The distinct and potentially conflicting effects of tDCS and tRNS on brain connectivity, cortical inhibition, and visuospatial memory.

Noninvasive brain stimulation (NIBS) techniques, including transcranial direct current stimulation (tDCS) and transcranial random noise stimulation (tRNS), are emerging as promising tools for enhancing cognitive functions by modulating brain activity and enhancing cognitive functions. Despite their potential, the specific and combined effects of tDCS and tRNS on brain functions, especially regarding functional connectivity, cortical inhibition, and memory performance, are not well-understood. This study aims to explore the distinct and combined impacts of tDCS and tRNS on these neural and cognitive parameters. Using a within-subject design, ten participants underwent four stimulation conditions: sham, tDCS, tRNS, and combined tDCS + tRNS. We assessed the impact on resting-state functional connectivity, cortical inhibition via Cortical Silent Period (CSP), and visuospatial memory performance using the Corsi Block-tapping Test (CBT). Our results indicate that while tDCS appears to induce brain lateralization, tRNS has more generalized and dispersive effects. Interestingly, the combined application of tDCS and tRNS did not amplify these effects but rather suggested a non-synergistic interaction, possibly due to divergent mechanistic pathways, as observed across fMRI, CSP, and CBT measures. These findings illuminate the complex interplay between tDCS and tRNS, highlighting their non-additive effects when used concurrently and underscoring the necessity for further research to optimize their application for cognitive enhancement.

Charge-mode Neural Stimulator with a Capacitor-reuse Residual Charge Detector and Active Charge Balancing for Epileptic Seizure Suppression.

This study proposes a charge-mode neural stimulator for electrical stimulation systems that utilizes a capacitor-reuse technique with a residual charge detector and achieves active charge balancing simultaneously. The design is mainly used for epilepsy suppression systems to achieve real-time symptom relief during seizures. A charge-mode stimulator is adopted in consideration of the complexity of circuit design, the high voltage tolerance of transistors, and system integration requirements in the future. The residual charge detector allows users to understand the current stimulus situation, enabling them to make optimal adjustments to the stimulation parameters. On the basis of the information on actual stimulation charge, active charge balancing can effectively prevent the accumulation of mismatched charges on electrode impedance. The capacitor- and phase-reuse techniques help realize high integration of the overall stimulator circuit in consideration of the commonality of the use of a capacitor and charging/discharging phase in the stimulation circuit and charge detector. The proposed charge-mode neural stimulator is implemented in a TSMC 0.18 µm 1P6M CMOS process with a core area of 0.2127 mm2. Measurement results demonstrate the accuracy of the stimulation's functionality and the programmable stimulus parameters. The effectiveness of the proposed charge-mode neural stimulator for epileptic seizure suppression is verified through animal experiments.

A Direct Current-Sensing VCO-Based 2nd-Order Continuous-Time Sigma-Delta Modulator for Biosensor Readout Applications.

A second-order voltage-controlled oscillator (VCO)-based continuous-time sigma-delta modulator (CTSDM) for current-sensing readout applications is proposed. Current signals from the sensor can directly be quantized by the proposed VCO-based CTSDM, which does not require any extra trans-impedance amplifiers. With the proportional-integral (PI) structure and a VCO phase integrator, the capability of second-order noise shaping is available to reduce the in-band quantization noise. The PI structure can be simply realized by a resistor in series with the integrating capacitor, which can reduce the architecture complexity and maintain the stability of the system. The current-steering digital-to-analog converter with tail and sink current sources is used on the feedback path for the subtraction of the current-type input signal. All the components of the circuit are scaling friendly and applicable to current-sensing readout applications in the Internet of Things (IoT). The proposed VCO-based CTSDM implemented in a 0.18-µm standard CMOS process has a measured signal-to-noise and distortion ratio (SNDR) of 74.6 dB at 10 kHz bandwidth and consumes 44.8 µw only under a supply voltage of 1.2 V, which can achieve a Figure-of-Merit (FoM) of 160.76 dB.

The Ratio of Urine N-Terminal Pro B-Type Natriuretic Peptide to Cyclic Guanosine Monophosphate Predicts Emergency Department Visits for Heart Failure.

