Pub Date : 2010-11-01DOI: 10.1109/BIOCAS.2010.5709627
K. Mazurek, B. J. Holinski, D. Everaert, R. Stein, V. Mushahwar, R. Etienne-Cummings
A proposed Locomotion Processing Unit (LPU) is described for generating stimulation patterns for restoring walking in individuals with spinal cord injury (SCI). The LPU operates using sensory and timing based control providing feed forward and feedback information. By breaking down different components of locomotion into states, the LPU activates different muscle groups, or synergies, to recreate the desired functional movements. The LPU circuitry was simulated and compared against another controller designed to restore locomotion in an anesthetized cat to validate its performance.
{"title":"Locomotion Processing Unit","authors":"K. Mazurek, B. J. Holinski, D. Everaert, R. Stein, V. Mushahwar, R. Etienne-Cummings","doi":"10.1109/BIOCAS.2010.5709627","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709627","url":null,"abstract":"A proposed Locomotion Processing Unit (LPU) is described for generating stimulation patterns for restoring walking in individuals with spinal cord injury (SCI). The LPU operates using sensory and timing based control providing feed forward and feedback information. By breaking down different components of locomotion into states, the LPU activates different muscle groups, or synergies, to recreate the desired functional movements. The LPU circuitry was simulated and compared against another controller designed to restore locomotion in an anesthetized cat to validate its performance.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"1 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":"128558251","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.2010.5709564
T. Torfs, R. Yazicioglu, Sunyoung Kim, Hyejung Kim, C. van Hoof, Dilpreet Buxi, I. Romero, J. Wijsman, F. Massé, J. Penders
A wireless ECG monitoring system is presented that is able to perform high-quality ECG signal acquisition, beat detection, and real time monitoring of skin-electrode impedance which can be used to monitor the presence of motion artefacts. The whole system consumes only 170μW while performing local beat detection. The beat detection algorithm was verified against the MIT-BIH arrhythmia database and obtains a median sensitivity of 99.74% and positive predictivity of 99.87%. The system was validated using applied signals at varying signal to noise ratio as well as on human volunteers.
{"title":"Ultra low power wireless ECG system with beat detection and real time impedance measurement","authors":"T. Torfs, R. Yazicioglu, Sunyoung Kim, Hyejung Kim, C. van Hoof, Dilpreet Buxi, I. Romero, J. Wijsman, F. Massé, J. Penders","doi":"10.1109/BIOCAS.2010.5709564","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709564","url":null,"abstract":"A wireless ECG monitoring system is presented that is able to perform high-quality ECG signal acquisition, beat detection, and real time monitoring of skin-electrode impedance which can be used to monitor the presence of motion artefacts. The whole system consumes only 170μW while performing local beat detection. The beat detection algorithm was verified against the MIT-BIH arrhythmia database and obtains a median sensitivity of 99.74% and positive predictivity of 99.87%. The system was validated using applied signals at varying signal to noise ratio as well as on human volunteers.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"1 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":"124604121","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.2010.5709587
J. B. Cees, C. Sawigun, A. Wouter
This paper presents an additive instantaneous companding technique in order to record the compound action potentials from the stimulated auditory nerve. This technique is intended to be combined with an analog to digital converter to achieve the 126-dB dynamic range that covers both stimulus (up to 20V), artifact and the neural response (down to 10μV). From the readout signal, the correct operation and placement of the cochlear stimulator can be estimated and useful information for further clinical studies can be obtained. The proposed system is designed to be implemented in AMIS I3T25 (high voltage) CMOS technology. Simulation results confirm the correct operation of the circuit.
{"title":"An additive instantaneously companding readout system for cochlear implants","authors":"J. B. Cees, C. Sawigun, A. Wouter","doi":"10.1109/BIOCAS.2010.5709587","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709587","url":null,"abstract":"This paper presents an additive instantaneous companding technique in order to record the compound action potentials from the stimulated auditory nerve. This technique is intended to be combined with an analog to digital converter to achieve the 126-dB dynamic range that covers both stimulus (up to 20V), artifact and the neural response (down to 10μV). From the readout signal, the correct operation and placement of the cochlear stimulator can be estimated and useful information for further clinical studies can be obtained. The proposed system is designed to be implemented in AMIS I3T25 (high voltage) CMOS technology. Simulation results confirm the correct operation of the circuit.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"26 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":"124164097","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}
An implantable 16-channel neural recording front-end system is presented for acute neural recording. This system consists of implantable silicon-based microelectrode arrays, neural-signal amplifiers and a microprocessor. The neural-signal amplifiers, which have been fabricated by a 0.35-μm CMOS process, have a mid-band gain of 66.5 dB, a high cut-off frequency at 9.6 kHz. Each recording channel has a tunable low cut-off frequency independently which is controlled by a microprocessor to fit different kinds of neural signals. The system has been tested and verified in-vitro experiment.
