IEEE transactions on biomedical circuits and systems最新文献

英文中文

Wearable Stimulator for Upper and Lower Limb Somatotopic Sensory Feedback Restoration 用于上肢和下肢体位感觉反馈恢复的穿戴式刺激器。

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-09-09 DOI: 10.1109/TBCAS.2025.3607203

Roberto Paolini;Riccardo Collu;Laura Tullio;Andrea Demofonti;Alessia Scarpelli;Francesca Cordella;Massimo Barbaro;Loredana Zollo

Neuroprostheses capable of providing Somatotopic Sensory Feedback (SSF) enables the restoration of tactile sensations in amputees, thereby enhancing prosthesis embodiment, object manipulation, balance and walking stability. Transcutaneous Electrical Nerve Stimulation (TENS) represents a primary non-invasive technique for eliciting somatotopic sensations. Devices commonly used to evaluate the effectiveness of TENS stimulation are often bulky and main powered. However, current portable TENS devices frequently fall short of key functional requirements, particularly in terms of stimulation parameter ranges that are insufficient to reliably evoke somatotopic sensations in either upper and lower limb applications. Moreover, they typically do not support real-time independent channels programming and wireless communication. This work introduces a compact, wearable stimulator, including its external casing, with a total weight of 64 g and dimensions of 70

${boldsymbol{times}}$

35 mm, designed to deliver SSF in both upper and lower limb applications. The device was validated through bench testing and human trials involving 20 healthy participants, by comparing the intensity, qualitative characteristics, and referred area of the elicited sensations with those produced by a benchmark. The stimulator reliably delivered the required parameters on a skin-like capacitive-resistive load and elicited somatotopic sensations consistent with the benchmark device and prior somatotopic feedback studies. The proposed stimulator provides non-invasive somatotopic sensory feedback for both upper and lower limbs. Its portability and modular design address key limitations of current commercial and research-grade TENS systems, enabling future studies on the functional benefits of sensory feedback in prosthetic control.

能够提供体位感觉反馈（SSF）的神经假肢能够恢复截肢者的触觉，从而增强假肢的体现、物体操纵、平衡和行走稳定性。经皮神经电刺激（TENS）是一种主要的无创技术，用于引发体位感觉。通常用于评估TENS刺激效果的设备通常体积庞大且主要由电源供电。然而，目前的便携式TENS设备经常达不到关键的功能要求，特别是在刺激参数范围方面，不足以在上肢和下肢应用中可靠地唤起体位感觉。此外，它们通常不支持实时独立频道编程和无线通信。这项工作介绍了一种紧凑的可穿戴刺激器，包括其外部外壳，总重量为64克，尺寸为70% - 40% - 35毫米，旨在为上肢和下肢应用提供SSF。该装置通过台架测试和20名健康参与者的人体试验进行了验证，通过比较诱发感觉的强度、定性特征和参考区域与基准产生的感觉。该刺激器在类似皮肤的容阻负载上可靠地传递所需参数，并引发与基准装置和先前的躯体反馈研究一致的躯体感觉。所提出的刺激器为上肢和下肢提供非侵入性的躯体感觉反馈。它的便携性和模块化设计解决了当前商业和研究级TENS系统的关键限制，使未来的假肢控制感官反馈的功能优势研究成为可能。

