporous C (f‐HNPC) incorporated into laser‐scribed graphene (LSG). Hydroxyl (OH) group‐functionalized NPC, achieved through KOH activation, facilitates electron transport at the electrode–electrolyte interface. This enhances the electrochemical activity, thereby improving sensor sensitivity and expanding the detection range. The integration of f‐HNPC provides enhanced surface area and electrochemical properties, enabling sensitive and selective detection of sweat biomarkers, including glucose (103 µA mM−1 cm−2) and uric acid (184 µA mM−1 cm−2) along with an ultra‐wide glucose detection range (up to 41.5 mM). Moreover, the incorporation of LSG ensures excellent mechanical flexibility, facilitating conformal contact with the skin for reliable signal acquisition. The proposed skin patch demonstrates promising performance in real‐time perspiration analysis and ECG monitoring with a signal‐to‐noise ratio of 23.63 dB, along with high stability and long‐term durability. The synergistic combination of f‐HNPC and LSG shows great potential for developing advanced wearable biosensing platforms for personalized healthcare applications.

Physiological sensing system integrated with vibration sensor and frequency gel dampers inspired by spider.

Recent advances in bioelectronics in mechanical and electrophysiological signal detection are remarkable, but there are still limitations because they are inevitably affected by environmental noise and motion artifacts. Thus, we develop a gel damper-integrated crack sensor inspired by the vibration response of the viscoelastic cuticular pad and slit organs in a spider. Benefitting from the specific crack structure design, the sensor possesses excellent sensing behaviors, including a low detection limit (0.05% strain), ultrafast response ability (3.4 ms) and superior durability (>300 000 cycles). Such typical low-amplitude fast response properties allow the ability to accurately perceive vibration frequency and waveform. In addition, the gel damper exhibits frequency-dependent dynamic mechanical behavior that results in improved stability and reliability of signal acquisition by providing shock resistance and isolating external factors. They effectively attenuate external motion artifacts and low-frequency mechanical noise, resulting in cleaner and more reliable signal acquisition. When the gel damper is combined with the crack-based vibration sensor, the integrated sensor exhibits superior anti-interference capability and frequency selectivity, demonstrating its effectiveness in extracting genuine vocal vibration signals from raw voice recordings. The integration of damping materials with sensors offers an efficient approach to improving signal acquisition and signal quality in various applications.

Adhesive, multifunctional, and wearable electronics based on MXene-coated textile for personal heating systems, electromagnetic interference shielding, and pressure sensing.

Adhesion between flexible devices and skin surface facilitates portability of devices and reliable signal acquisition from human body, which is essential for medical therapy devices or monitoring systems. Here, we utilize a simple, cost-effective, and scalable layer-by-layer dip-coating method to fabricate a skin-adhesive multifunctional textile-based device, consisting of three parts: low-cost and easily available airlaid paper (AP) substrate, conductive MXene sensitive layer, and adhesive polydimethylsiloxane (PDMS). The adhesive layer of lightly cross-linked PDMS enables the device to form conformal contact with skin even during human joint bending. The smart textile device exhibits excellent electro-thermal and photo-thermal conversion performance with good cycling stability and tunability. Furthermore, the textile electronics show good electromagnetic interference (EMI) shielding properties due to the good electrical conductivity, as well as sensitive and stable pressure sensing properties for human motion detection. Consequently, this efficient strategy provides a possible way to design multifunctional and wearable electronic textiles for medical applications.

Randomized Spectral Separation Coefficient for Short Code Acquisition Performance Evaluation

Reliable signal acquisition with low computational complexity is an important design objective for the evolution of global navigation satellite systems (GNSS). Most GNSS signals consist of long pseudorandom noise (PRN) codes whose acquisition is expensive in terms of memory, computation time, and energy. As these resources are particularly scarce in the emerging mass-market user segment, cyclostationary pilot signals with short PRN codes are an attractive option to keep the number of acquisition search bins low. However, reducing the code length degrades the acquisition performance, as multiple access interference (MAI) becomes more pronounced and can lead to an increased false alarm rate. We demonstrate that, quite different from stationary MAI, cyclostationary MAI does not affect each bin of the search space uniformly, and is therefore not easily modeled with the well-known spectral separation coefficient (SSC). We propose a new randomized SSC (SSC-R) based on code/Doppler interference functions, which can be used for simple and accurate acquisition performance evaluation. As an application example, we demonstrate how the SSC-R can be utilized in signal design to minimize the PRN code length under an acquisition performance constraint. We conclude that feasible PRN code lengths for GNSS can be on the order of 300-700.

In Vivo Evaluation of a Subcutaneously Injectable Implant with a Low-Power Photoplethysmography ASIC for Animal Monitoring.