{"title":"A smart 16-channel front-end system for extracelluar neural recording","authors":"Beiju Huang, Yun Gui, Xu Zhang, Weihua Pei, Hongda Chen","doi":"10.1109/BIOCAS.2010.5709582","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709582","url":null,"abstract":"An implantable 16-channel neural recording front-end system is presented for acute neural recording. This system consists of implantable silicon-based microelectrode arrays, neural-signal amplifiers and a microprocessor. The neural-signal amplifiers, which have been fabricated by a 0.35-μm CMOS process, have a mid-band gain of 66.5 dB, a high cut-off frequency at 9.6 kHz. Each recording channel has a tunable low cut-off frequency independently which is controlled by a microprocessor to fit different kinds of neural signals. The system has been tested and verified in-vitro experiment.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"3 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":"129659790","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.2010.5709608
Florian Kolbl, A. Zbrzeski, Emilie Syed, S. Renaud, N. Lewis
Brain recording and stimulating systems are of major importance in neuroscience. They include an electrode or an array of electrodes, at the neuro-electronic interface. The electrodes NEX 100 and MS 306 are commonly used for accurate placement in deep sites of rats' brain, but few characterization data are available. After considerations related to the interface electrical model, this paper exposes an in vivo characterization set-up, for those specific electrodes, in LFP recording conditions. We discuss the variability of the electrode model parameters. Then the extracted model is included in electrical simulations and we evaluate its influence on the bio-amplifier design.
{"title":"In vivo electrical characterization of deep brain electrode and impact on bio-amplifier design","authors":"Florian Kolbl, A. Zbrzeski, Emilie Syed, S. Renaud, N. Lewis","doi":"10.1109/BIOCAS.2010.5709608","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709608","url":null,"abstract":"Brain recording and stimulating systems are of major importance in neuroscience. They include an electrode or an array of electrodes, at the neuro-electronic interface. The electrodes NEX 100 and MS 306 are commonly used for accurate placement in deep sites of rats' brain, but few characterization data are available. After considerations related to the interface electrical model, this paper exposes an in vivo characterization set-up, for those specific electrodes, in LFP recording conditions. We discuss the variability of the electrode model parameters. Then the extracted model is included in electrical simulations and we evaluate its influence on the bio-amplifier design.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"5 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":"123760623","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.2010.5709562
M. Stoopman, A. Wouter
This paper proposes the use of sub-GHz impulse radio Ultra-Wideband (UWB) communication for implantable medical devices. This new concept can offer a more reliable, safer and lower power consuming wireless link compared to other biomedical communications today. An operating frequency below 1 GHz is required to minimize the dielectric absorption of the human tissue and simultaneously allows for low power electronics. Investigating the antenna-electronics interface show that a current driven antenna results in the most reliable signal transfer. This interface is not bounded to the conventional 50 Ω interface.
{"title":"Sub-GHz UWB biomedical communication","authors":"M. Stoopman, A. Wouter","doi":"10.1109/BIOCAS.2010.5709562","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709562","url":null,"abstract":"This paper proposes the use of sub-GHz impulse radio Ultra-Wideband (UWB) communication for implantable medical devices. This new concept can offer a more reliable, safer and lower power consuming wireless link compared to other biomedical communications today. An operating frequency below 1 GHz is required to minimize the dielectric absorption of the human tissue and simultaneously allows for low power electronics. Investigating the antenna-electronics interface show that a current driven antenna results in the most reliable signal transfer. This interface is not bounded to the conventional 50 Ω interface.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"58 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":"132206181","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.2010.5709572
V. Fotopoulos, Argyro Sgourou, N. S. Athanassios
Agarose gel electrophoresis is an ideal method for separating and analyzing DNA and RNA molecules. Analysis is based on digital images taken by cameras equipped with UV filters and finds its main use in DNA identification. It is thus of paramount importance that these images employ authentication mechanisms and if possible, self-restore capabilities against malicious tampering. The proposed approach achieves the required authentication and self-correction by hiding a copy of the regions-of-interest into the region-of-non-interest of the images.
{"title":"Authentication and self-correction in DNA identification based on agarose-gel images","authors":"V. Fotopoulos, Argyro Sgourou, N. S. Athanassios","doi":"10.1109/BIOCAS.2010.5709572","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709572","url":null,"abstract":"Agarose gel electrophoresis is an ideal method for separating and analyzing DNA and RNA molecules. Analysis is based on digital images taken by cameras equipped with UV filters and finds its main use in DNA identification. It is thus of paramount importance that these images employ authentication mechanisms and if possible, self-restore capabilities against malicious tampering. The proposed approach achieves the required authentication and self-correction by hiding a copy of the regions-of-interest into the region-of-non-interest of the images.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"42 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":"133944382","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.2010.5709568
N. Nicolaou, J. Georgiou
This paper investigates the use of Permutation Entropy (PE) as a feature for mental task classification for a Brain-Computer Interface system. PE is a recently introduced measure which quantifies signal complexity by measuring the departure of a time series from a random one. More regular signals are characterized by lower PE values. Here, PE is utilized to characterize signals from electroencephalograms of 3 subjects performing 4 motor imagery tasks, which are then classified using a Support Vector Machine. Even though it is possible to obtain 100% single-trial classification accuracy, this is very much subject-dependent.