{"title":"Wearable Stimulator for Upper and Lower Limb Somatotopic Sensory Feedback Restoration","authors":"Roberto Paolini;Riccardo Collu;Laura Tullio;Andrea Demofonti;Alessia Scarpelli;Francesca Cordella;Massimo Barbaro;Loredana Zollo","doi":"10.1109/TBCAS.2025.3607203","DOIUrl":"10.1109/TBCAS.2025.3607203","url":null,"abstract":"Neuroprostheses capable of providing Somatotopic Sensory Feedback (SSF) enables the restoration of tactile sensations in amputees, thereby enhancing prosthesis embodiment, object manipulation, balance and walking stability. Transcutaneous Electrical Nerve Stimulation (TENS) represents a primary non-invasive technique for eliciting somatotopic sensations. Devices commonly used to evaluate the effectiveness of TENS stimulation are often bulky and main powered. However, current portable TENS devices frequently fall short of key functional requirements, particularly in terms of stimulation parameter ranges that are insufficient to reliably evoke somatotopic sensations in either upper and lower limb applications. Moreover, they typically do not support real-time independent channels programming and wireless communication. This work introduces a compact, wearable stimulator, including its external casing, with a total weight of 64 g and dimensions of 70 <inline-formula><tex-math>${boldsymbol{times}}$</tex-math></inline-formula> 40 <inline-formula><tex-math>${boldsymbol{times}}$</tex-math></inline-formula> 35 mm, designed to deliver SSF in both upper and lower limb applications. The device was validated through bench testing and human trials involving 20 healthy participants, by comparing the intensity, qualitative characteristics, and referred area of the elicited sensations with those produced by a benchmark. The stimulator reliably delivered the required parameters on a skin-like capacitive-resistive load and elicited somatotopic sensations consistent with the benchmark device and prior somatotopic feedback studies. The proposed stimulator provides non-invasive somatotopic sensory feedback for both upper and lower limbs. Its portability and modular design address key limitations of current commercial and research-grade TENS systems, enabling future studies on the functional benefits of sensory feedback in prosthetic control.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"20 1","pages":"95-106"},"PeriodicalIF":4.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11154842","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145031543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Sparse-Integrated Filtering Residual Spiking Neural Network for High-Accuracy Spike Sorting and Co-Optimization on Memristor Platforms 忆阻器平台上高精度尖峰排序与协同优化的稀疏集成滤波残差尖峰神经网络。

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-22 DOI: 10.1109/TBCAS.2025.3601403

Yiwen Zhu;Jingyi Chen;Lingli Cheng;Fangduo Zhu;Xumeng Zhang;Qi Liu

Brain-computer interfaces rely on precise decoding of neural signals, where spike sorting is a critical step to extract individual neuronal activities from complex neural data. This work presents a spiking neural network (SNN) framework for efficient spike sorting, named SIFT-RSNN. In the SIFT-RSNN, raw neural signals are encoded into spike trains using a threshold-based temporal encoding strategy, then a sparse-integrated filtering module refines misfiring spikes, enhancing data sparsity for pattern learning. The RSNN module with a membrane shortcut structure ensures efficient feature transfer and improves generalization performance of the overall system. The SIFT-RSNN achieves an accuracy of 96.2% and 99.6% on the Difficult1 and Difficult2 subsets of Leicester dataset, surpassing state-of-the-art methods. We also implement it on a compute-in-memory platform with 8k memristor cells utilizing quantization-free mapping method and propose two algorithm-hardware co-optimization strategies to mitigate non-ideal hardware effects: weight outlier pre-constraint (WOP) and noise adaptation training (NAT). After optimization, our algorithm continues to outperform existing spike sorting methods, achieving accuracies of 94.2% and 99.7%, while also demonstrating improved robustness. The memristor platform only exhibits a 2% and 1.5% accuracy drop compared to software results on the two difficult subsets. Additionally, it achieves 3.52

$ boldsymbol{mu}$

J energy consumption and 0.5 ms latency per inference. This work offers promising solutions for brain-computer interface systems and neural prosthesis applications in the future.

脑机接口依赖于神经信号的精确解码，其中脉冲排序是从复杂的神经数据中提取单个神经元活动的关键步骤。本文提出了一种用于高效尖峰排序的尖峰神经网络（SNN）框架，称为SIFT-RSNN。在SIFT-RSNN中，使用基于阈值的时间编码策略将原始神经信号编码成尖峰序列，然后使用稀疏集成滤波模块对失发尖峰进行细化，增强数据的稀疏性，用于模式学习。RSNN模块采用膜捷径结构，保证了特征的高效传递，提高了整个系统的泛化性能。SIFT-RSNN在Leicester数据集的hardt1和hardt2子集上实现了96.2%和99.6%的准确率，超过了最先进的方法。此外，我们利用无量化映射方法在内存中计算平台上进行了8k忆阻器单元，并提出了两种算法-硬件协同优化策略来减轻非理想硬件影响：权重异常值预约束（WOP）和噪声适应训练（NAT）。优化后，我们的算法继续优于现有的尖峰排序方法，准确率达到94.2%和99.7%，同时也显示出更好的鲁棒性。与软件在两个困难子集上的结果相比，忆阻器平台的精度仅下降了2%和1.5%。此外，每次推理的能耗为3.52 μJ，延迟为0.5 ms。这项工作为未来的脑机接口系统和神经假体应用提供了有希望的解决方案。

