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作者： Chow, Eric Y. Yang, Chin-Lung Chlebowski, Arthur Moon, Sungwook Chappell, William J. Irazoqui, Pedro P. Brain Computer Interface Laboratory Weldon School of Biomedical Engineering Purdue University West Lafayette IN 47907 United States Electrical Engineering Department National Cheng Kung University Tainan Taiwan IDEAS Microwave Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette IN 47907 United States

We report live animal studies that verify and quantify successful transocular transmission of data from a miniature low-power implant. To minimize damage, implantation within layers of the eye requires an ultrasmall device on a scale of just a few millimeters on each side and less than 500 μm in thickness. A high-frequency transmitter integrated circuit (IC) was designed, fabricated, and bonded onto a board containing an antenna, matching network components, and interconnects. The transmitter must achieve sufficient efficiency to draw minimal power from the limited onboard storage array while outputting a sufficiently large signal to overcome tissue-induced attenuation. Two different versions of the system were developed, one using a low-temperature co-fired ceramic material for the substrate and the other using silicon. Animal studies performed using live rabbits followed by empirical measurements verified the feasibility of a wireless telemetry scheme for a low-power miniature ocular implant. © 2006 IEEE.

关键词： Transmitters

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High data-rate 6.7 GHz wireless ASIC transmitter for neural prostheses

High data-rate 6.7 GHz wireless ASIC transmitter for neural ...

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29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07

作者： Chow, Eric Y. Kahn, Adam Irazoqui, Pedro P. IEEE Brain Computer Interface Laboratory Weldon School of Biomedical Engineering Purdue University West Lafayette IN 47907 United States

ISBN: (纸本)1424407885

A high-frequency transmitter has been designed for high data-rate biomedical telemetry. Although high frequencies face greater attenuation, transcutaneous transmission was successfully tested and verified using a 3.76 mm thick sample of porcine skin. The structure transmits over 440 μW of power, consumes about 4.9 mA of current from a 1.8 V supply, and achieves a phase noise of -72 dBc/Hz at 100 KHz. The transmitter operates at around 6.7 GHz with a 50 MHz tuning range and is fully integrated on the CMOS IBM7RF 0.18 μm process. © 2007 IEEE.

关键词： Transmitters

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High Data-Rate 6.7GHz Wireless ASIC Transmitter for neural Prostheses

High Data-Rate 6.7GHz Wireless ASIC Transmitter for Neural P...

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29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), vol.16

作者： Eric Y. Chow Adam Kahn Pedro P. Irazoqui Brain Computer Interface Laboratory Weldon School of Biomedical Engineering and School of Electrical and Computer Engineering Purdue University West Lafayette IN USA Purdue University System West Lafayette IN US Brain Computer Interface Laboratory Weldon School of Biomedical Engineering Purdue University West Lafayette IN USA

A high-frequency transmitter has been designed for high data-rate biomedical telemetry. Although high frequencies face greater attenuation, transcutaneous transmission was successfully tested and verified using a 3.76mm thick sample of porcine skin. The structure transmits over 440μW of power, consumes about 4.9mA of current from a 1.8V supply, and achieves a phase noise of -72dBc/Hz at 100KHz. The transmitter operates at around 6.7GHz with a 50MHz tuning range and is fully integrated on the CMOS IBM7RF 0.18μm process.

关键词： Application specific integrated circuits Neurotransmitters Prosthetics Transmitters Biomedical telemetry Frequency Attenuation Testing Skin Phase noise

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A compact nanopower low output impedance CMOS operational amplifier for wireless intraocular pressure recordings

A compact nanopower low output impedance CMOS operational am...

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29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07

作者： Dresher, Russell P. Irazoqui, Pedro P. IEEE Worcester Polytechnic Institute Worcester MA 01609 United States Brain Computer Interface Laboratory Purdue University West Lafayette IN 47907 United States University of California at Los Angeles Los Angeles CA 90095 United States Department of Biomedical Engineering

ISBN: (纸本)1424407885

Wireless sensing has shown potential benefits for the continuous-time measurement of physiological data. One such application is the recording of intraocular pressure (IOP) for patients with glaucoma. Ultra-low-power circuits facilitate the use of inductively-coupled power for implantable wireless systems. Compact circuit size is also desirable for implantable systems. As a first step towards the realization of such circuits, we have designed a compact, ultra-low-power operational amplifier which can be used to record IOP. This paper presents the measured results of a CMOS operational amplifier that can be incorporated with a wireless IOP monitoring system or other low-power application. It has a power consumption of 736 nW, chip area of 0.023 mm 2, and output impedance of 69 Ω to drive low-impedance loads. © 2007 IEEE.