INTRODUCTION: Emergency department (ED) visits for decompensated heart failure (HF) are frequent and associated with poor long-term outcomes. Plasma N-terminal pro B-type natriuretic peptide (NT-proBNP) and cyclic guanosine monophosphate (cGMP) are used in diagnosis and prognosis of HF patients, while clinical values of urine NT-proBNP/cGMP ratio have been rarely explored. This study aims to compare the predictive values of urine NT-proBNP/cGMP ratio versus plasma NT-proBNP for ED visits for decompensated HF. METHODS: This prospective study included 126 HF patients with reduced left ventricular ejection fraction (<50%) and without chronic kidney disease. Baseline data included demographics, co-morbidities, and co-medications. Medical records were used to determine the incidence of ED visits for decompensated HF during the 3 months following the last visit. RESULTS: Patients with subsequent ED visits had significantly higher levels of plasma and urine NT-proBNP and urine cGMP in than those without. Multivariate Cox regression analysis disclosed that Lg10urine NT-proBNP/cGMP was an independent risk factor for subsequent ED visits (OR = 3.267; 95% CI: 1.105-9.663; p = 0.032). ROC analysis revealed an Lg10urine NT-proBNP/cGMP ratio optimal cut-off value of 0.1706 (AUC, 0.700; 95% CI: 0.543-0.857; p = 0.036) for predicting subsequent HF-related ED visits. CONCLUSION: A single measurement of urinary NT-proBNP/cGMP ratio is predictive of subsequent ED visits for decompensated HF. This noninvasive and easy measurement may be a clinically useful tool for identifying a subset of patients at higher risk of ED visits.

A 0.8-µW and 74-dB High-Pass Sigma-Delta Modulator With OPAMP Sharing and Noise-Coupling Techniques for Biomedical Signal Acquisition.

This work presents a third-order high-pass sigma-delta modulator (HPSDM) for biomedical signal acquisition. The operational amplifier (op-amp) sharing and noise-coupling techniques are adopted to reduce the required quantity of op-amps and add a noise-shaping order, which can achieve low power consumption and high resolution. A novel switched-capacitor architecture is proposed to suppress the increasing in-band noise and alleviate the circuit sensitivity to capacitor mismatch in the high-pass integrator. The proposed HPSDM was fabricated in a 0.18-µm standard CMOS process. Measurement results reveal that the proposed HPSDM has a signal-to-noise and distortion ratio (SNDR) of 75.26/74 dB in 200 Hz bandwidth and consumes 1.52/0.8 µW under 1.2/1 V supply voltage, which can achieve a peak Schreier Figure-of-Merit of 156.45/157.98 dB and a peak Walden FoM of 0.802/0.488 pJ/conv.

A Portable Wireless Urine Detection System With Power-Efficient Electrochemical Readout ASIC and ABTS-CNT Biosensor for UACR Detection.

This work presents a portable wireless urine detection system which consists of an electrochemical readout application specific integrated circuit (ASIC) and a biosensor composed of 2, 2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) and carbon nanotube (ABTS-CNT) for the detection of urine albumin-to-creatinine ratio (UACR). The ASIC includes a potentiostat, a digital circuitry and a power management circuit which can perform electrochemistry techniques with a dual-channel screen-printing carbon electrode (SPCE). Electrochemical experiments on the proposed biosensor (SPCE|ABTS-CNT|Nafion) have revealed promising sensing characteristics for creatinine and human serum albumin detection. Practical urine tests has demonstrated the capability of the proposed urine detection system for UACR detection with both the power-efficient readout ASIC and the ABTS-CNT biosensor. A user-friendly prototype has also been designed which can be useful for either personal health administrationor homecare.

RISC-V CNN Coprocessor for Real-Time Epilepsy Detection in Wearable Application.

