Pub Date : 2015-10-01DOI: 10.1109/TBCAS.2015.2498758
P. Georgiou, W. Fang, S. Sonkusale
The papers in this special issue were presented at the 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS 2014) on Breakthrough for Distributed Diagnostic and Therapy, that was held October 22–24, 2014, at EPFL, Lausanne, Switzerland.
{"title":"Guest Editorial - Special Issue on Selected Papers From IEEE BioCAS 2014","authors":"P. Georgiou, W. Fang, S. Sonkusale","doi":"10.1109/TBCAS.2015.2498758","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2498758","url":null,"abstract":"The papers in this special issue were presented at the 2014 IEEE Biomedical Circuits and Systems Conference (BioCAS 2014) on Breakthrough for Distributed Diagnostic and Therapy, that was held October 22–24, 2014, at EPFL, Lausanne, Switzerland.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"9 5 1","pages":"605-6"},"PeriodicalIF":5.1,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2498758","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62964978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-09-22DOI: 10.1109/TBCAS.2015.2483618
Yi Chen, Enyi Yao, A. Basu
Currently, state-of-the-art motor intention decoding algorithms in brain-machine interfaces are mostly implemented on a PC and consume significant amount of power. A machine learning coprocessor in 0.35- μm CMOS for the motor intention decoding in the brain-machine interfaces is presented in this paper. Using Extreme Learning Machine algorithm and low-power analog processing, it achieves an energy efficiency of 3.45 pJ/MAC at a classification rate of 50 Hz. The learning in second stage and corresponding digitally stored coefficients are used to increase robustness of the core analog processor. The chip is verified with neural data recorded in monkey finger movements experiment, achieving a decoding accuracy of 99.3% for movement type. The same coprocessor is also used to decode time of movement from asynchronous neural spikes. With time-delayed feature dimension enhancement, the classification accuracy can be increased by 5% with limited number of input channels. Further, a sparsity promoting training scheme enables reduction of number of programmable weights by ≈ 2X.
{"title":"A 128-Channel Extreme Learning Machine-Based Neural Decoder for Brain Machine Interfaces","authors":"Yi Chen, Enyi Yao, A. Basu","doi":"10.1109/TBCAS.2015.2483618","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2483618","url":null,"abstract":"Currently, state-of-the-art motor intention decoding algorithms in brain-machine interfaces are mostly implemented on a PC and consume significant amount of power. A machine learning coprocessor in 0.35- μm CMOS for the motor intention decoding in the brain-machine interfaces is presented in this paper. Using Extreme Learning Machine algorithm and low-power analog processing, it achieves an energy efficiency of 3.45 pJ/MAC at a classification rate of 50 Hz. The learning in second stage and corresponding digitally stored coefficients are used to increase robustness of the core analog processor. The chip is verified with neural data recorded in monkey finger movements experiment, achieving a decoding accuracy of 99.3% for movement type. The same coprocessor is also used to decode time of movement from asynchronous neural spikes. With time-delayed feature dimension enhancement, the classification accuracy can be increased by 5% with limited number of input channels. Further, a sparsity promoting training scheme enables reduction of number of programmable weights by ≈ 2X.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"10 1","pages":"679-692"},"PeriodicalIF":5.1,"publicationDate":"2015-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2483618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62965145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-08-01DOI: 10.1109/TBCAS.2015.2472315
R. Sarpeshkar
{"title":"Guest Editorial - Special Issue on Synthetic Biology","authors":"R. Sarpeshkar","doi":"10.1109/TBCAS.2015.2472315","DOIUrl":"https://doi.org/10.1109/TBCAS.2015.2472315","url":null,"abstract":"","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"9 4 1","pages":"449-52"},"PeriodicalIF":5.1,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2015.2472315","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62964420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Feeding and swallowing disorders are relatively common in early infancy. In Clinical, it shows negative impacts on growth and neurodevelopmental, therefore it has become a high risk of neurodevelopmental delays in preterm infants. Oral feeding that requires suckling, swallowing, and breathing coordination, and it is the most complex sensorimotor process for the newborn infant. Currently, both preterm infant's oral feeding disorders and severity are dependent on subjective clinical experience. Directly monitoring sucking-swallowing-breathing activities of oral is difficult for preterm infants. In this study, a wireless monitoring system for oral feeding of preterm infants was developed to monitor the events of sucking-swallowing-breathing activities continuously and objectively. Finally, the experimental results show that the proposed system can detect the events of sucking, swallowing, and breathing activities effectively.
