Pub Date : 2024-12-19DOI: 10.1109/TBCAS.2024.3519932
{"title":"2024 Index IEEE Transactions on Biomedical Circuits and Systems Vol. 18","authors":"","doi":"10.1109/TBCAS.2024.3519932","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3519932","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"1385-1410"},"PeriodicalIF":0.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10810376","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142858944","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}
Pub Date : 2024-12-11DOI: 10.1109/TBCAS.2024.3511193
{"title":"TechRxiv: Share Your Preprint Research with the World!","authors":"","doi":"10.1109/TBCAS.2024.3511193","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3511193","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"1382-1382"},"PeriodicalIF":0.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10783937","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810604","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}
Pub Date : 2024-12-11DOI: 10.1109/TBCAS.2024.3511176
{"title":"Blank Page","authors":"","doi":"10.1109/TBCAS.2024.3511176","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3511176","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"C4-C4"},"PeriodicalIF":0.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10783941","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810607","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}
Pub Date : 2024-12-11DOI: 10.1109/TBCAS.2024.3485302
{"title":"IEEE Transactions on Biomedical Circuits and Systems Publication Information","authors":"","doi":"10.1109/TBCAS.2024.3485302","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3485302","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10783938","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810609","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}
Pub Date : 2024-12-11DOI: 10.1109/TBCAS.2024.3511197
{"title":"Together, We are advance technology","authors":"","doi":"10.1109/TBCAS.2024.3511197","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3511197","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"1384-1384"},"PeriodicalIF":0.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10783940","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810605","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}
Pub Date : 2024-12-11DOI: 10.1109/TBCAS.2024.3511174
{"title":"IEEE Circuits and Systems Society Information","authors":"","doi":"10.1109/TBCAS.2024.3511174","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3511174","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10783933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810606","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}
{"title":"Guest Editorial: Selected Papers From the 2024 IEEE International Solid-State Circuits Conference","authors":"Alison Burdett;Maysam Ghovanloo;Roman Genov;Mehdi Kiani","doi":"10.1109/TBCAS.2024.3507312","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3507312","url":null,"abstract":"","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"1194-1196"},"PeriodicalIF":0.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10783936","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142798007","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}
Pub Date : 2024-11-11DOI: 10.1109/TBCAS.2024.3495652
Linran Zhao, Yan Gong, Raymond G Stephany, Wei Shi, Wen Li, Yaoyao Jia
This paper presents an application-specific integrated circuit (ASIC) fabricated using the CMOS 180 nm process to perform simultaneous neural recording and optogenetic stimulation. To perform effective optogenetic stimulation, the ASIC features an advanced switched-capacitor-based stimulation (SCS) driver, called voltage-boosting SCS (VB-SCS). The VB-SCS can drive LED with large current pulses up to 8 mA while reducing the required supply voltage by half, facilitating wireless power reception. To prevent saturation from stimulation-induced artifacts, the ASIC integrates a direct digitizing recording frontend with a high-resolution delta-sigma (ΔΣ) analog-to-digital converter (ADC) that directly digitizes neural signals with a large input dynamic range. This ΔΣ ADC involves a Gm-C integrator followed by a noise-shaping (NS) successive approximation register (SAR) quantizer. Measurement results indicate that this ΔΣ ADC-based direct digitizing frontend can tolerate large artifacts up to 300 mVPP while linearly digitizing neural signals with an effective number of bits (ENOB) of 11.4 bits, consuming 10.8 μW. The ASIC, together with its associated passive components, was assembled into a headstage for in vivo verification, successfully demonstrating the functionality of the ASIC.
