Yi-Han Ou-Yang, Ronald Wijermars, Pyungwoo Yeon, Tianqi Lu, Amin Arbabian, Wouter A Serdijn, Sijun Du, Dante G Muratore
{"title":"A 40.68-MHz Fully-Integrated Voltage/Current-Mode Dual-Output PMU for Wireless Neural Implants.","authors":"Yi-Han Ou-Yang, Ronald Wijermars, Pyungwoo Yeon, Tianqi Lu, Amin Arbabian, Wouter A Serdijn, Sijun Du, Dante G Muratore","doi":"10.1109/TBCAS.2025.3591228","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3591228","url":null,"abstract":"<p><p>This paper presents a fully-integrated single-input dual-output power management unit operating both in voltage/ current modes for powering mm-scale wireless neural implants. The chip operates in voltage mode most of the time, using an active full-wave rectifier to regulate a low-voltage, high-load output with high power efficiency and low output ripple (<32 mV<sub>pp</sub>). It switches to current mode rectification when generating a high-voltage, low-load output. This dual-mode operation allows for flexible power distribution and configurable voltage ratios between the two outputs. The selected 40.68 MHz operating frequency reduces the required capacitances for input impedance matching and output filtering, enabling on-chip integration; the only external component is the receiver coil. A novel resonance breakup switch compatible with full-wave rectification ensures a smooth cold start-up of the chip without any external voltage supply. The chip was fabricated using 40-nm CMOS technology with an active area of 1.18 mm<sup>2</sup>and was tested in a wireless power link. Measurement results demonstrate that the chip can simultaneously regulate two outputs, $V_{LV} = text{1 V}$ and $V_{HV} = text{2 V}$, with a tested maximum output power of 10 mW and 32.6 μW on $V_{LV}$ and $V_{HV}$ , respectively. At the optimal output power condition $(P_{LV} = 4.4 sim 6.7, text{mW})$, the system achieves a peak power conversion efficiency of 85.87% and a peak end-to-end efficiency of 17.32% when regulating $V_{LV}$. The end-to-end efficiency drops by only 2.38% when regulating both outputs with $R_{LV} = 225 Omega$ and $R_{HV} = 400 ,text{k}Omega$.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Novel Stimulus Artifact Suppression System with Fast Template Subtraction.","authors":"Yirui Liu, Quanbei Chang, Xuhui Li, Xiao Liu","doi":"10.1109/TBCAS.2025.3591110","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3591110","url":null,"abstract":"<p><p>The presence of large stimulus artifact (SA) makes it difficult to perform concurrent stimulation and recording in retinal prostheses. This paper presents a novel template-based system for suppressing SA visible at the stimulation/recording electrodes. The template of SA has been derived by working out the full Randles impedance model whose expression in the frequency domain serves as the transfer function from the stimulus current to SA. A prototype ASIC has been fabricated in a 180-nm CMOS process and validated in saline. The template calculation framework utilizes a pipeline digital processing which achieves rapid template generation within 26.35 ms (25.6 ms for acquiring the SA waveform and 0.75 ms for computation) after the detection of the first stimulation cycle. The real-time SA suppression is 20.2 dB and can be boosted to 44.3 dB with offline signal processing. The ASIC's core occupies 0.43 mm<sup>2</sup>. It consumes 8.27 μW and 30.83 μW in the normal amplification mode and SA suppression mode, respectively.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144692834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qiuyang Lin, Sander Crols, Aurojyoti Das, Marcel Zevenbergen, Wim Sijbers, Nick Van Helleputte, Carolina Mora Lopez
{"title":"Advances and Challenges in Integrated Circuits for Electrochemical Sensing: Enabling Next-Generation Biomedical and Molecular Applications.","authors":"Qiuyang Lin, Sander Crols, Aurojyoti Das, Marcel Zevenbergen, Wim Sijbers, Nick Van Helleputte, Carolina Mora Lopez","doi":"10.1109/TBCAS.2025.3589027","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3589027","url":null,"abstract":"<p><p>This manuscript provides a comprehensive review of the design, implementation, and advancements in integrated circuits (ICs) for electrochemical sensing, with a focus on biomedical and molecular applications. It begins by discussing the fundamental principles of electrochemical sensing and core modalities, including potentiometry, amperometry, impedimetry, and ISFET-based sensing, highlighting their unique requirements and challenges. A detailed analysis of state-of-the-art readout circuit architectures is presented, emphasizing strategies for achieving high dynamic range (DR), low noise, and enhanced stability while minimizing leakage currents. Both resistive and capacitive transimpedance amplifiers (TIAs) and current conveyor (CC)-based circuits are examined, exploring critical trade-offs between speed, power consumption, and noise performance. This review also discusses emerging applications such as DNA sequencing and molecular sensing, covering both ISFET and nanopore-based approaches, to showcase recent advancements in high-throughput, high-speed, and low-power interface circuit designs. By highlighting the challenges of the readout-circuit miniaturization, integration, and scalability, as well as the current limitations in existing approaches, this review provides a comprehensive synthesis of advancements in high-performance electrochemical readout architectures and their potential to address the evolving demands of modern biomedical applications.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144639078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Fully-Integrated 0.068-mm<sup>3</sup> Implantable Pressure Sensing Device with Wireless Energy Harvesting and Data Telemetry.","authors":"Zehua Lan, Jiahua Shi, Jiayue Hao, Zhihua Wang, Yanshu Guo, Hanjun Jiang","doi":"10.1109/TBCAS.2025.3586009","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3586009","url":null,"abstract":"<p><p>This paper reports a fully-integrated sub-0.1 mm<sup>3</sup> wireless pressure sensing device for implantable applications. The miniature device integrates a customized system-on-a-chip (SoC) and an off-the-shelf half-bridge piezoresistive pressure transducer, eliminating off-chip passive components. The SoC mainly comprises a resistance-to-time converter, a 915 MHz inductively coupled energy harvester with an on-chip coil, and a backscatter telemetry. Key innovations enabling low power, small size and high precision include: (1) A source-input common-gate amplifier based R-V converter, that reuses the transducer's bias current, (2) advanced noise management via chopper stabilization and supply noise cancellation, and (3) A compact high-Q on-chip multi-layer stacked coil design for wireless link. The active circuits consume 9.75 μW power, which is fully supplied by the energy harvested wirelessly through the on-chip coil. The sensing data is transmitted wirelessly to an external recorder through the RF backscatter link. Fabricated in a 65-nm CMOS technology, the SoC occupies a die area of 400 μm × 490 μm, and the entire fully-integrated sensor has a volume of only 0.068 mm<sup>3</sup>, enabling syringe injection through a ≤0.5 mm needle. Experiments with the sensing device covered by pork have demonstrated that the device can operate at an implant depth of up to 10 mm with excellent misalignment tolerance. It offers a pressure sensing resolution of 3.1 mmHg over a relative pressure range of 0-200 mmHg and a temperature sensing resolution of 0.18°C.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144565570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Differential Impedance Flow Cytometry Front-End with Baseline Current Cancellation.","authors":"Siyuan Yu, Louis Marun, Matthew L Johnston","doi":"10.1109/TBCAS.2025.3585089","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3585089","url":null,"abstract":"<p><p>In this work, we present a high-performance analog front-end (AFE) circuit for impedance-based flow cytometry readout. The AFE is designed to interface to a three-electrode sensor topology using center electrode excitation and differential current output. To satisfy the needs of a differential high gain signal path, we propose a digitally tunable and calibrated cancellation current generation path to remove the baseline current injected into the transimpedance amplifier (TIA) stages. This prevents TIA saturation and allows for higher gain. Consequently, the AFE is more power efficient while maintaining better noise and interference rejection. The proposed circuit is designed and fabricated in a 180nm CMOS process. It covers an excitation frequency range of 0.5MHz to 10MHz and consumes 15.6mW during nominal operation. Digital calibration is implemented using an off-chip ADC and automated calibration algorithm. Measurement results show that at 1MHz excitation, the AFE achieves $1.7 text{pA}/sqrt{text{Hz}}$ input-referred current noise density with floating inputs. The AFE achieves detection of 3um diameter particles in a microfluidic flow cell, demonstrating its performance and practicality for impedance flow cytometry.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144546653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mannhee Cho, Minil Kang, Minseong Um, Hangue Park, Hyung-Min Lee
