Pub Date : 2010-11-03DOI: 10.1109/BIOCAS.2010.5709560
Mohsen Judy, A. M. Sodagar, R. Lotfi
A bandwidth-efficient technique for nonlinearly converting analog neural signals into digital is presented to be used in implantable neural recording microsystems. It is shown that the choice of a proper nonlinear quantization function helps reduce the outgoing bit rate carrying the recorded neural data. Another major benefit of digitizing neural signals using a proper nonlinear analog-to-digital converter (ADC) is the improvement in the signal-to-noise ratio (SNR) of the signal. The 8-b nonlinear anti-logarithmic ADC reported in this paper digitizes large action potentials with 10b resolution, while quantizing the small background noise with a resolution of as low as 3b. The circuit was designed and simulated in a 0.18-um CMOS process. According to the experimental results, SNR of the neural signal increases from 5.11 before digitization to 22 after being digitized using the proposed ADC approach.
提出了一种将模拟神经信号非线性转换为数字信号的带宽高效技术，用于植入式神经记录微系统。结果表明，选择适当的非线性量化函数有助于降低携带记录神经数据的输出比特率。使用适当的非线性模数转换器(ADC)对神经信号进行数字化的另一个主要好处是提高信号的信噪比(SNR)。本文报道的8-b非线性抗对数ADC以10b的分辨率对大动作电位进行数字化，同时以低至3b的分辨率对小背景噪声进行量化。在0.18 um CMOS工艺下设计并仿真了该电路。实验结果表明，采用该方法后，神经信号的信噪比由数字化前的5.11提高到数字化后的22。
{"title":"A nonlinear signal-specific ADC for efficient neural recording","authors":"Mohsen Judy, A. M. Sodagar, R. Lotfi","doi":"10.1109/BIOCAS.2010.5709560","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709560","url":null,"abstract":"A bandwidth-efficient technique for nonlinearly converting analog neural signals into digital is presented to be used in implantable neural recording microsystems. It is shown that the choice of a proper nonlinear quantization function helps reduce the outgoing bit rate carrying the recorded neural data. Another major benefit of digitizing neural signals using a proper nonlinear analog-to-digital converter (ADC) is the improvement in the signal-to-noise ratio (SNR) of the signal. The 8-b nonlinear anti-logarithmic ADC reported in this paper digitizes large action potentials with 10b resolution, while quantizing the small background noise with a resolution of as low as 3b. The circuit was designed and simulated in a 0.18-um CMOS process. According to the experimental results, SNR of the neural signal increases from 5.11 before digitization to 22 after being digitized using the proposed ADC approach.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130616372","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709611
C. Sawigun, W. Ngamkham, W. Serdijn
This paper presents the design of a sub-threshold CMOS peak-instant detector to be used in a phase-locking peak-picking (PL-PP) bionic ear (BE) processor. The detector is formed by a current sample and hold circuit and a voltage comparator to perform the detection of occurrences of maximum and minimum values of the input. Circuit simulation results using CMOS 0.35 μm AMIS technology confirm that the proposed detector can be operated from a 1.2 V supply and consumes less than 1μW static power for detecting a 5kHz input signal (maximum frequency of the processor). For lower input frequencies the power consumption can be scaled down to further reduce the BE processor's power consumption.