关键词： Wireless sensor networks

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A Compact Nanopower Low Output Impedance CMOS Operational Amplifier for Wireless Intraocular Pressure Recordings

A Compact Nanopower Low Output Impedance CMOS Operational Am...

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29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2007), vol.15

作者： Russell P. Dresher Pedro P. Irazoqui Brain Computer Interface Laboratory Purdue University West Lafayette IN USA Worcester Polytechnic Institute Worcester MA USA University of California Los Angeles Los Angeles CA USA

Wireless sensing has shown potential benefits for the continuous-time measurement of physiological data. One such application is the recording of intraocular pressure (TOP) for patients with glaucoma. Ultra-low-power circuits facilitate the use of inductively-coupled power for implantable wireless systems. Compact circuit size is also desirable for implantable systems. As a first step towards the realization of such circuits, we have designed a compact, ultra-low-power operational amplifier which can be used to record IOP. This paper presents the measured results of a CMOS operational amplifier that can be incorporated with a wireless IOP monitoring system or other low-power application. It has a power consumption of 736nW, chip area of 0.023mm{sup}2, and output impedance of 69Ω to drive low-impedance loads.

关键词： Impedance Operational amplifiers Wireless sensor networks Circuits Biomedical monitoring Biomedical measurements Biomedical engineering Nanobioscience Optical amplifiers Semiconductor device measurement

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Towards development of a 3-state self-paced brain-computer interface

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Computational Intelligence and Neuroscience 2007年第1期2007卷 84386页

作者： Bashashati, Ali Ward, Rabab K. Birch, Gary E. Electrical and Computer Engineering Department University of British Columbia Vancouver BC V6T 1Z4 Canada Terry Fox Laboratory British Columbia Cancer Research Center Vancouver BC V5Z 1L3 Canada Brain Interface Laboratory Neil Squire Society Burnaby BC V5M 3Z3 2250 Boundary Road Canada Institute for Computing Information and Cognitive Systems Vancouver BC V6T 1Z4 Canada

Most existing brain-computer interfaces (BCIs) detect specific mental activity in a so-called synchronous paradigm. Unlike synchronous systems which are operational at specific system-defined periods, self-paced (asynchronous) interfaces have the advantage of being operational at all times. The low-frequency asynchronous switch design (LF-ASD) is a 2-state self-paced BCI that detects the presence of a specific finger movement in the ongoing EEG. Recent evaluations of the 2-state LF-ASD show an average true positive rate of 41 at the fixed false positive rate of 1. This paper proposes two designs for a 3-state self-paced BCI that is capable of handling idle brain state. The two proposed designs aim at detecting right- and left-hand extensions from the ongoing EEG. They are formed of two consecutive detectors. The first detects the presence of a right- or a left-hand movement and the second classifies the detected movement as a right or a left one. In an offline analysis of the EEG data collected from four able-bodied individuals, the 3-state brain-computer interface shows a comparable performance with a 2-state system and significant performance improvement if used as a 2-state BCI, that is, in detecting the presence of a right- or a left-hand movement (regardless of the type of movement). It has an average true positive rate of 37.5 and 42.8 (at false positives rate of 1) in detecting right- and left-hand extensions, respectively, in the context of a 3-state self-paced BCI and average detection rate of 58.1 (at false positive rate of 1) in the context of a 2-state self-paced BCI.

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Vibrotactile feedback for brain-computer interface operation

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Computational Intelligence and Neuroscience 2007年第1期2007卷 48937页

作者： Cincotti, Febo Kauhanen, Laura Aloise, Fabio Palomäki, Tapio Caporusso, Nicholas Jylänki, Pasi Mattia, Donatella Babiloni, Fabio Vanacker, Gerolf Nuttin, Marnix Marciani, Maria Grazia Millán, José Del R. Laboratory of Neuroelectrical Imaging and Brain Computer Interface Fondazione Santa Lucia IRCCS Roma 00179 Via Ardeatina 306 Italy Laboratory of Computational Engineering Helsinki University of Technology TKK 02015 P.O. Box 9203 Finland Department of Computer Science University of Bari Bari 70125 Via Orabona 4 Italy Department of Mechanical Engineering Katholieke Universiteit Leuven Leuven 3000 Celestijnenlaan 300 B Belgium Dipartimento di Fisiologia Umana e Farmacologia Universitá Degli Studi di Roma la Sapienza Roma 00185 Piazzale Aldo Moro 5 Italy Dipartimento di Neuroscienze Universitá Degli Studi di Roma Tor Vergata Roma 00173 Via Montpellier 1 Italy IDIAP Research Institute Martigny 1920 Switzerland Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne 1015 Switzerland