{"title":"Wireless monitoring system for oral-feeding evaluation of preterm infants","authors":"Chen-An Wang, Yi-Chien Liao, Pei-Jung Wu, Yu-Lin Wang, Bor-Shing Lin, Bor-Shyh Lin","doi":"10.1109/BioCAS.2014.6981713","DOIUrl":"https://doi.org/10.1109/BioCAS.2014.6981713","url":null,"abstract":"Feeding and swallowing disorders are relatively common in early infancy. In Clinical, it shows negative impacts on growth and neurodevelopmental, therefore it has become a high risk of neurodevelopmental delays in preterm infants. Oral feeding that requires suckling, swallowing, and breathing coordination, and it is the most complex sensorimotor process for the newborn infant. Currently, both preterm infant's oral feeding disorders and severity are dependent on subjective clinical experience. Directly monitoring sucking-swallowing-breathing activities of oral is difficult for preterm infants. In this study, a wireless monitoring system for oral feeding of preterm infants was developed to monitor the events of sucking-swallowing-breathing activities continuously and objectively. Finally, the experimental results show that the proposed system can detect the events of sucking, swallowing, and breathing activities effectively.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"4 1","pages":"264-267"},"PeriodicalIF":5.1,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/BioCAS.2014.6981713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62153256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 2013 IEEE Biomedical Circuits and Systems Conference (BioCAS 2013) on Advancing Healthcare Technology, October 31-November 2, 2013, Rotterdam, Netherlands.","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"8 5","pages":"605-750"},"PeriodicalIF":5.1,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"34304001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-03-06DOI: 10.1109/ISSCC.2014.6757453
Po-Hung Kuo, J. Hsieh, Yi-Chun Huang, Yu-Jie Huang, Rong-Da Tsai, Tao Wang, Hung-Wei Chiu, Shey-Shi Lu
As implantable medical CMOS devices become a reality [1], motion control of such implantable devices has become the next challenge in the advanced integrated micro-system domain. With integrated sensors and a controllable propulsion mechanism, a micro-system will be able to perform tumor scan, drug delivery, neuron stimulation, bio-test, etc, in a revolutionary way and with minimum injury. Such devices are especially suitable for human hollow organs, such as urinary bladder and stomach. Motivated by the art reported in ISSCC 2012 [2], we demonstrate a remotely-controlled locomotive CMOS IC which is realized in TSMC 0.35μm technology. As illustrated in Fig. 18.7.1, a bare CMOS chip flipped on a liquid surface can be moved to the desired position without any wire connections. Instead of Lorentz forces [2], this chip utilizes the gas pressure resulting from electrolytic bubbles as the propulsive force. By appointing voltages to the on-chip electrolysis electrodes, one can decide the electrolysis location and thereby control the bubbles emissions as well as the direction of motion. With power management circuits, wireless receiver and micro-control unit (MCU), the received signal can be exploited as the movement control as well as wireless power. Experiments show a moving speed of 0.3mm/s of this chip. The total size is 21.2mm2 and the power consumption of the integrated circuits and the electrolysis electrodes are 125.4μW and 82μW, respectively.