{"title":"A Sparse-Integrated Filtering Residual Spiking Neural Network for High-Accuracy Spike Sorting and Co-Optimization on Memristor Platforms","authors":"Yiwen Zhu;Jingyi Chen;Lingli Cheng;Fangduo Zhu;Xumeng Zhang;Qi Liu","doi":"10.1109/TBCAS.2025.3601403","DOIUrl":"10.1109/TBCAS.2025.3601403","url":null,"abstract":"Brain-computer interfaces rely on precise decoding of neural signals, where spike sorting is a critical step to extract individual neuronal activities from complex neural data. This work presents a spiking neural network (SNN) framework for efficient spike sorting, named SIFT-RSNN. In the SIFT-RSNN, raw neural signals are encoded into spike trains using a threshold-based temporal encoding strategy, then a sparse-integrated filtering module refines misfiring spikes, enhancing data sparsity for pattern learning. The RSNN module with a membrane shortcut structure ensures efficient feature transfer and improves generalization performance of the overall system. The SIFT-RSNN achieves an accuracy of 96.2% and 99.6% on the Difficult1 and Difficult2 subsets of Leicester dataset, surpassing state-of-the-art methods. We also implement it on a compute-in-memory platform with 8k memristor cells utilizing quantization-free mapping method and propose two algorithm-hardware co-optimization strategies to mitigate non-ideal hardware effects: weight outlier pre-constraint (WOP) and noise adaptation training (NAT). After optimization, our algorithm continues to outperform existing spike sorting methods, achieving accuracies of 94.2% and 99.7%, while also demonstrating improved robustness. The memristor platform only exhibits a 2% and 1.5% accuracy drop compared to software results on the two difficult subsets. Additionally, it achieves 3.52 <inline-formula><tex-math>$ boldsymbol{mu}$</tex-math></inline-formula>J energy consumption and 0.5 ms latency per inference. This work offers promising solutions for brain-computer interface systems and neural prosthesis applications in the future.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"20 1","pages":"82-94"},"PeriodicalIF":4.9,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984004","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}

引用次数: 0

MRDust: Wireless Implant Data Uplink & Localization via Magnetic Resonance Image Modulation. MRDust：通过磁共振图像调制的无线植入数据上行和定位。

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-13 DOI: 10.1109/TBCAS.2025.3598682

Biqi Rebekah Zhao, Alexander Chou, Robert Peltekov, Elad Alon, Chunlei Liu, Rikky Muller, Michael Lustig

Magnetic resonance imaging (MRI) exhibits rich and clinically useful endogenous contrast mechanisms, which can differentiate soft tissues and are sensitive to flow, diffusion, magnetic susceptibility, blood oxygenation level, and more. However, MRI sensitivity is ultimately constrained by Nuclear Magnetic Resonance (NMR) physics, and its spatiotemporal resolution is limited by SNR and spatial encoding. On the other hand, miniaturized implantable sensors offer highly localized physiological information, yet communication and localization can be challenging when multiple implants are present. This paper introduces the MRDust, an active "contrast agent" that integrates active sensor implants with MRI, enabling the direct encoding of highly localized physiological data into MR images to augment the anatomical images. MRDust employs a micrometer-scale on-chip coil to actively modulate the local magnetic field, enabling MR signal amplitude and phase modulation for digital data transmission. Since MRI inherently captures the anatomical tissue structure, this method has the potential to enable simultaneous data communication, localization, and image registration with multiple implants. This paper presents the underlying physical principles, design tradeoffs, and design methodology for this approach. To validate the concept, a 900 × 990 µm² chip was designed using TSMC 28 nm technology, with an on-chip coil measuring 630 µm in diameter. The chip was tested with custom hardware in an MR750W GE3T MRI scanner. Successful voxel amplitude modulation is demonstrated with Spin-Echo Echo-Planar-Imaging (SE-EPI) sequence, achieving a contrast-to-noise ratio (CNR) of 25.58 with a power consumption of 130 µW.