{"title":"An Energy-Efficient and Artifact-Resilient ASIC for Simultaneous Neural Recording and Optogenetic Stimulation.","authors":"Linran Zhao, Yan Gong, Raymond G Stephany, Wei Shi, Wen Li, Yaoyao Jia","doi":"10.1109/TBCAS.2024.3495652","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3495652","url":null,"abstract":"<p><p>This paper presents an application-specific integrated circuit (ASIC) fabricated using the CMOS 180 nm process to perform simultaneous neural recording and optogenetic stimulation. To perform effective optogenetic stimulation, the ASIC features an advanced switched-capacitor-based stimulation (SCS) driver, called voltage-boosting SCS (VB-SCS). The VB-SCS can drive LED with large current pulses up to 8 mA while reducing the required supply voltage by half, facilitating wireless power reception. To prevent saturation from stimulation-induced artifacts, the ASIC integrates a direct digitizing recording frontend with a high-resolution delta-sigma (ΔΣ) analog-to-digital converter (ADC) that directly digitizes neural signals with a large input dynamic range. This ΔΣ ADC involves a Gm-C integrator followed by a noise-shaping (NS) successive approximation register (SAR) quantizer. Measurement results indicate that this ΔΣ ADC-based direct digitizing frontend can tolerate large artifacts up to 300 mV<sub>PP</sub> while linearly digitizing neural signals with an effective number of bits (ENOB) of 11.4 bits, consuming 10.8 μW. The ASIC, together with its associated passive components, was assembled into a headstage for in vivo verification, successfully demonstrating the functionality of the ASIC.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142635135","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}
High-throughput biosensor screening and optimization are critical for health and environmental monitoring applications to ensure rapid and accurate detection of biological and chemical targets. Traditional biosensor design and optimization methods involve labor-intensive processes, such as manual pipetting of large sample volumes, making them low throughput and inefficient for large-scale library screenings under various environmental and chemical conditions. We address these challenges by introducing a modular droplet microfluidic system embedded with custom CMOS integrated circuits (ICs) for impedance spectroscopy and bioluminescence detection. Fabricated in a 65 nm process, our CMOS ICs enable efficient droplet detection and analysis. We demonstrate successful sensing of luciferase enzyme-substrate reactions in nL-volume droplets. The impedance spectroscopy chip detects 4 nL droplets at 67 mm/s with a 45 pA resolution, while the luminescence detector senses optical signals from 38 nL droplets with a 6.7 nA/count resolution. We show real-time concurrent use of both detection methods within our hybrid platform for cross-validation. This system greatly advances conventional biosensor testing by increasing flexibility, scalability, and cost-efficiency.
{"title":"Integrated Real-Time CMOS Luminescence Sensing and Impedance Spectroscopy in Droplet Microfluidics","authors":"Qijun Liu;Diana Arguijo Mendoza;Alperen Yasar;Dilara Caygara;Aya Kassem;Douglas Densmore;Rabia Tugce Yazicigil","doi":"10.1109/TBCAS.2024.3491594","DOIUrl":"10.1109/TBCAS.2024.3491594","url":null,"abstract":"High-throughput biosensor screening and optimization are critical for health and environmental monitoring applications to ensure rapid and accurate detection of biological and chemical targets. Traditional biosensor design and optimization methods involve labor-intensive processes, such as manual pipetting of large sample volumes, making them low throughput and inefficient for large-scale library screenings under various environmental and chemical conditions. We address these challenges by introducing a modular droplet microfluidic system embedded with custom CMOS integrated circuits (ICs) for impedance spectroscopy and bioluminescence detection. Fabricated in a 65 nm process, our CMOS ICs enable efficient droplet detection and analysis. We demonstrate successful sensing of luciferase enzyme-substrate reactions in nL-volume droplets. The impedance spectroscopy chip detects 4 nL droplets at 67 mm/s with a 45 pA resolution, while the luminescence detector senses optical signals from 38 nL droplets with a 6.7 nA/count resolution. We show real-time concurrent use of both detection methods within our hybrid platform for cross-validation. This system greatly advances conventional biosensor testing by increasing flexibility, scalability, and cost-efficiency.","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"18 6","pages":"1233-1252"},"PeriodicalIF":0.0,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142607700","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}