Epilepsy is a common clinical disease. Severe epilepsy can be life-threatening in certain unexpected conditions, so it is important to detect seizures instantly with a wearable device and to provide treatment within the golden window. The observation of the electroencephalography (EEG) signal is an imperative method to assist correct epilepsy diagnosis. To detect and classify EEG signals, a convolutional neural network (CNN) is an intuitive and appropriate method that borrows expertise from neurologists. However, the computational cost of training and inference on artificial intelligence (AI)-based solutions make software-only and hardware-only solutions incompetent for real-time monitoring on embedded devices. Hence, this study proposes three key contributions for the challenge, namely, an algorithm framework to provide real-time epilepsy detection, a dedicated coprocessor chip implementing this framework to enable real time epilepsy detection to offload and accelerate detection algorithm, and a custom interface with the coprocessor and reduced instruction set computer-V (RISC-V) instructions to reconfigure the coprocessor and transfer data. The epilepsy detection framework is implemented in 11-layer CNN. The proposed epilepsy detection algorithm performs 97.8% accuracy for floating-point and 93.5% for fixed-point operations through animal experiments with lab rats. The RISC-V CNN coprocessor is fabricated in the TSMC 0.18-µm CMOS process. For each classification, the coprocessor consumes 51 nJ/class. and 0.9 µJ/class. energy on data transfer and inference, respectively. The detection latency on the chip is 0.012 s. With the integration of the hardware coprocessor, AI algorithms can be applied to epilepsy detection for real-time monitoring.

High-Pass Sigma-Delta Modulator With Techniques of Operational Amplifier Sharing and Programmable Feedforward Coefficients for ECG Signal Acquisition.

A high-pass sigma-delta modulator (HPSDM) is proposed for electrocardiography (ECG) signal acquisition system. The HPSDM is implemented using operational amplifier (op-amp) sharing and programmable feedforward coefficients. The op-amp sharing is adopted to reduce the quantity of amplifiers because they dominate the power consumption of the HPSDM. In addition, given that the magnitude of the ECG is dependent on different persons, programmable feedforward coefficients are utilized to extend the dynamic range of the HPSDM to fit the actual application. The proposed HPSDM is fabricated in a 0.18-µm standard CMOS process. Measurement results reveal that the proposed HPSDM has a signal-to-noise and distortion ratio (SNDR) of 54.5 dB and a power consumption of 2.25 µW under a 1.2 V supply voltage and achieves a figure of merit (FoM) of 12.96 pJ/conv. Moreover, the proposed HPSDM has an SNDR of 64.8 dB and a power consumption of 5.2 µW under a 1.8 V supply voltage and achieves a FoM of 9.15 pJ/conv due to the op-amp sharing technique. Under the 1.2 V and 1.8 V supply voltages, the dynamic range of the HPSDM is extended to approximately 12 dB due to the technique of programmable feedforward coefficients.

Urine High-Sensitivity Troponin I Predict Incident Cardiovascular Events in Patients with Diabetes Mellitus.

In patients with diabetes mellitus (DM), incident cardiovascular (CV) events are associated with poor long-term outcomes. Serum high-sensitivity troponin I (hs-TnI) is widely used to diagnose and predict outcomes in patients with acute coronary syndrome, however, few studies have investigated the accuracy of urine hs-TnI as a predictor for incident CV events in patients with DM. The enrolled participants included patients with DM. Fresh urine hs-TnI levels were measured. Medical records of enrolled patients were used to determine the number of incident CV events prospectively for 3 months. The study cohort comprised 378 participants. We observed significantly higher levels of urine hs-TnI in those with than without subsequent incident CV events. The multivariate logistic regression analysis using different models consistently showed that urine hs-TnI > 4.10 pg/mL was an independent factor predictive of incident CV events. The ROC-AUC analysis revealed that the optimal cutoff value for urine hs-TnI for predicting incident CV events was 1.55 pg/mL and the area was 0.611 (p = 0.027). A single measurement of urinary hs-TnI, collected easily and non-invasively, may be an acceptable biomarker for predicting subsequent incident CV events in patients with DM.

Urine N-terminal pro b-type natriuretic peptide is predictive of heart failure-related emergency department visits.