{"title":"CMOS LIF Neurons with Local Membrane Dynamic Biasing Based on Reciprocal Inhibition for Self-Oscillatory Neural Networks.","authors":"Mannhee Cho, Minil Kang, Minseong Um, Hangue Park, Hyung-Min Lee","doi":"10.1109/TBCAS.2025.3583093","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3583093","url":null,"abstract":"<p><p>This paper presents a CMOS-based neuron network that can emulate self-oscillatory biasing behaviors found in biological neural oscillator models. Based on leaky integrate-and-fire (LIF) neuron models, the proposed neuron circuit adopts the concept of reciprocal inhibitory network and synaptic fatigue as well as excitatory drive stimulation for replicating extracellular fluidic biasing of membrane potentials. On top of the base neuron circuit, an excitation integrator integrates positive and negative excitatory input spikes to stimulate the membrane potential bias, and a bias controller receives inhibitory drive input and generates output inhibitory drives depending on the membrane potential bias level. The proposed networks of multiple neurons with inhibitory connections can generate oscillating membrane potential biases, which can be used as local dynamic thresholds for neuron spike firing, resulting in self-patterned output spikes such as switching or dynamic firing rate patterns. The proposed neuron network was implemented with 250-nm CMOS process operating at the supply voltage of 2.5 V and consuming average power of 99.31μW per neuron during full operation. Operation waveforms were measured in various input conditions which can produce multiple output patterns. Variances in output signals due to process variation were measured from 32 neurons to verify the stability of operation, showing the standard deviation of 18% in the membrane potential gain per input spike and 12% in oscillation periods of the membrane potential bias. The results verified that the proposed neuron network can replicate the self-oscillatory behaviors of biological neuron models.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144499941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A 0.66-mm<sup>2</sup> 0.49 pJ/SOP SNN Processor with Temporal-Spatial Post-Neuron-Processing and Model-Adaptive Crossbar in 40-nm CMOS.","authors":"Jinqiao Yang, Zikai Zhu, Haoming Chu, Anqin Xiao, Yuxiang Huan, Lirong Zheng, Zhuo Zou","doi":"10.1109/TBCAS.2025.3582246","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3582246","url":null,"abstract":"<p><p>This paper presents a Spiking Neural Network (SNN) processor specifically designed to overcome the limitations of existing parallel architectures in maintaining high energy efficiency and model adaptability in a compact area footprint for Artificial Intelligence of Things (AIoT). This is achieved through two key design features: a Temporal-Spatial Post-Neuron Processing (PoNP) scheme that efficiently reuses membrane potential, maximizes parallelism, and reduces memory bank requirements; and a Model-Adaptive Crossbar design with preconfigured parameters and a dynamic switching mechanism enables processing of various SNN models through operation orchestration without efficiency degradation. Using an 8-way parallel pipeline design, the processor achieves a throughput of 128 Synaptic Operations (SOPs) per cycle, resulting in a 2.8× enhancement in energy efficiency. Fabricated in a 40-nm CMOS process, the chip occupies a compact core area of 0.66 mm<sup>2</sup>. It achieves a power consumption of 6.26 mW, an energy efficiency of 0.49 pJ/SOP, and a throughput of 12.8 GSOPS/s at 0.75 V, 100 MHz. The chip is evaluated using typical spatial, temporal, and temporal-spatial datasets, including MIT-BIH, MNIST, N-MNIST, NavGesture, and SHD. These results demonstrate that our chip achieves best-in-class in terms of energy efficiency and latency compared to state-of-the-art architectures.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144487501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Regulating 3D Magnetic Flux Density for Stable Wireless Power Transfer in a Compact Planar Charger for Capsule Endoscopy.","authors":"Heng Zhang, Zheng Li, Chi-Kwan Lee","doi":"10.1109/TBCAS.2025.3581526","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3581526","url":null,"abstract":"<p><p>Wireless charging for small electronic devices remains a significant challenge, especially for applications that demand high-performance operation, such as wearable electronics and medical devices. Many compact devices, including smart-watches and capsule endoscopes, often suffer from limited battery life and frequent recharging requirements. To address these issues, this paper proposes a compact, planar, omnidirectional wireless power transmitter implemented on a multilayer printed circuit board. The proposed design achieves stable wireless charging across varying positions and orientations while maintaining a portable form factor that enables convenient use in diverse settings. To mitigate control challenges arising from overlapping transmitter coils in the planar configuration, a current source inverter is integrated with an LCCL compensation network. Comprehensive mathematical modeling is developed to provide design insights, and the system performance is further validated through computer simulations. In addition, we propose a robust wireless charging algorithm that maintains stable performance under arbitrary spatial positions and orientations, as evidenced by experimental tests demonstrating a mean receiving current fluctuation of only 2.16 mA. Moreover, in capsule endoscopy scenarios, the system achieved an effective charging performance with a maximum transmission power of 1904.4 mW, underscoring its competitiveness with current state-of-the-art designs.