磁共振成像（MRI）显示了丰富和临床有用的内源性对比机制，可以区分软组织，对血流、扩散、磁化率、血氧水平等敏感。然而，MRI的灵敏度最终受到核磁共振（NMR）物理特性的限制，其时空分辨率受到信噪比和空间编码的限制。另一方面，微型植入式传感器提供高度定位的生理信息，但当多个植入物存在时，通信和定位可能具有挑战性。本文介绍了MRDust，一种将主动传感器植入物与MRI相结合的活性“造影剂”，可以将高度定位的生理数据直接编码到MR图像中，以增强解剖图像。MRDust采用微米级片上线圈主动调制本地磁场，使MR信号的幅度和相位调制用于数字数据传输。由于MRI固有地捕获解剖组织结构，因此该方法具有实现多个植入物同时进行数据通信，定位和图像配准的潜力。本文介绍了这种方法的基本物理原理、设计权衡和设计方法。为了验证这一概念，采用台积电28纳米技术设计了一个900 × 990µm2的芯片，片上线圈直径为630µm。该芯片在MR750W GE3T核磁共振扫描仪上使用定制硬件进行测试。利用自旋回波回波平面成像（SE-EPI）序列成功实现了体素调幅，实现了25.58的对比噪声比（CNR），功耗为130µW。

{"title":"MRDust: Wireless Implant Data Uplink & Localization via Magnetic Resonance Image Modulation.","authors":"Biqi Rebekah Zhao, Alexander Chou, Robert Peltekov, Elad Alon, Chunlei Liu, Rikky Muller, Michael Lustig","doi":"10.1109/TBCAS.2025.3598682","DOIUrl":"https://doi.org/10.1109/TBCAS.2025.3598682","url":null,"abstract":"Magnetic resonance imaging (MRI) exhibits rich and clinically useful endogenous contrast mechanisms, which can differentiate soft tissues and are sensitive to flow, diffusion, magnetic susceptibility, blood oxygenation level, and more. However, MRI sensitivity is ultimately constrained by Nuclear Magnetic Resonance (NMR) physics, and its spatiotemporal resolution is limited by SNR and spatial encoding. On the other hand, miniaturized implantable sensors offer highly localized physiological information, yet communication and localization can be challenging when multiple implants are present. This paper introduces the MRDust, an active \"contrast agent\" that integrates active sensor implants with MRI, enabling the direct encoding of highly localized physiological data into MR images to augment the anatomical images. MRDust employs a micrometer-scale on-chip coil to actively modulate the local magnetic field, enabling MR signal amplitude and phase modulation for digital data transmission. Since MRI inherently captures the anatomical tissue structure, this method has the potential to enable simultaneous data communication, localization, and image registration with multiple implants. This paper presents the underlying physical principles, design tradeoffs, and design methodology for this approach. To validate the concept, a 900 × 990 µm2 chip was designed using TSMC 28 nm technology, with an on-chip coil measuring 630 µm in diameter. The chip was tested with custom hardware in an MR750W GE3T MRI scanner. Successful voxel amplitude modulation is demonstrated with Spin-Echo Echo-Planar-Imaging (SE-EPI) sequence, achieving a contrast-to-noise ratio (CNR) of 25.58 with a power consumption of 130 µW.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":4.9,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144850105","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}

引用次数: 0

Fully Wireless ASIC With MagSonic Operation Using Magnetoelectric Transducer for Neural Stimulation and Recording 使用磁电换能器进行神经刺激和记录的全无线专用集成电路。

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-13 DOI: 10.1109/TBCAS.2025.3598568