Pub Date : 2024-11-04DOI: 10.1109/TBCAS.2024.3487782
Anirudh Kumar Parag, Bogdan C Raducanu, Oguz Kaan Erden, Stefano Stanzione, Fabian Beutel, Chinmay Pendse, Chris Van Hoof, Nick Van Helleputte, Georges Gielen
Ultrasound (US) as a wireless power transfer methodology has drawn considerable attention from the implantable medical devices (IMD) research community. Beamforming (BF) using an external transducer array patch (ETAP) has been proposed as a robust localization scheme to find a mm-sized IMD inside the human body. However, for applications focusing on deep and shallow IMDs, optimum resource utilization at the ETAP is a major power efficiency concern for energy-constrained wearable patches. Moreover, misalignment tolerance due to IMD movements (respiratory and patient ambulatory reasons) relative to the ETAP remains a challenge. This paper presents an energy-efficient method to localize a mm-sized IMD through the dynamic selection of a sub-array within the ETAP. It is fully adaptive to the heterogeneity of the media and requires no a priori knowledge of the IMD. To improve the tolerance to IMD movements, tracking is implemented by adding and subtracting elements on the sub-array such that the sub-array electrically follows the IMD movement. Furthermore, it is shown that a minimum sampling frequency of 10X the US frequency can improve the tolerance to random noise. K-wave simulations in MATLAB are performed in different heterogenous, scattering biological media to prove the efficacy of the proposed method over standard BF methods. Measurement results in heterogenous scattering media consisting of a 3D-printed human ribs phantom and a partially blocking multipath cancellous bone phantom show an energy efficiency improvement of 10.53X and 14.4X compared to the delay-and-sum beamforming method and the unfocused transmission employing all the elements of the ETAP, respectively.
{"title":"Dynamic sub-array selection-based energy-efficient localization and tracking method to power implanted medical devices in scattering heterogenous media employing ultrasound.","authors":"Anirudh Kumar Parag, Bogdan C Raducanu, Oguz Kaan Erden, Stefano Stanzione, Fabian Beutel, Chinmay Pendse, Chris Van Hoof, Nick Van Helleputte, Georges Gielen","doi":"10.1109/TBCAS.2024.3487782","DOIUrl":"https://doi.org/10.1109/TBCAS.2024.3487782","url":null,"abstract":"<p><p>Ultrasound (US) as a wireless power transfer methodology has drawn considerable attention from the implantable medical devices (IMD) research community. Beamforming (BF) using an external transducer array patch (ETAP) has been proposed as a robust localization scheme to find a mm-sized IMD inside the human body. However, for applications focusing on deep and shallow IMDs, optimum resource utilization at the ETAP is a major power efficiency concern for energy-constrained wearable patches. Moreover, misalignment tolerance due to IMD movements (respiratory and patient ambulatory reasons) relative to the ETAP remains a challenge. This paper presents an energy-efficient method to localize a mm-sized IMD through the dynamic selection of a sub-array within the ETAP. It is fully adaptive to the heterogeneity of the media and requires no a priori knowledge of the IMD. To improve the tolerance to IMD movements, tracking is implemented by adding and subtracting elements on the sub-array such that the sub-array electrically follows the IMD movement. Furthermore, it is shown that a minimum sampling frequency of 10X the US frequency can improve the tolerance to random noise. K-wave simulations in MATLAB are performed in different heterogenous, scattering biological media to prove the efficacy of the proposed method over standard BF methods. Measurement results in heterogenous scattering media consisting of a 3D-printed human ribs phantom and a partially blocking multipath cancellous bone phantom show an energy efficiency improvement of 10.53X and 14.4X compared to the delay-and-sum beamforming method and the unfocused transmission employing all the elements of the ETAP, respectively.</p>","PeriodicalId":94031,"journal":{"name":"IEEE transactions on biomedical circuits and systems","volume":"PP ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577324","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号