{"title":"18.7 A remotely controlled locomotive IC driven by electrolytic bubbles and wireless powering","authors":"Po-Hung Kuo, J. Hsieh, Yi-Chun Huang, Yu-Jie Huang, Rong-Da Tsai, Tao Wang, Hung-Wei Chiu, Shey-Shi Lu","doi":"10.1109/ISSCC.2014.6757453","DOIUrl":"https://doi.org/10.1109/ISSCC.2014.6757453","url":null,"abstract":"As implantable medical CMOS devices become a reality [1], motion control of such implantable devices has become the next challenge in the advanced integrated micro-system domain. With integrated sensors and a controllable propulsion mechanism, a micro-system will be able to perform tumor scan, drug delivery, neuron stimulation, bio-test, etc, in a revolutionary way and with minimum injury. Such devices are especially suitable for human hollow organs, such as urinary bladder and stomach. Motivated by the art reported in ISSCC 2012 [2], we demonstrate a remotely-controlled locomotive CMOS IC which is realized in TSMC 0.35μm technology. As illustrated in Fig. 18.7.1, a bare CMOS chip flipped on a liquid surface can be moved to the desired position without any wire connections. Instead of Lorentz forces [2], this chip utilizes the gas pressure resulting from electrolytic bubbles as the propulsive force. By appointing voltages to the on-chip electrolysis electrodes, one can decide the electrolysis location and thereby control the bubbles emissions as well as the direction of motion. With power management circuits, wireless receiver and micro-control unit (MCU), the received signal can be exploited as the movement control as well as wireless power. Experiments show a moving speed of 0.3mm/s of this chip. The total size is 21.2mm2 and the power consumption of the integrated circuits and the electrolysis electrodes are 125.4μW and 82μW, respectively.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"1 1","pages":"322-323"},"PeriodicalIF":5.1,"publicationDate":"2014-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ISSCC.2014.6757453","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62165926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-05-20DOI: 10.1109/ISCAS.2012.6271420
I. Williams, T. Constandinou
This paper presents an 8 channel energy-efficient neural stimulator for generating charge-balanced asymmetric pulses. Power consumption is reduced by implementing a fully-integrated DC-DC converter that uses a reconfigurable switched capacitor topology to provide 4 output voltages for Dynamic Voltage Scaling (DVS). DC conversion efficiencies of up to 82% are achieved using integrated capacitances of under 1 nF and the DVS approach offers power savings of up to 50% compared to the front end of a typical current controlled neural stimulator. A novel charge balancing method is implemented which has a low level of accuracy on a single pulse and a much higher accuracy over a series of pulses. The method used is robust to process and component variation and does not require any initial or ongoing calibration. Measured results indicate that the charge imbalance is typically between 0.05%-0.15% of charge injected for a series of pulses. Ex-vivo experiments demonstrate the viability in using this circuit for neural activation. The circuit has been implemented in a commercially-available 0.18 μm HV CMOS technology and occupies a core die area of approximately 2.8 mm2 for an 8 channel implementation.
{"title":"An Energy-Efficient, Dynamic Voltage Scaling Neural Stimulator for a Proprioceptive Prosthesis","authors":"I. Williams, T. Constandinou","doi":"10.1109/ISCAS.2012.6271420","DOIUrl":"https://doi.org/10.1109/ISCAS.2012.6271420","url":null,"abstract":"This paper presents an 8 channel energy-efficient neural stimulator for generating charge-balanced asymmetric pulses. Power consumption is reduced by implementing a fully-integrated DC-DC converter that uses a reconfigurable switched capacitor topology to provide 4 output voltages for Dynamic Voltage Scaling (DVS). DC conversion efficiencies of up to 82% are achieved using integrated capacitances of under 1 nF and the DVS approach offers power savings of up to 50% compared to the front end of a typical current controlled neural stimulator. A novel charge balancing method is implemented which has a low level of accuracy on a single pulse and a much higher accuracy over a series of pulses. The method used is robust to process and component variation and does not require any initial or ongoing calibration. Measured results indicate that the charge imbalance is typically between 0.05%-0.15% of charge injected for a series of pulses. Ex-vivo experiments demonstrate the viability in using this circuit for neural activation. The circuit has been implemented in a commercially-available 0.18 μm HV CMOS technology and occupies a core die area of approximately 2.8 mm2 for an 8 channel implementation.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"7 1","pages":"129-139"},"PeriodicalIF":5.1,"publicationDate":"2012-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ISCAS.2012.6271420","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62145716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Proceedings of the 2011 IEEE International Symposium on Circuits and Systems (ISCAS 2011), May 15-18, 2011, Rio de Janeiro, Brazil.","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"6 2","pages":"85-187"},"PeriodicalIF":5.1,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"32547239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-03-02DOI: 10.1109/TBCAS.2013.2271727
M. A. Miled, G. Massicotte, M. Sawan
We present in this paper a new Lab-on-Chip (LoC) architecture for dielectrophoresis-based cell manipulation, detection, and capacitive measurement. The proposed LoC is built around a CMOS full-custom chip and a microfluidic structure. The CMOS chip is used to deliver all parameters required to control the dielectrophoresis (DEP) features such as frequency, phase, and amplitude of signals spread on in-channel electrodes of the LoC. It is integrated to the LoC and experimental results are related to micro and nano particles manipulation and detection in a microfluidic platform. The proposed microsystem includes an on-chip 27-bit frequency divider, a digital phase controller with a 3.6° phase shift resolution and a 2.5 V dynamic range. The sensing module is composed of a 3 × 3 capacitive sensor array with 10 fF per mV sensitivity, and a dynamic range of 1.5 V. The obtained results show an efficient nano and micro-particles (PC05N, PA04N and PS03N) separation based on frequency segregation with low voltages less than 1.7 V and a fully integrated and reconfigurable system.