{"title":"An ultra low-power peak-instant detector for a peak picking cochlear implant processor","authors":"C. Sawigun, W. Ngamkham, W. Serdijn","doi":"10.1109/BIOCAS.2010.5709611","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709611","url":null,"abstract":"This paper presents the design of a sub-threshold CMOS peak-instant detector to be used in a phase-locking peak-picking (PL-PP) bionic ear (BE) processor. The detector is formed by a current sample and hold circuit and a voltage comparator to perform the detection of occurrences of maximum and minimum values of the input. Circuit simulation results using CMOS 0.35 μm AMIS technology confirm that the proposed detector can be operated from a 1.2 V supply and consumes less than 1μW static power for detecting a 5kHz input signal (maximum frequency of the processor). For lower input frequencies the power consumption can be scaled down to further reduce the BE processor's power consumption.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"10 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120857227","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709624
D. Truong, B. Baas
Ultrasound remains a popular imaging modality due to its mobility and cost-effectiveness. As general purpose computing and DSPs are entering an era of multi-core architectures, the potential for parallel performance gains are significant when used properly. This work explores the possibility of using a massively parallel processor array to meet realtime throughputs for mid-/back-end ultrasound processing. A many-core array of simple DSP cores, shared memories, and an FFT processor is shown to dissipate 87.79 mW for B-mode, 33.20 mW for color flow, and 29.24 mW for spectral doppler, while achieving a frame rate of 37.6 fps for B-mode and 12.5 fps for color flow.
{"title":"Massively parallel processor array for mid-/back-end ultrasound signal processing","authors":"D. Truong, B. Baas","doi":"10.1109/BIOCAS.2010.5709624","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709624","url":null,"abstract":"Ultrasound remains a popular imaging modality due to its mobility and cost-effectiveness. As general purpose computing and DSPs are entering an era of multi-core architectures, the potential for parallel performance gains are significant when used properly. This work explores the possibility of using a massively parallel processor array to meet realtime throughputs for mid-/back-end ultrasound processing. A many-core array of simple DSP cores, shared memories, and an FFT processor is shown to dissipate 87.79 mW for B-mode, 33.20 mW for color flow, and 29.24 mW for spectral doppler, while achieving a frame rate of 37.6 fps for B-mode and 12.5 fps for color flow.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129880859","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709559
M. K. Awais, J. M. Andrew
Modern microelectrode arrays acquire neural signals from hundreds of neurons in parallel that are subsequently processed for spike sorting. It is important to identify, extract and transmit appropriate features that allow accurate spike sorting while using minimum computational resources. This paper describes a new set of spike sorting features, explicitly framed to be computationally efficient and shown to outperform PCA based spike sorting. A hardware friendly architecture, feasible for implantation, is also presented for detecting neural spikes and extracting features to be transmitted for off chip spike classification.
{"title":"On-chip feature extraction for spike sorting in high density implantable neural recording systems","authors":"M. K. Awais, J. M. Andrew","doi":"10.1109/BIOCAS.2010.5709559","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709559","url":null,"abstract":"Modern microelectrode arrays acquire neural signals from hundreds of neurons in parallel that are subsequently processed for spike sorting. It is important to identify, extract and transmit appropriate features that allow accurate spike sorting while using minimum computational resources. This paper describes a new set of spike sorting features, explicitly framed to be computationally efficient and shown to outperform PCA based spike sorting. A hardware friendly architecture, feasible for implantation, is also presented for detecting neural spikes and extracting features to be transmitted for off chip spike classification.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115898273","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709592
S. Carrara, Michele Daniel Torre, A. Cavallini, D. De Venuto, G. De Micheli
Robust and reliable measurements in electrochemical biosensing of molecules are crucial for personalized medicine. Electrochemical sensors based on cytochrome P450 can detect the large majority of drugs commonly used in pharmacological treatments. The same cytochrome can detect different substrates; each of them changes the electrochemical response of the enzyme in a specific manner. Our system exploits the measure of electrical potential to identify the drug type, while current measurements decode the drug concentration. Since potential and current are affected by pH and temperature, and since variations occur in the patient samples, we propose a novel design for multiplexing biosensing with pH and temperature control, which ensures more precise measurements for drugs identification and their quantification.