To be correctly mastered, brain-computer interfaces (BCIs) need an uninterrupted flow of feedback to the user. This feedback is usually delivered through the visual channel. Our aim was to explore the benefits of vibrotactile feedback during users' training and control of EEG-based BCI applications. A protocol for delivering vibrotactile feedback, including specific hardware and software arrangements, was specified. In three studies with 33 subjects (including 3 with spinal cord injury), we compared vibrotactile and visual feedback, addressing: (I) the feasibility of subjects' training to master their EEG rhythms using tactile feedback;(II) the compatibility of this form of feedback in presence of a visual distracter;(III) the performance in presence of a complex visual task on the same (visual) or different (tactile) sensory channel. The stimulation protocol we developed supports a general usage of the tactors;preliminary experimentations. All studies indicated that the vibrotactile channel can function as a valuable feedback modality with reliability comparable to the classical visual feedback. Advantages of using a vibrotactile feedback emerged when the visual channel was highly loaded by a complex task. In all experiments, vibrotactile feedback felt, after some training, more natural for both controls and SCI users.

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Nonparametric density estimation based independent component analysis via particle swarm optimization

Nonparametric density estimation based independent component...

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2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05

作者： Krusienski, D.J. Jenkins, W.K. Brain-Computer Interface Laboratory Wadsworth Center NYSDOH Albany NY United States Department of Electrical Engineering Pennsylvania State University University Park PA United States

ISBN: (纸本)0780388747

This paper investigates the application of a modified particle swarm optimization technique to nonparametric density estimation based independent component analysis (ICA). Nonparametric ICA has the advantage over traditional ICA techniques in that its performance is not dependent upon prior assumptions about the source distributions. Particle swarm optimization (PSO) is similar to the genetic algorithm in that it utilizes a population based search suitable for optimizing multimodal error surfaces where gradient-based algorithms tend to fail, such as those generated by nonlinear entropy maximization schemes used in ICA algorithms. © 2005 IEEE.

关键词： Independent component analysis

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Tracking of the Mu Rhythm using an Empirically Derived Matched Filter

Tracking of the Mu Rhythm using an Empirically Derived Match...

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International IEEE/EMBS Conference on neural Engineering, CNE

作者： D.J. Krusienski G. Schalk D.J. McFarland J.R. Wolpaw Brain-Computer Interface Laboratory Wadsworth Center NYSDOH Albany NY USA

This paper introduces a method for improved detection and tracking of cortical mu rhythm modulation for the purpose of a brain-computer interface (BCI). The cortical mu rhythm found in the EEG is of particular interest in BCIs because it can be modulated through motor imagery and can be monitored via noninvasive techniques. With proper training, a disabled person can learn to control the mu rhythm to operate a communication device. This paper discusses the extraction of the empirical mu rhythm, proposes a synthetic model for the mu rhythm, and examines the effectiveness of the synthetic model as a matched filter on two-dimensional cursor control data recorded from a BCI

关键词： Rhythm Matched filters Electroencephalography brain computer interfaces brain modeling Synchronous motors Communication system control Laboratories Monitoring Noninvasive treatment

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Nonparametric density estimation based independent component analysis via particle swarm optimization

Nonparametric density estimation based independent component...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： D.J. Krusienski W.K. Jenkins Brain-Computer Interface Laboratory Wadsworth Center Albany NY USA Department of Electrical Engineering Pennsylvania State University University Park PA USA

The paper investigates the application of a modified particle swarm optimization technique to nonparametric density estimation based independent component analysis (ICA). Nonparametric ICA has the advantage over traditional ICA techniques in that its performance is not dependent upon prior assumptions about the source distributions. Particle swarm optimization (PSO) is similar to the genetic algorithm in that it utilizes a population based search suitable for optimizing multimodal error surfaces where gradient-based algorithms tend to fail, such as those generated by nonlinear entropy maximization schemes used in ICA algorithms.

关键词： Independent component analysis Particle swarm optimization Entropy neural networks brain computer interfaces Laboratories State estimation Genetic algorithms Signal generators Heart

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