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144334645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zhongzheng Wang, Han Shao, Alan O Riordan, Javier Higes-Marquez, Ivan O Connell, Daniel O Hare
{"title":"A Fast Electrochemical Impedance Spectroscopy with A Square Wave as Excitation Signal for Impedance-based Biomedical Applications.","authors":"Zhongzheng Wang, Han Shao, Alan O Riordan, Javier Higes-Marquez, Ivan O Connell, Daniel O Hare","doi":"10.1109/TBCAS.2025.3579698","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3579698","url":null,"abstract":"<p><p>This paper introduces a fast, high-accuracy methodology for conducting Electrochemical Impedance Spectroscopy (EIS) based on Fast Fourier Transform (FFT), to meet the requirements of portable, real-time biomedical impedance-based detections with Ultra-Microband (UMB) sensor. Instead of using white noise-like wideband signals as in conventional FFT-based EIS, the proposed method uses a square wave as the excitation signal, which achieves a fast, accurate EIS measurement, but no longer requires complex circuits like high-resolution DACs or frequency mixers for the signal generation. This work starts with the theoretical justification for treating the sensor as a Linear Time-Invariant (LTI), then the practical linear region for operating the sensor as an LTI system is experimentally verified and determined, which enables the capacity of employing the harmonics of a square wave for EIS measurements. A dynamic model of the charge-transfer resistance together with an approximated of the Constant Phase Element (CPE) are implemented with Verilog-A for simulations, and a circuit consisting of a control amplifier and a Trans-Impedance Amplifier (TIA) is designed and fabricated with 65 nm CMOS for validating its on-chip feasibility. This work shortens the EIS measurement time by 91.7% in a frequency sweep range from 0.5 Hz to 500 Hz, with only 2.73% average Mean Absolute Percentage Error (MAPE), compared to a commercial electrochemical instrument AutoLab, with five pre-modified electrodes across four different concentrations of Ferrocene Carboxylic Acid (FcCOOH), demonstrating this method is suitable for portable, real-time label-free EIS biomedical detections and applications.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144328223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bokyung Kim, Qijia Huang, Brady Taylor, Qilin Zheng, Jonathan Ku, Yiran Chen, Hai Li
{"title":"MulPi: A Multi-class and Patient-independent Epileptic Seizure Classifier with Co-designed Input-stationary Computing-in-SRAM.","authors":"Bokyung Kim, Qijia Huang, Brady Taylor, Qilin Zheng, Jonathan Ku, Yiran Chen, Hai Li","doi":"10.1109/TBCAS.2025.3579273","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3579273","url":null,"abstract":"<p><p>Unprovoked seizures have threatened epilepsy patients over 70 million. Automated classification to detect and predict seizures could bring seizure-free lives to epilepsy patients, delivering them from fatal danger and increasing the quality of life. Authentic detection and prediction of seizures require 1) multi-class (Mul) and 2) patient-independent (Pi) classification. Recent implementable chips for seizure classification rarely satisfy the two requirements due to restricted resources in small chips; therefore, high efficiency is imperative along with accuracy. This paper introduces an efficient MulPi chip, fabricated for the first time to simultaneously fulfill multi-class and patient independence, based on a co-design approach. We develop a 5-layer convolutional neural network (CNN), MulPiCNN, with advanced training techniques for lightness and accuracy. At the hardware level, our SRAM-based chip leverages computingin- memory (CIM) for efficiency. The fabricated MulPi chip is distinguished from prior CIMs in two folds, namely ISRW-CIM: a) input-stationary (IS) CIM for resource-saving, and b) rowwise (RW) computing to address a challenge of SRAM CIM, empowered by our novel 2T-Hadamard product unit (HPU). MulPi outperforms state-of-the-art chips with 98.5% sensitivity and 99.2% specificity, classifying in 0.12s and 0.348mm<sup>2</sup>.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}