{"title":"Permutation Entropy: A new feature for Brain-Computer Interfaces","authors":"N. Nicolaou, J. Georgiou","doi":"10.1109/BIOCAS.2010.5709568","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709568","url":null,"abstract":"This paper investigates the use of Permutation Entropy (PE) as a feature for mental task classification for a Brain-Computer Interface system. PE is a recently introduced measure which quantifies signal complexity by measuring the departure of a time series from a random one. More regular signals are characterized by lower PE values. Here, PE is utilized to characterize signals from electroencephalograms of 3 subjects performing 4 motor imagery tasks, which are then classified using a Support Vector Machine. Even though it is possible to obtain 100% single-trial classification accuracy, this is very much subject-dependent.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"15 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":"133339908","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.2010.5709579
L. Ravichandran, A. Papandreou-Suppappola, A. Spanias, Z. Lacroix
We propose a protein structure alignment method that exploits advances in time-frequency signal processing to increase the similarity measure accuracy between distantly-related proteins. The new method uses a waveform non-linear mapping technique and waveform transformations in time-frequency (TF) space. Specifically, protein amino acids are mapped to three-dimensional (3-D) linear frequency-modulated (LFM) Gaussian chirps that are translated and rotated to account for all possible protein structure matches. The protein structure directionality is changed by considering all possible chirp rate parameters. Furthermore, both local and global alignments can be identified between multiple protein structures due to the linear separability property of the Gaussian-type functions. Our results are successfully demonstrated using proteins structures from a known database without performing any pre-processing. The paper also introduces a web-based learning module Java-DSP that can be used to implement bioinformatics functions using signal processing methods.
{"title":"Multiple protein structure alignment using time-frequency processing techniques","authors":"L. Ravichandran, A. Papandreou-Suppappola, A. Spanias, Z. Lacroix","doi":"10.1109/BIOCAS.2010.5709579","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709579","url":null,"abstract":"We propose a protein structure alignment method that exploits advances in time-frequency signal processing to increase the similarity measure accuracy between distantly-related proteins. The new method uses a waveform non-linear mapping technique and waveform transformations in time-frequency (TF) space. Specifically, protein amino acids are mapped to three-dimensional (3-D) linear frequency-modulated (LFM) Gaussian chirps that are translated and rotated to account for all possible protein structure matches. The protein structure directionality is changed by considering all possible chirp rate parameters. Furthermore, both local and global alignments can be identified between multiple protein structures due to the linear separability property of the Gaussian-type functions. Our results are successfully demonstrated using proteins structures from a known database without performing any pre-processing. The paper also introduces a web-based learning module Java-DSP that can be used to implement bioinformatics functions using signal processing methods.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"159 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":"124440246","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.2010.5709563
F. Asgarian, M. Amir
A novel noncoherent BPSK demodulator is presented for wirelessly-powered biomedical implants. The received data are detected based on rising or falling edge of the digitized carrier, while all components of the circuit are independent of the carrier frequency. Besides simplicity and ultra low-power consumption, the proposed demodulator benefits from an outstanding data-rate-to-carrier-frequency ratio of 100%. Thus, it can easily achieve high data rates with lower carrier frequencies, which is desirable in implantable biomedical applications such as visual prostheses. The circuit is designed and simulated in a 0.18-μm standard CMOS technology and merely consumes 119-μW@1.8V at a data rate of 10 Mbps. The proposed idea is also supported by experimental results of a proof-of-concept prototype.
{"title":"A carrier-frequency-independent BPSK demodulator with 100% data-rate-to-carrier-frequency ratio","authors":"F. Asgarian, M. Amir","doi":"10.1109/BIOCAS.2010.5709563","DOIUrl":"https://doi.org/10.1109/BIOCAS.2010.5709563","url":null,"abstract":"A novel noncoherent BPSK demodulator is presented for wirelessly-powered biomedical implants. The received data are detected based on rising or falling edge of the digitized carrier, while all components of the circuit are independent of the carrier frequency. Besides simplicity and ultra low-power consumption, the proposed demodulator benefits from an outstanding data-rate-to-carrier-frequency ratio of 100%. Thus, it can easily achieve high data rates with lower carrier frequencies, which is desirable in implantable biomedical applications such as visual prostheses. The circuit is designed and simulated in a 0.18-μm standard CMOS technology and merely consumes 119-μW@1.8V at a data rate of 10 Mbps. The proposed idea is also supported by experimental results of a proof-of-concept prototype.","PeriodicalId":440499,"journal":{"name":"2010 Biomedical Circuits and Systems Conference (BioCAS)","volume":"6 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":"124905584","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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