AIMS: Emergency department (ED) visits for decompensated heart failure (HF) are frequent and associated with poor long-term outcomes in patients with HF. Serum N-terminal pro b-type natriuretic peptide (NT-proBNP) is widely used to assist diagnosis and predict clinical outcomes in HF patients. Few studies have investigated the use of urine NT-proBNP as an HF biomarker. This study aims to assess the value of urine NT-proBNP for predicting ED visits for decompensated HF as compared with that of serum NT-proBNP. METHODS AND RESULTS: This study included 122 HF patients with reduced left ventricular ejection fraction (<50%). Serum and urine NT-proBNP levels were measured. Baseline data included demographics, comorbidities, and co-medications. Medical records were used to determine the incidence of visits to the ED for decompensated HF during the 3 months following the last visit. We observed significantly higher levels of both serum and urine NT-proBNP in patients with subsequent ED visits than in those without. Multivariate logistic regression analysis showed that urine NT-proBNP/creatinine ratio (OR, 1.031; 95% CI, 1.001-1.061; P = 0.046) but not serum NT-proBNP was an independent factor associated with subsequent ED visits. According to receiver-operating characteristic-area under the curve analysis, the optimal cut-off value of urine NT-proBNP/creatinine ratio for predicting subsequent heart-failure related ED visits was 0.272 pg/µg Cr (area under the curve, 0.675; P = 0.011). CONCLUSIONS: For HF patients with reduced left ventricular ejection fraction, a single measurement of urinary NT-proBNP/creatinine ratio is predictive of subsequent ED visits for decompensated HF. This non-invasive and easy measurement may be a clinically useful tool for monitoring clinical outcomes and identifying a subset of patients at higher risk of ED visits within a short time.

A 2.4 GHz ISM Band OOK Transceiver With High Energy Efficiency for Biomedical Implantable Applications.

This article presents a high energy efficiency, high-integrated, and low-power on-off keying transceiver for a 2.4 GHz industrial scientific medical band. The proposed receiver includes an input matching network, a low-noise amplifier, a novel single-to-differential envelope detector, a level shifter, cascaded baseband amplifiers, and a hysteresis comparator. The proposed transmitter includes a bias-stimulating circuit, a current-reused self-mixing voltage controlled oscillator, and a quadruple-transconductance power amplifier. Numerous proposed techniques implemented in the mentioned circuits improve the energy per bit and power efficiency. Therefore, the proposed receiver for short-distanced propagation can achieve a sensitivity of -46 dBm with a carrier frequency of 2.45 GHz and a high data rate of 2 Mbps. The proposed transmitter achieves an output power of -17 dBm with a high data rate of 20 Mbps. This work is fabricated in a TSMC 0.18 µm CMOS process and consumes 160 µW and 0.6 mW in the receiver and transmitter, respectively, from a 1.2 V supply voltage. The energy per bit of 80 pJ/bit in the receiver part and the figure of merit of 9 in the transmitter part are better than those of existing state-of-the-art transceivers.

Electrocardiogram and Phonocardiogram Monitoring System for Cardiac Auscultation.

Heart-sound auscultation is a rapid and fundamental technique used for examining the cardiovascular system. The main components of heart sounds are the first and second heart sounds. Discriminating these heart sounds under the presence of additional heart sounds and murmurs will be difficult. To recognize these signals efficiently, this study proposes a monitoring system with phonocardiogram and electrocardiogram. This system has two key points. The first is chip implementation, including capacitor coupled amplifier, transimpedance amplifier, high-pass sigma-delta modulator, and digital signal processing block. The chip in the system is fabricated in 0.18 µm standard complementary metal-oxide-semiconductor process. The second is a software application on smartphones for heart-related physiological signal recording, display, and identification. A wavelet-based QRS complex detection algorithm verified by MIT/BIH Arrhythmia Database is also proposed. The overall measured positive prediction, sensitivity, and error rate of the proposed algorithm are 99.90%, 99.82%, and 0.28%, respectively. During auscultation, doctors may refer to these physiological signals displayed on the smartphone and simultaneously listen to the heart sounds to diagnose the potential heart disease. By taking advantage of signal visualization and keeping the original diagnosis procedure, the uncertainty existing in heart sounds can be eliminated, and the training period to acquire auscultation skills can be reduced.

Low-Voltage OTA-C Filter With an Area- and Power-Efficient OTA for Biosignal Sensor Applications.