{"title":"Dielectrophoresis-Based Integrated Lab-on-Chip for Nano and Micro-Particles Manipulation and Capacitive Detection","authors":"M. A. Miled, G. Massicotte, M. Sawan","doi":"10.1109/TBCAS.2013.2271727","DOIUrl":"https://doi.org/10.1109/TBCAS.2013.2271727","url":null,"abstract":"We present in this paper a new Lab-on-Chip (LoC) architecture for dielectrophoresis-based cell manipulation, detection, and capacitive measurement. The proposed LoC is built around a CMOS full-custom chip and a microfluidic structure. The CMOS chip is used to deliver all parameters required to control the dielectrophoresis (DEP) features such as frequency, phase, and amplitude of signals spread on in-channel electrodes of the LoC. It is integrated to the LoC and experimental results are related to micro and nano particles manipulation and detection in a microfluidic platform. The proposed microsystem includes an on-chip 27-bit frequency divider, a digital phase controller with a 3.6° phase shift resolution and a 2.5 V dynamic range. The sensing module is composed of a 3 × 3 capacitive sensor array with 10 fF per mV sensitivity, and a dynamic range of 1.5 V. The obtained results show an efficient nano and micro-particles (PC05N, PA04N and PS03N) separation based on frequency segregation with low voltages less than 1.7 V and a fully integrated and reconfigurable system.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"6 1","pages":"120-132"},"PeriodicalIF":5.1,"publicationDate":"2012-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/TBCAS.2013.2271727","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62964615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2011-05-15DOI: 10.1109/ISCAS.2011.5937741
Brian Goldstein, Dongsoo Kim, A. Rottigni, Jian Xu, T. Vanderlick, E. Culurciello
We present a micro-chip implementation of a low current measurement system for biomedical applications using capacitive feedback that exhibits 190 fA of RMS noise in a 1 kHz bandwidth. The sampling rate is selectable up to 100 kHz. When measuring the amplifier noise with a 10 G Ω resistor and a 47 pF capacitor at the input, typical of cell membrane capacitance in DNA and patch clamp experiments, the measured RMS noise was 2.44 pA on a 50 pA signal in a 10 kHz bandwidth. Two channels were implemented on 630 × 440 μm2 using a 0.5- μm 3-metal 2-poly CMOS process. Each channel consumes 1.5 mW of power from a 3.3 V supply. We measured the characteristics of an artificial lipid bilayer similar to the ones used in DNA sequencing experiments via nanopores.
{"title":"CMOS Low Current Measurement System for Biomedical Applications","authors":"Brian Goldstein, Dongsoo Kim, A. Rottigni, Jian Xu, T. Vanderlick, E. Culurciello","doi":"10.1109/ISCAS.2011.5937741","DOIUrl":"https://doi.org/10.1109/ISCAS.2011.5937741","url":null,"abstract":"We present a micro-chip implementation of a low current measurement system for biomedical applications using capacitive feedback that exhibits 190 fA of RMS noise in a 1 kHz bandwidth. The sampling rate is selectable up to 100 kHz. When measuring the amplifier noise with a 10 G Ω resistor and a 47 pF capacitor at the input, typical of cell membrane capacitance in DNA and patch clamp experiments, the measured RMS noise was 2.44 pA on a 50 pA signal in a 10 kHz bandwidth. Two channels were implemented on 630 × 440 μm2 using a 0.5- μm 3-metal 2-poly CMOS process. Each channel consumes 1.5 mW of power from a 3.3 V supply. We measured the characteristics of an artificial lipid bilayer similar to the ones used in DNA sequencing experiments via nanopores.","PeriodicalId":13151,"journal":{"name":"IEEE Transactions on Biomedical Circuits and Systems","volume":"6 1","pages":"111-119"},"PeriodicalIF":5.1,"publicationDate":"2011-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/ISCAS.2011.5937741","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"62145702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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