Photoplethysmography is an extensively-used, portable, and noninvasive technique for measuring vital parameters such as heart rate, respiration rate, and blood pressure. The deployment of this technology in veterinary medicine has been hindered by the challenges in effective transmission of light presented by the thick layer of skin and fur of the animal. We propose an injectable capsule system to circumvent these limitations by accessing the subcutaneous tissue to enable reliable signal acquisition even with lower light brightness. In addition to the reduction of power usage, the injection of the capsule offers a less invasive alternative to surgical implantation. Our current prototype combines two application-specific integrated circuits (ASICs) with a microcontroller and interfaces with a commercial light emitting diode (LED) and photodetector pair. These ASICs implement a signal-conditioning analog front end circuit and a frequency-shift keying (FSK) transmitter respectively. The small footprint of the ASICs is the key in the integration of the complete system inside a 40-mm long glass tube with an inner diameter of 4 mm, which enables its injection using a custom syringe similar to the ones used with microchip implants for animal identification. The recorded data is transferred wirelessly to a computer for post-processing by means of the integrated FSK transmitter and a software-defined radio. Our optimized LED duty cycle of 0.4% at a sampling rate of 200 Hz minimizes the contribution of the LED driver (only 0.8 mW including the front-end circuitry) to the total power consumption of the system. This will allow longer recording periods between the charging cycles of the batteries, which is critical given the very limited space inside the capsule. In this work, we demonstrate the wireless operation of the injectable system with a human subject holding the sensor between the fingers and the in vivo functionality of the subcutaneous sensing on a pilot study performed on anesthetized rat subjects.

Carotid Local Pulse Wave Velocity Measurement using Dual- Element Accelerometric Patch Probe.

In this work, we demonstrate an accelerometric patch probe with two microelectromechanical accelerometer sensors for local pulse wave velocity (PWV) measurement from the carotid artery. Dual acceleration plethysmogram (APG) signals were acquired from a small section of the artery by keeping the sensors at 32 mm apart. A custom analog front-end circuit (inter-channel delay $< 0.15$ ms) was used for reliable signal acquisition. Simultaneously acquired dual APG signals were processed in real-time and local PWV was evaluated in a beat-by-beat manner. A transversal study on a cohort of 15 volunteers (4 males, 11 females, mean age = $25.6 \pm 1.92$ years) was conducted to validate the developed prototype system. During the study, carotid local PWV and brachial blood pressure (BP) parameters were recorded from both sitting and standing posture. The absolute values of measured carotid local PWV were in the range of 3 m/s - 4.2 m/s (beat-to-beat variation $=$ 2.61% - 13.07%). Measured local PWV values significantly correlated with brachial systolic BP ($\textbf{R}^{\mathbf {2}} =$ 0.87) and diastolic BP ($\textbf{R}_{\mathbf {\, }}^{\mathbf {2}} \quad =$ 0.79). Logarithmic functions provided the best monotonic model for carotid local PWV versus brachial BP parameters for the recorded data points. The developed population-specific mathematical models were then used for cuffless evaluation of BP parameters from carotid local PWV. The root-mean-square error in the estimated systolic and diastolic pressure was 7.53 mmHg and 6.0 mmHg respectively. Study results illustrate the potential application of the developed dual-accelerometric system in non-invasive, continuous cuffless BP measurement techniques.

Objective-lens-free Fiber-based Position Detection with Nanometer Resolution in a Fiber Optical Trapping System

Position detection with high accuracy is crucial for force calibration of optical trapping systems. Most existing position detection methods require high-numerical-aperture objective lenses, which are bulky, expensive, and difficult to miniaturize. Here, we report an affordable objective-lens-free, fiber-based position detection scheme with 2 nm spatial resolution and 150 MHz bandwidth. This fiber based detection mechanism enables simultaneous trapping and force measurements in a compact fiber optical tweezers system. In addition, we achieved more reliable signal acquisition with less distortion compared with objective based position detection methods, thanks to the light guiding in optical fibers and small distance between the fiber tips and trapped particle. As a demonstration of the fiber based detection, we used the fiber optical tweezers to apply a force on a cell membrane and simultaneously measure the cellular response.

The Feasibility of Flat, Portable and Wireless Device for Non-Invasive Peripheral Oxygenation Measurement over the Entire Body

Peripheral oxygenation level (SpO2) can provide vital information on body functions. Continuous monitoring facilitates effective diagnosis and treatment and can even be lifesaving. Clinical device monitor SpO2 using a clip, and measure light transmission through the tissue. This method limits the body locations of the clip’s placement and is sensitive to body movement, which hampers continuous SpO2 monitoring during wakefulness or sleep, thus decreasing its usability in clinics and its accessibility in homecare usage. We developed a portable, wireless, flat and low cost prototype for continuous monitoring of SpO2 that overcomes those limitations. The prototype enables convenient measurement in larger variety of body locations by spectrophotometric measurements of changes in the optical reflectance unlike other device that measure absorption through the tissue. The original design and signal processing enable reliable signal acquisition, synchronization and control. An Android’s application was developed to provide a user friendly interface for results display on smartphones. The prototype’s measurements were compared to commercial device that simultaneously measured heart rate frequency, transcutaneous oxygen tension (tcPO2) and SpO2. The prototype’s measurements accurately reflected changes caused by blood pulses, were correlated to the heart rate, and were sensitive to changes in oxygen saturation. Excellent real time behavior and synchronization were demonstrated between the hardware and smartphone software. Our prototype thus enables convenient SpO2 measurement over the entire body, while maintaining accuracy comparable to commercial device. Its smartphone application enables accessible and understandable results display to patients, care-givers and healthcare professionals. The application’s display and alert calibration flexibility facilitates the prototype’s usage in changing medical requirements and for various disease and conditions. A device based on this prototype can monitor continuously and accurately patients’ SpO2 without limiting their everyday activities or disturbing their sleep and can thus significantly im-prove their medical care in both clinics and home.