Sujay Hosur;Hyunjin Lee;Tao Zhou;Mehdi Kiani

A wireless application-specific integrated circuit (ASIC), operating with the MagSonic modality using one magnetoelectric (ME) transducer, is presented for neural stimulation and recording. The ASIC integrates a bridge circuit that forms both power management and data transmitter with voltage doubling, rectification, regulation, and over voltage protection, a biphasic AC stimulator with high voltage tolerance and direct external control simplifying downlink complexities and on-chip processing overhead, an active charge balancing circuit adjusting the duration of second stimulation phase, and a continuous neural recording and uplink communication. The prototype MagSonic ASIC was fabricated in a 180 nm standard CMOS process (2

${boldsymboltimes}$

1.75 mm² total area) and requires only one ME transducer and an external storage capacitor to operate. In measurements, a bar shaped millimeter-scale ME transducer (5.1

${boldsymboltimes}$

2.29

${boldsymboltimes}$

1.69 mm³) with length mode operation at 330 kHz was used to power the ASIC, achieving up to 8.1 mW of received power at 40 mm depth. The biphasic AC stimulator occupying only 0.027 mm² of active chip area provided 6.6 V (2

${boldsymboltimes}$

V_DD) tolerance (using 3.3 V transistors) with residual electrode voltage of < 50 mV. The amplified signals were converted into time using an analog-to-time converter and transmitted at a data rate of 186.2 kbps (< 10⁻³ BER) using the ME transducer’s thickness mode frequency (1.66 MHz). Animal experiment results demonstrate the feasibility of ASIC’s direct AC stimulation.

提出了一种无线专用集成电路（ASIC），使用一个磁电（ME）换能器与MagSonic模式一起工作，用于神经刺激和记录。ASIC集成了一个桥接电路，该桥接电路构成电源管理和数据发送器，具有倍压、整流、调节和过压保护功能；一个具有高电压容限和直接外部控制的双相交流刺激器，简化了下行链路的复杂性和片上处理开销；一个调节第二刺激阶段持续时间的有源电荷平衡电路，以及一个连续的神经记录和上行通信。原型MagSonic ASIC采用180 nm标准CMOS工艺（2×1.75 mm2总面积）制造，只需要一个ME换能器和一个外部存储电容器即可运行。在测量中，使用长度模式工作在330 kHz的条形毫米级ME换能器（5.1×2.29×1.69 mm3）为ASIC供电，在40 mm深度处实现高达8.1 mW的接收功率。双相交流刺激器仅占用0.027 mm2的有源芯片面积，提供6.6 V （2×VDD）容差（使用3.3 V晶体管），剩余电极电压< 50 mV。放大后的信号通过模拟-时间转换器转换为时间，并使用ME换能器的厚度模式频率（1.66 MHz）以186.2 kbps （< 10-3 BER）的数据速率传输。动物实验结果证明了ASIC直接交流刺激的可行性。

{"title":"Fully Wireless ASIC With MagSonic Operation Using Magnetoelectric Transducer for Neural Stimulation and Recording","authors":"Sujay Hosur;Hyunjin Lee;Tao Zhou;Mehdi Kiani","doi":"10.1109/TBCAS.2025.3598568","DOIUrl":"10.1109/TBCAS.2025.3598568","url":null,"abstract":"A wireless application-specific integrated circuit (ASIC), operating with the MagSonic modality using one magnetoelectric (ME) transducer, is presented for neural stimulation and recording. The ASIC integrates a bridge circuit that forms both power management and data transmitter with voltage doubling, rectification, regulation, and over voltage protection, a biphasic AC stimulator with high voltage tolerance and direct external control simplifying downlink complexities and on-chip processing overhead, an active charge balancing circuit adjusting the duration of second stimulation phase, and a continuous neural recording and uplink communication. The prototype MagSonic ASIC was fabricated in a 180 nm standard CMOS process (2 <inline-formula><tex-math>${boldsymboltimes}$</tex-math></inline-formula> 1.75 mm2 total area) and requires only one ME transducer and an external storage capacitor to operate. In measurements, a bar shaped millimeter-scale ME transducer (5.1<inline-formula><tex-math>${boldsymboltimes}$</tex-math></inline-formula>2.29<inline-formula><tex-math>${boldsymboltimes}$</tex-math></inline-formula>1.69 mm3) with length mode operation at 330 kHz was used to power the ASIC, achieving up to 8.1 mW of received power at 40 mm depth. The biphasic AC stimulator occupying only 0.027 mm2 of active chip area provided 6.6 V (2<inline-formula><tex-math>${boldsymboltimes}$</tex-math></inline-formula><italic>VDD) tolerance (using 3.3 V transistors) with residual electrode voltage of < 50 mV. The amplified signals were converted into time using an analog-to-time converter and transmitted at a data rate of 186.2 kbps (< 10−3 BER) using the ME transducer’s thickness mode frequency (1.66 MHz). Animal experiment results demonstrate the feasibility of ASIC’s direct AC stimulation.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"20 1","pages":"69-81"},"PeriodicalIF":4.9,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144850104","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}