This paper presents a systematic method for decreasing the amount of transconductors used by an operational transconductance amplifier-capacitor (OTA-C) filter to decrease the power consumption and the active area. An OTA with a local-feedback linearized technique and a transconductance booster is proposed based on the presented method. The proposed OTA combines current division with source degeneration to enhance linearity and implement low transconductance. This topology enables the proposed OTA to drive multiple integration capacitors without an additional output stage. The OTA-based circuit realizes low power consumption by operating under a weak inversion at a supply voltage of 1 V. Thus, a fifth-order ladder-type low-pass Butterworth OTA-C filter is implemented for the acquisition of electrocardiograph signals. The proposed method is validated using a prototype fabricated through a 1P6M 0.18-µm CMOS process. Results show that in ECG signal acquisition, the proposed filter has a signal bandwidth located within 250 Hz, a dynamic range of 61.2 dB, and a power consumption of 41 nW to achieve a figure-of-merit of 5.4 × 10-13. The active area of the filter is 0.24 mm2.

A 2.5 mW/ch, 50 Mcps, 10-Analog Channel, Adaptively Biased Read-Out Front-End IC With Low Intrinsic Timing Resolution for Single-Photon Time-of-Flight PET Applications With Time-Dependent Noise Analysis in 90 nm CMOS.

This paper presents a 10-channel time-of-flight application-specific integrated circuit (ASIC) for positron emission tomography in a 90 nm standard CMOS process. To overcome variations in channel-to-channel timing resolution caused by mismatch and process variations, adaptive biases and a digital-to-analog converter (DAC) are utilized. The main contributions of this work are as follows. First, multistage architectures reduce the total power consumption, and detection bandwidths of analog preamplifiers and comparators are increased to 1 and 1.5 GHz, respectively, relative to those in previous studies. Second, a total intrinsic electronic timing resolution of 9.71 ps root-mean-square (RMS) is achieved (13.88 ps peak and 11.8 ps average of the 10 channels in 5 ASICs). Third, the proposed architecture reduces variations in channel-to-channel timing resolution to 2.6 bits (equivalent to 4.17 ps RMS) by calibrating analog comparator threshold levels. A 181.5 ps full-width-at-half-maximum timing resolution is measured with an avalanche photo diode and a laser setup. The power consumption is 2.5 mW using 0.5 and 1.2 V power supplies. The proposed ASIC is implemented in a 90 nm TSMC CMOS process with a total area of 3.3 mm × 2.7 mm.

A simplification of Cobelli's glucose-insulin model for type 1 diabetes mellitus and its FPGA implementation.

Cobelli's glucose-insulin model is the only computer simulator of glucose-insulin interactions accepted by Food Drug Administration as a substitute to animal trials. However, it consists of multiple differential equations that make it hard to be implemented on a hardware platform. In this investigation, the Cobelli's model is simplified by Padé approximant method and implemented on a field-programmable gate array-based platform as a hardware model for predicting glucose changes in subjects with type 1 diabetes mellitus. Compared with the original Cobelli's model, the implemented hardware model provides a nearly perfect approximation in predicting glucose changes with rather small root-mean-square errors and maximum errors. The RMSE results for 30 subjects show that the method for simplifying and implementing Cobelli's model has good robustness and applicability. The successful hardware implementation of Cobelli's model will promote a wider adoption of this model that can substitute animal trials, provide fast and reliable glucose and insulin estimation, and ultimately assist the further development of an artificial pancreas system.

Integration of Bioelectronics and Bioinformatics: Future Direction of Bioengineering Research.

This special issue of the Journal of Medical and Biological Engineering highlights the field of advanced bioelectronics and bioinformatics. Several papers were considered for this special issue, including those on bioelectronics in wearable and implantable medical devices, such as sensors, and bioinformatics in healthcare, brain cognition, and various neural pathologies. Many investigators contributed original research articles to this issue, demonstrating emerging research fields. More than 20 papers were accepted for publication after a high-quality critical review was conducted, and 14 papers were selected for this special issue. This special issue on bioelectronics and bioinformatics attracted a substantial number of full-paper submissions from many countries. We appreciate the numerous volunteers who helped review the manuscripts. This paper provides a brief review of issues regarding bioelectronics and bioinformatics devices.

