IEEE transactions on biomedical circuits and systems最新文献_第4页

A 40.68-MHz Fully-Integrated Voltage/Current-Mode Dual-Output PMU for Wireless Neural Implants. 用于无线神经植入物的40.68 mhz全集成电压/电流模式双输出PMU。

IF 4.9

IEEE transactions on biomedical circuits and systems Pub Date : 2026-02-01 DOI: 10.1109/TBCAS.2025.3591228

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":"10.1109/TBCAS.2025.3591228","url":null,"abstract":"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 $mathrm{mV}_{mathrm{pp}}$). 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 $mathrm{mm^{2}}$ and was tested in a wireless power link. Measurement results demonstrate that the chip can simultaneously regulate two outputs, $V_{LV}$ = 1 V and $V_{HV}$ = 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 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 k$Omega$.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":"41-56"},"PeriodicalIF":4.9,"publicationDate":"2026-02-01","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}

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

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IEEE transactions on biomedical circuits and systems Pub Date : 2026-01-28 DOI: 10.1109/TBCAS.2025.3639842

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

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IEEE transactions on biomedical circuits and systems Pub Date : 2026-01-28 DOI: 10.1109/TBCAS.2026.3654281

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Incoming Editorial 传入的编辑

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IEEE transactions on biomedical circuits and systems Pub Date : 2026-01-28 DOI: 10.1109/TBCAS.2026.3654331

Pedram Mohseni

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2025 Index IEEE Transactions on Biomedical Circuits and Systems 2025索引IEEE生物医学电路与系统学报

IF 4.9

IEEE transactions on biomedical circuits and systems Pub Date : 2025-12-19 DOI: 10.1109/TBCAS.2025.3646307

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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 : 2025-12-11 DOI: 10.1109/TBCAS.2025.3637418

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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 : 2025-12-11 DOI: 10.1109/TBCAS.2025.3637420

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Guest Editorial: Selected Papers from the 2025 IEEE International Solid-State Circuits Conference 嘉宾评论：2025年IEEE国际固态电路会议论文选集

IF 4.9

IEEE transactions on biomedical circuits and systems Pub Date : 2025-12-11 DOI: 10.1109/TBCAS.2025.3636715

Alison Burdett;Mehdi Kiani

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Configurable γ Photon Spectrometer to Enable Precision Radioguided Tumor Resection 可配置γ光子光谱仪，实现精确的放射引导肿瘤切除。

IF 4.9

IEEE transactions on biomedical circuits and systems Pub Date : 2025-12-05 DOI: 10.1109/TBCAS.2025.3625580

Rahul Lall;Youngho Seo;Ali M. Niknejad;Mekhail Anwar

{"title":"Configurable γ Photon Spectrometer to Enable Precision Radioguided Tumor Resection","authors":"Rahul Lall;Youngho Seo;Ali M. Niknejad;Mekhail Anwar","doi":"10.1109/TBCAS.2025.3625580","DOIUrl":"10.1109/TBCAS.2025.3625580","url":null,"abstract":"Surgical tumor resection aims to remove all cancer cells in the tumor margin and at centimeter-scale depths below the tissue surface. During surgery, microscopic clusters of disease are intraoperatively difficult to visualize and are often left behind, significantly increasing the risk of cancer recurrence. Radioguided surgery (RGS) has shown the ability to selectively tag cancer cells with gamma (γ) photon emitting radioisotopes to identify them, but require a mm-scale γ photon spectrometer to localize the position of these cells in the tissue margin (i.e., a function of incident γ photon energy) with high specificity. Here we present a 9.9 mm2 integrated circuit (IC)-based γ spectrometer implemented in 180 nm CMOS, to enable the measurement of single γ photons and their incident energy with sub-keV energy resolution. We use small <inline-formula><tex-math>$2 times 2$</tex-math></inline-formula> µm reverse-biased diodes that have low depletion region capacitance, and therefore produce millivolt-scale voltage signals in response to the small charge generated by incident γ photons. A low-power energy spectrometry method is implemented by measuring the decay time it takes for the generated voltage signal to settle back to DC after a γ detection event, instead of measuring the voltage drop directly. This spectrometry method is implemented in three different pixel architectures that allow for configurable pixel sensitivity, energy-resolution, and energy dynamic range based on the widely heterogenous surgical and patient presentation in RGS. The spectrometer was tested with three common γ-emitting radioisotopes (64Cu, 133Ba, 177Lu), and is able to resolve activities down to 1 µCi with sub-keV energy resolution and 1.315 MeV energy dynamic range, using 5-minute acquisitions.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"19 6","pages":"1048-1064"},"PeriodicalIF":4.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145688770","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}

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A 40-nm 3.9mW, 200words/Min Neural Signal Processor in Speech Decoding for Brain-Machine Interface 一种用于脑机接口语音解码的40nm 3.9mW、200words/min神经信号处理器。

IF 4.9

IEEE transactions on biomedical circuits and systems Pub Date : 2025-11-13 DOI: 10.1109/TBCAS.2025.3625650

Tun-Yu Chang;Jeng-Bang Wang;Yu-Hsuan Tsai;Yu Tsao;Chia-Hsiang Yang

{"title":"A 40-nm 3.9mW, 200words/Min Neural Signal Processor in Speech Decoding for Brain-Machine Interface","authors":"Tun-Yu Chang;Jeng-Bang Wang;Yu-Hsuan Tsai;Yu Tsao;Chia-Hsiang Yang","doi":"10.1109/TBCAS.2025.3625650","DOIUrl":"10.1109/TBCAS.2025.3625650","url":null,"abstract":"Brain-machine interface (BMI) technology enables the human brain to communicate directly with machines. This work presents a neural signal processor for real-time BMI, supporting translation from user’s speech attempt to sentences. By employing speech attempt detection, the energy consumption is reduced by 46% and the number of channels for speech attempt detection can be decreased from 128 to 16. The proposed weight encoding, which leverages both sparse encoding and mixed-precision arithmetic, reduces the off-chip memory size of the neural network by 80%. Computation reordering decreases the processing latency by 55%. For the partial sum caching technique, the number of neural network operations is reduced by 25%. The processing element (PE) array in the neural network engine exploits both input and weight sparsity to lower the processing latency by 95%. By using the proposed mixed-precision multiplier in the PE array, the area is reduced by 27% compared with the PE array with the full precision. In the beam search engine, the proposed approximate top-k selection architecture exhibits 16<inline-formula><tex-math>$boldsymbol{times}$</tex-math></inline-formula> fewer comparators. The neural signal processor achieves speech decoding with a phone error rate of 16.6% and a word error rate of 23.5%. Fabricated in 40-nm CMOS, the chip achieves the maximum communication rate of 200 words/min, which is 16.7-to-42.6<inline-formula><tex-math>$boldsymbol{times}$</tex-math></inline-formula> faster than the state-of-the-art designs. This work is able to decode up to 125,000 words, which is not achievable by prior works that can only decode up to 31 characters.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"19 6","pages":"1065-1077"},"PeriodicalIF":4.9,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145515417","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}

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