引用次数: 0

Special Section on Selected Papers From IEEE BioCAS 2024 IEEE BioCAS 2024论文精选专题

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-05 DOI: 10.1109/TBCAS.2025.3590820

Sohmyung Ha;Hossein Kassiri;Milin Zhang;Andrea Cossettini

引用次数: 0

IEEE Circuits and Systems Society Information IEEE电路与系统学会信息

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-05 DOI: 10.1109/TBCAS.2025.3590819

引用次数: 0

IEEE Transactions on Biomedical Circuits and Systems Publication Information IEEE生物医学电路和系统汇刊信息

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-05 DOI: 10.1109/TBCAS.2025.3576469

引用次数: 0

Erratum to “A 43.5dB Gain Unipolar a-IGZO TFT Amplifier with Parallel Bootstrap Capacitor for Bio-signals Sensing Applications” “用于生物信号传感应用的带并联自引导电容的43.5dB增益单极A - igzo TFT放大器”的校误

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-05 DOI: 10.1109/TBCAS.2025.3583095

Mingjian Zhao;Laiqing Li;Rui Liu;Bin Li;Rongsheng Chen;Zhaohui Wu

In [1], a critical labeling error was identified in Fig. 21, where the x-axis was incorrectly labeled “−50 ms to 50 ms” instead of the correct range “0 s to 5 s” (reflecting the actual ECG data duration). This discrepancy resulted from unintentional reuse of a plotting template and insufficient validation during proofing. While the underlying ECG waveform data remains accurate, the mislabeled scale misrepresents the signal’s temporal characteristics. The Fig. 21 should be corrected as follows:

在[1]中，在图21中发现了一个关键的标记错误，其中x轴被错误地标记为“−50 ms至50 ms”，而不是正确的范围“0 s至5 s”（反映实际ECG数据持续时间）。这种差异是由于绘图模板的无意重用和打样过程中的验证不足造成的。虽然潜在的心电图波形数据仍然准确，但错误标记的尺度错误地表示了信号的时间特征。图21应修改如下：

引用次数: 0

A Fast Electrochemical Impedance Spectroscopy With a Square Wave as Excitation Signal for Impedance-Based Biomedical Applications. 基于阻抗的生物医学应用中以方波为激励信号的快速电化学阻抗谱。

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-01 DOI: 10.1109/TBCAS.2025.3579698

Zhongzheng Wang, Han Shao, Alan O'Riordan, Javier Higes-Marquez, Ivan O'Connell, Daniel O'Hare

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.

本文介绍了一种基于快速傅里叶变换（FFT）的快速、高精度电化学阻抗谱（EIS）方法，以满足便携式、实时生物医学阻抗检测的要求。该方法不像传统的基于fft的EIS那样使用类白噪声的宽带信号，而是使用方波作为激励信号，实现了快速、准确的EIS测量，但不再需要高分辨率dac或混频器等复杂电路来产生信号。这项工作从将传感器视为线性时不变（LTI）的理论论证开始，然后通过实验验证和确定将传感器作为LTI系统操作的实际线性区域，这使得能够使用方波的谐波进行EIS测量。利用Verilog-A软件建立了电荷转移电阻的动态模型和恒相元件（CPE）的近似模型进行仿真，并采用65 nm CMOS设计和制作了由控制放大器和跨阻抗放大器组成的电路，验证了其片上可行性。与AutoLab的商用电化学仪器相比，这项工作在0.5 Hz至500 Hz的频率扫描范围内将EIS测量时间缩短了91.7%，平均绝对百分比误差（MAPE）仅为2.73%，在四种不同浓度的二茂铁羧酸（FcCOOH）中使用了五个预修饰电极，证明了该方法适用于便携式，实时无标签的EIS生物医学检测和应用。