{"title":"Multiplexing pH and temperature in a molecular biosensor","authors":"S. Carrara, Michele Daniel Torre, A. Cavallini, D. De Venuto, G. De Micheli","doi":"10.1109/BIOCAS.2010.5709592","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709592","url":null,"abstract":"Robust and reliable measurements in electrochemical biosensing of molecules are crucial for personalized medicine. Electrochemical sensors based on cytochrome P450 can detect the large majority of drugs commonly used in pharmacological treatments. The same cytochrome can detect different substrates; each of them changes the electrochemical response of the enzyme in a specific manner. Our system exploits the measure of electrical potential to identify the drug type, while current measurements decode the drug concentration. Since potential and current are affected by pH and temperature, and since variations occur in the patient samples, we propose a novel design for multiplexing biosensing with pH and temperature control, which ensures more precise measurements for drugs identification and their quantification.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123920816","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709570
Cheng-Zhou Zhan, Kai Chang, Yu-Hao Chen, Pai-Chi Li, A. Wu
Color Doppler processing in the ultrasound imaging systems is mainly used to observe the blood flow in the region of interest. The desired blood signal will be greatly affected by the speckle noises, and the major design issues are to eliminate these kinds of noises effectively. In this work, we propose the time-domain (1) motion-tracking adaptive persistence and spatial-domain (2) adaptive-size median filter for effectively eliminating the speckle noises, respectively. The proposed two filters have individually 2~3 dB better performance than the referenced algorithms, and the proposed adaptive de-speckle filters can also work together in the same system to obtain even better performances. At last, the proposed signal-processing algorithms are implemented on the multi-core platform, and the property of parallel processing significantly accelerates the computation.
{"title":"Motion-tracking adaptive persistence and adaptive-size median filter for color Doppler processing in ultrasound systems on multicore platform","authors":"Cheng-Zhou Zhan, Kai Chang, Yu-Hao Chen, Pai-Chi Li, A. Wu","doi":"10.1109/BIOCAS.2010.5709570","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709570","url":null,"abstract":"Color Doppler processing in the ultrasound imaging systems is mainly used to observe the blood flow in the region of interest. The desired blood signal will be greatly affected by the speckle noises, and the major design issues are to eliminate these kinds of noises effectively. In this work, we propose the time-domain (1) motion-tracking adaptive persistence and spatial-domain (2) adaptive-size median filter for effectively eliminating the speckle noises, respectively. The proposed two filters have individually 2~3 dB better performance than the referenced algorithms, and the proposed adaptive de-speckle filters can also work together in the same system to obtain even better performances. At last, the proposed signal-processing algorithms are implemented on the multi-core platform, and the property of parallel processing significantly accelerates the computation.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125991874","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709617
F. Robert-Inacio, Rémy Scaramuzzino, Q. Stainer, Edith Kussener-Combier
In biomedical field, electronic eyes are of a great interest to provide visual information to blind people. Some of them are built to be plugged to the optical nerve and others to the visual cortex itself. In our case the electronic eye processes images in order to reproduce the retina behavior, as well as some of the visual cortex abilities. The main task presented in this paper deals with data acquisition and restitution. In other words the image acquired by a classical CCD is re-sampled in order to reproduce cone acquisition. Cones are small photo-receptors located on the retina perpendicularly to the visual axis. As cones are dedicated to color perception the presented method shows how to process color data in order to obtain a radial-sampled image. In this way the amount of data decreases considerably and the image processing to be achieved later is fastened up.
{"title":"Biologically inspired image sampling for electronic eye","authors":"F. Robert-Inacio, Rémy Scaramuzzino, Q. Stainer, Edith Kussener-Combier","doi":"10.1109/BIOCAS.2010.5709617","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709617","url":null,"abstract":"In biomedical field, electronic eyes are of a great interest to provide visual information to blind people. Some of them are built to be plugged to the optical nerve and others to the visual cortex itself. In our case the electronic eye processes images in order to reproduce the retina behavior, as well as some of the visual cortex abilities. The main task presented in this paper deals with data acquisition and restitution. In other words the image acquired by a classical CCD is re-sampled in order to reproduce cone acquisition. Cones are small photo-receptors located on the retina perpendicularly to the visual axis. As cones are dedicated to color perception the presented method shows how to process color data in order to obtain a radial-sampled image. In this way the amount of data decreases considerably and the image processing to be achieved later is fastened up.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130223479","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709565
D. Teichmann, J. Foussier, S. Leonhardt
Respiratory activity correlates with the conductivity distribution within the thorax. The change in conductivity can be monitored by impedance measurements based on eddy current induction without any need for contact between instrumentation and body. A system for magnetic induction measurements of the thorax using a single sensor-coil is presented. In contrast to most other known single coil respiration monitoring systems, the signal is amplitude and not frequency modulated. This renders the possibility of measuring with constant excitation frequencies.