A Multistage Architecture for Statistical Inference with Stochastic Signal Acquisition

We describe a statistical inference approach for designing signal acquisition interfaces and inference systems with stochastic devices. A signal is observed by an array of binary comparison sensors, such as highly scaled comparators in an analog-to-digital converter, that exhibit random offsets in their reference levels due to process variations or other uncertainties. These offsets can limit the performance of conventional measurement devices. In our approach, we build redundancy into the sensor array and use statistical estimation techniques to account for uncertainty in the observations and produce a more reliable estimate of the acquired signal. We develop an observational model and find a Cramer-Rao lower bound on the achievable square error performance of such a system. We then propose a two-stage inference architecture that uses a coarse estimate to select a subset of the sensor outputs for further processing, reducing the overall complexity of the system while achieving near-optimal performance. The performance of the architecture is demonstrated using a simulated prototype for parameter estimation and symbol detection applications. The results suggest the feasibility of using unreliable components to build reliable signal acquisition and inference systems.

Design of Sensor-Tag Using Radio Frequency Power to Energize and its Research on Structural Health Monitoring

A new method of structural health monitoring based on sensor-tags using radio frequency power to energize node wirelessly is proposed. A modular RFID sensor-tag, which has the function of signal conditioning, energy harvesting, and wireless transmission, is designed for some sensing elements commonly used in structural health monitoring, such as resistance strain gauges, piezoelectric ceramic and shape memory alloy (SMA). Sensor-tags receive energy which is the feedback of reader antenna coupling and provide power for sensor nodes. It overcomes defects of wireless sensor network (WSN) powered by battery, such as weak capabilities of processing, storage and communication. Stretching, bending and impact tests show that the system can achieve reliable signal acquisition and wireless transmission, the wireless communication distance between tag and reader is up to 128 meters, bit error rate of signal transmission 2 %.

Time and Frequency Synchronization for Multicarrier Transmission on Hexagonal Time-Frequency Lattice

In this paper, a novel synchronization acquisition approach, including preamble structure, time and frequency synchronization algorithms, is proposed for hexagonal multicarrier transmission (HMCT) system. Specifically, a novel signal acquisition scheme based on time-frequency subspace projection (TFSP) and its simplified form are proposed for reliable signal acquisition. Time and frequency synchronization is divided into three steps: 1) the coarse time offset (TO) and coarse fractional carrier frequency offset (CFO) estimation; 2) fine TO and integer CFO estimation; and 3) fine fractional CFO estimation. The closed-form Cramér-Rao lower bound of the proposed CFO estimation scheme is given. Theoretical analyses and simulation results show that the proposed preamble structure, time and frequency synchronization algorithms for HMCT system can obtain robust performance over doubly dispersive (DD) channel, and the simulation results show excellent agreement with theoretical analyses.

Designment and Implementation on Bullet-Data-Acquisition System

Measurement of bullet data is very important to the target trial. The reliable signal acquisition and analysis is the bases of the design of weapon. When the ordinary photoelectric target work, firelight or ambient light will bring an error trigger signal or cannot capture the shot off target signal. These may affect accuracy and sensitivity of the system. A system of the data acquisition and process based on PCI local bus is introduced in this paper. The device of hardware and data acquisition base on PCI local bus is in detail. Introduce how to design the PCI driver. This system has been successfully used to measure several kinds of projectiles’ velocity.

A Rapid and Reliable Signal Acquisition Scheme for Indoor UWB Systems

We propose a rapid and reliable signal acquisition scheme for UWB (Ultra Wide Band) systems in indoor wireless environments. The proposed scheme is a two-step search with different thresholds and search windows, where each step utilizes the single-dwell search with the bit reversal. Simulation results show that the proposed scheme for the UWB signals can achieve significant reduction of the required mean acquisition time as compared to other schemes including general double-dwell search scheme for various threshold levels. Furthermore, it is also observed that the proposed scheme can achieve much faster and reliable signal acquisition as the first threshold is larger in noisy environments.

Neuro-fuzzy closed-loop control of depth of anaesthesia

The utility of the auditory evoked potential (AEP) is under investigation as a feedback signal for the automatic closed-loop control of general anaesthesia using neural networks and fuzzy logic. The AEP is a signal derived from the electroencephalogram (EEG) in response to auditory stimulation, which may be useful as an index of the ‘depth’ of anaesthesia. A simple back-propagation neural network can learn the AEP and provides a satisfactory input to a fuzzy logic infusion controller for the administration of anaesthetic drugs, but the problem remains that of reliable signal acquisition.