{"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":"10.1109/TBCAS.2025.3579698","url":null,"abstract":"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.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":"726-742"},"PeriodicalIF":4.9,"publicationDate":"2025-08-01","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}

引用次数: 0

FPGA-Based Medical Image Processing Using Hardware-Software Co-Design Approach 基于fpga的医学图像处理软硬件协同设计方法。

IF 4.9

IEEE transactions on biomedical circuits and systems

Pub Date : 2025-08-01 DOI: 10.1109/TBCAS.2025.3594840

Abhishek Yadav;Vyom Kumar Gupta;Binod Kumar

This paper presents a field-programmable gate array (FPGA) based medical image processing framework using a hardware-software co-design approach for biomedical tasks such as Malaria and Pneumonia detection. The design is implemented on the AMD-Xilinx UltraScale+ MPSoC (ZCU104) FPGA, focusing on optimizing data movement between the Processing System (PS) and Programmable Logic (PL) through a customized high-level synthesis (HLS) process. Depth-wise convolution is employed to reduce computational complexity, while layer fusion is applied to optimize layer-wise execution, and custom cache is integrated to improve memory access efficiency. The accelerated architecture is integrated with AXI interconnects and tested using the PYNQ overlay process. The experimental results demonstrate that the proposed accelerator achieves a throughput of 298.22 FPS and 205.87 FPS for the detection of malaria and pneumonia, respectively. The proposed design significantly improves energy efficiency, consuming 14.62 mJ/img for the detection of malaria and 23.89 mJ/img for the detection of pneumonia. Compared to alternative hardware platforms like Raspberry Pi with Coral TPU, the FPGA-based implementation offers superior performance, achieving 8.3

$boldsymbol{times}$

higher throughput and 4.3

$boldsymbol{times}$

better energy efficiency, making it well-suited for real-time medical image processing applications.

本文提出了一种基于现场可编程门阵列（FPGA）的医学图像处理框架，该框架采用软硬件协同设计方法用于疟疾和肺炎检测等生物医学任务。该设计是在AMD-Xilinx UltraScale+ MPSoC (ZCU104) FPGA上实现的，重点是通过定制的高级合成（HLS）工艺优化处理系统（PS）和可编程逻辑（PL）之间的数据移动。采用深度卷积降低计算复杂度，采用层融合优化分层执行，集成自定义缓存提高内存访问效率。加速架构与AXI互连集成，并使用PYNQ覆盖过程进行测试。实验结果表明，该加速器检测疟疾和肺炎的吞吐量分别为298.22 FPS和205.87 FPS。该设计显著提高了能效，疟疾检测能耗为14.62 mJ/img，肺炎检测能耗为23.89 mJ/img。与其他硬件平台（如带有Coral TPU的树莓派）相比，基于fpga的实现提供了卓越的性能，实现了8.3倍的吞吐量和4.3倍的能效，使其非常适合实时医疗图像处理应用。