Low-power wireless ECG acquisition and classification system for body sensor networks.

A low-power biosignal acquisition and classification system for body sensor networks is proposed. The proposed system consists of three main parts: 1) a high-pass sigma delta modulator-based biosignal processor (BSP) for signal acquisition and digitization, 2) a low-power, super-regenerative on-off keying transceiver for short-range wireless transmission, and 3) a digital signal processor (DSP) for electrocardiogram (ECG) classification. The BSP and transmitter circuits, which are the body-end circuits, can be operated for over 80 days using two 605 mAH zinc-air batteries as the power supply; the power consumption is 586.5 µW. As for the radio frequency receiver and DSP, which are the receiving-end circuits that can be integrated in smartphones or personal computers, power consumption is less than 1 mW. With a wavelet transform-based digital signal processing circuit and a diagnosis control by cardiologists, the accuracy of beat detection and ECG classification are close to 99.44% and 97.25%, respectively. All chips are fabricated in TSMC 0.18-µm standard CMOS process.

Implementation of a wireless ECG acquisition SoC for IEEE 802.15.4 (ZigBee) applications.

This paper presents a wireless biosignal acquisition system-on-a-chip (WBSA-SoC) specialized for electrocardiogram (ECG) monitoring. The proposed system consists of three subsystems, namely, 1) the ECG acquisition node, 2) the protocol for standard IEEE 802.15.4 ZigBee system, and 3) the RF transmitter circuits. The ZigBee protocol is adopted for wireless communication to achieve high integration, applicability, and portability. A fully integrated CMOS RF front end containing a quadrature voltage-controlled oscillator and a 2.4-GHz low-IF (i.e., zero-IF) transmitter is employed to transmit ECG signals through wireless communication. The low-power WBSA-SoC is implemented by the TSMC 0.18-µm standard CMOS process. An ARM-based displayer with FPGA demodulation and an RF receiver with analog-to-digital mixed-mode circuits are constructed as verification platform to demonstrate the wireless ECG acquisition system. Measurement results on the human body show that the proposed SoC can effectively acquire ECG signals.

A wireless ECG acquisition and classification system for body sensor networks.

This paper demonstrates a wireless ECG acquisition and classification system with a bio-signal processor (BSP), a super regenerative transceiver, and a digital signal processor (DSP). The BSP, which is implemented with low complexity architecture, includes only a low noise amplifier with chopping techniques and a high-pass sigma-delta modulator (HPSDM). The super-regenerative on-off keying (OOK) transceiver is applied for the low power, short range transmission and low date rate wireless communication. For the signal processing and analyzing, the DSP circuit is adopted in the receiver. The whole system is implemented in a TSMC 0.18 µm 1P6M CMOS process under the supply voltage of 1.2 V. In the near body node, the power consumption including a BSP and a transmitter is 587 µW only. With two PR44 zinc-air batteries of 605 mAh, the near body node circuit can be operated about 100 days. In the receiving node, the power consumption with a receiver and a DSP is 926 µW.

An RFID tag system-on-chip with wireless ECG monitoring for intelligent healthcare systems.

This paper presents a low-power wireless ECG acquisition system-on-chip (SoC), including an RF front-end circuit, a power unit, an analog front-end circuit, and a digital circuitry. The proposed RF front-end circuit can provide the amplitude shift keying demodulation and distance to digital conversion to accurately receive the data from the reader. The received data will wake up the power unit to provide the required supply voltages of analog front-end (AFE) and digital circuitry. The AFE, including a pre-amplifier, an analog filter, a post-amplifier, and an analog-to-digital converter, is used for the ECG acquisition. Moreover, the EPC Class I Gen 2 UHF standard is employed in the digital circuitry for the handshaking of communication and the control of the system. The proposed SoC has been implemented in 0.18-µm standard CMOS process and the measured results reveal the communication is compatible to the RFID protocol. The average power consumption for the operating chip is 12 µW. Using a Sony PR44 battery to the supply power (605mAh@1.4V), the RFID tag SoC operates continuously for about 50,000 hours (>5 years), which is appropriate for wireless wearable ECG monitoring systems.