{"title":"Respiration monitoring based on magnetic induction using a single coil","authors":"D. Teichmann, J. Foussier, S. Leonhardt","doi":"10.1109/BIOCAS.2010.5709565","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709565","url":null,"abstract":"Respiratory activity correlates with the conductivity distribution within the thorax. The change in conductivity can be monitored by impedance measurements based on eddy current induction without any need for contact between instrumentation and body. A system for magnetic induction measurements of the thorax using a single sensor-coil is presented. In contrast to most other known single coil respiration monitoring systems, the signal is amplitude and not frequency modulated. This renders the possibility of measuring with constant excitation frequencies.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126391476","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709586
A. Eftekhar, Sivylla E. Paraskevopoulou, T. Constandinou
In this paper, we review the state-of-the-art in neural interface recording architectures. Through this we identify schemes which show the trade-off between data information quality (lossiness), computation (i.e. power and area requirements) and the number of channels. We further extend these tradeoffs by band-limiting the signal through reducing the front-end amplifier bandwidth. We therefore explore the possibility of band-limiting the spectral content of recorded neural signals (to save power) and investigate the effect this has on subsequent processing (spike detection accuracy). We identify the spike detection method most robust to such signals, optimize the threshold levels and modify this to exploit such a strategy.
{"title":"Towards a next generation neural interface: Optimizing power, bandwidth and data quality","authors":"A. Eftekhar, Sivylla E. Paraskevopoulou, T. Constandinou","doi":"10.1109/BIOCAS.2010.5709586","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709586","url":null,"abstract":"In this paper, we review the state-of-the-art in neural interface recording architectures. Through this we identify schemes which show the trade-off between data information quality (lossiness), computation (i.e. power and area requirements) and the number of channels. We further extend these tradeoffs by band-limiting the signal through reducing the front-end amplifier bandwidth. We therefore explore the possibility of band-limiting the spectral content of recorded neural signals (to save power) and investigate the effect this has on subsequent processing (spike detection accuracy). We identify the spike detection method most robust to such signals, optimize the threshold levels and modify this to exploit such a strategy.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133403275","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 : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709585
A. Rodríguez-Pérez, J. Ruiz-Amaya, Oscar Guerra, M. Delgado-Restituto
This paper describes the architecture of a neural spike recording channel with feature extraction capabilities and presents the design of one of its key elements, a reconfigurable 8-bit ADC. The ADC can be programmed for different conversion rates and embeds a 0–18dB programmable gain amplifier with discrete gain steps of 3dB. Simulation results from extracted layout of the ADC, designed in a 130nm CMOS technology, obtain almost 8-bit ENOB at 22.2kS/s and 90kS/s, with a power consumption of 500nW and 1.8μW, respectively.
{"title":"A reconfigurable neural spike recording channel with feature extraction capabilities","authors":"A. Rodríguez-Pérez, J. Ruiz-Amaya, Oscar Guerra, M. Delgado-Restituto","doi":"10.1109/BIOCAS.2010.5709585","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709585","url":null,"abstract":"This paper describes the architecture of a neural spike recording channel with feature extraction capabilities and presents the design of one of its key elements, a reconfigurable 8-bit ADC. The ADC can be programmed for different conversion rates and embeds a 0–18dB programmable gain amplifier with discrete gain steps of 3dB. Simulation results from extracted layout of the ADC, designed in a 130nm CMOS technology, obtain almost 8-bit ENOB at 22.2kS/s and 90kS/s, with a power consumption of 500nW and 1.8μW, respectively.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"569 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113998164","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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