{"title":"FPGA-Based Medical Image Processing Using Hardware-Software Co-Design Approach","authors":"Abhishek Yadav;Vyom Kumar Gupta;Binod Kumar","doi":"10.1109/TBCAS.2025.3594840","DOIUrl":"10.1109/TBCAS.2025.3594840","url":null,"abstract":"This paper presents a field-programmable gate array (FPGA) based medical image processing framework using a hardware-software co-design approach for biomedical tasks such as Malaria and Pneumonia detection. The design is implemented on the AMD-Xilinx UltraScale+ MPSoC (ZCU104) FPGA, focusing on optimizing data movement between the Processing System (PS) and Programmable Logic (PL) through a customized high-level synthesis (HLS) process. Depth-wise convolution is employed to reduce computational complexity, while layer fusion is applied to optimize layer-wise execution, and custom cache is integrated to improve memory access efficiency. The accelerated architecture is integrated with AXI interconnects and tested using the PYNQ overlay process. The experimental results demonstrate that the proposed accelerator achieves a throughput of 298.22 FPS and 205.87 FPS for the detection of malaria and pneumonia, respectively. The proposed design significantly improves energy efficiency, consuming 14.62 mJ/img for the detection of malaria and 23.89 mJ/img for the detection of pneumonia. Compared to alternative hardware platforms like Raspberry Pi with Coral TPU, the FPGA-based implementation offers superior performance, achieving 8.3<inline-formula><tex-math>$boldsymbol{times}$</tex-math></inline-formula> higher throughput and 4.3<inline-formula><tex-math>$boldsymbol{times}$</tex-math></inline-formula> better energy efficiency, making it well-suited for real-time medical image processing applications.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"20 1","pages":"57-68"},"PeriodicalIF":4.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144765894","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}

引用次数: 0

首页上一页

下一页尾页

类型

全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

数据库

全部 ACS Publications Elsevier ieeexplore Springer The Royal Society of Chemistry Wiley

期刊

IEEE transactions on biomedical circuits and systems

全部 Acc. Chem. Res. ACS Applied Bio Materials ACS Appl. Electron. Mater. ACS Appl. Energy Mater. ACS Appl. Mater. Interfaces ACS Appl. Nano Mater. ACS Appl. Polym. Mater. ACS BIOMATER-SCI ENG ACS Catal. ACS Cent. Sci. ACS Chem. Biol. ACS Chemical Health & Safety ACS Chem. Neurosci. ACS Comb. Sci. ACS Earth Space Chem. ACS Energy Lett. ACS Infect. Dis. ACS Macro Lett. ACS Mater. Lett. ACS Med. Chem. Lett. ACS Nano ACS Omega ACS Photonics ACS Sens. ACS Sustainable Chem. Eng. ACS Synth. Biol. Anal. Chem. BIOCHEMISTRY-US Bioconjugate Chem. BIOMACROMOLECULES Chem. Res. Toxicol. Chem. Rev. Chem. Mater. CRYST GROWTH DES ENERG FUEL Environ. Sci. Technol. Environ. Sci. Technol. Lett. Eur. J. Inorg. Chem. IND ENG CHEM RES Inorg. Chem. J. Agric. Food. Chem. J. Chem. Eng. Data J. Chem. Educ. J. Chem. Inf. Model. J. Chem. Theory Comput. J. Med. Chem. J. Nat. Prod. J PROTEOME RES J. Am. Chem. Soc. LANGMUIR MACROMOLECULES Mol. Pharmaceutics Nano Lett. Org. Lett. ORG PROCESS RES DEV ORGANOMETALLICS J. Org. Chem. J. Phys. Chem. J. Phys. Chem. A J. Phys. Chem. B J. Phys. Chem. C J. Phys. Chem. Lett. Analyst Anal. Methods Biomater. Sci. Catal. Sci. Technol. Chem. Commun. Chem. Soc. Rev. CHEM EDUC RES PRACT CRYSTENGCOMM Dalton Trans. Energy Environ. Sci. ENVIRON SCI-NANO ENVIRON SCI-PROC IMP ENVIRON SCI-WAT RES Faraday Discuss. Food Funct. Green Chem. Inorg. Chem. Front. Integr. Biol. J. Anal. At. Spectrom. J. Mater. Chem. A J. Mater. Chem. B J. Mater. Chem. C Lab Chip Mater. Chem. Front. Mater. Horiz. MEDCHEMCOMM Metallomics Mol. Biosyst. Mol. Syst. Des. Eng. Nanoscale Nanoscale Horiz. Nat. Prod. Rep. New J. Chem. Org. Biomol. Chem. Org. Chem. Front. PHOTOCH PHOTOBIO SCI PCCP Polym. Chem.

﹀