Epileptic seizure onset detection prior to clinical manifestation

Salam, Muhammad Tariqus; Nguyen, Dang Khoa

doi:10.1109/iembs.2010.5627732

Cited by 8 publications

(10 citation statements)

References 7 publications

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“…The prospect of embedded detectors raises the issue of low-power computing and poses limit to the amount of processing that can be done by those devices in the assessment of ictal onset [33, 34]. Engineering of these implantable devices is forcing a compromise of detection power versus consumption.…”

Section: Embeddingmentioning

confidence: 99%

Improving early seizure detection

Jouny

Franaszczuk

Bergey

2011

Epilepsy & Behavior

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Over the last decade, the search for a method able to reliably predict seizures hours in advance has been largely replaced by a more realistic goal of very early detection of seizure onset which would allow therapeutic or warning devices to be triggered prior to the onset of disabling clinical symptoms. We explore in this article the steps along the pathway from data acquisition to closed loop applications that can and should be considered to design the most efficient early seizure detection. Microelectrodes, high-frequency oscillations, high sampling rate, high-density arrays, and modern analysis techniques are all elements of the recording and detection process that in combination with modeling studies can provide new insights into the dynamics of seizure onsets. Each of these step needs to be considered if one wants to implement improved detection devices that will favorably impact the quality of life of patients.

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Section: Embeddingmentioning

confidence: 99%

Improving early seizure detection

Jouny

Franaszczuk

Bergey

2011

Epilepsy & Behavior

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“…Although many seizure detection algorithms have so far been proposed [Nandan et al 2010;Polychronaki et al 2010;Zandi et al 2009], these have mainly been developed for high-speed desktop computers and short-term applications which cannot be employed in a low-power implantable microchip [Salam et al 2010c]. Further development in epileptic prosthetic devices would benefit from an epileptic seizure detection algorithm for low-power integrated circuits that could provide high-detection accuracy and reduce instrumentational lowfrequency noises [Patel et al 2009;Raghunathan et al 2009;Salam et al 2009Salam et al , 2010bVerma et al 2010].…”

Section: Introductionmentioning

confidence: 99%

Implantable Closed-Loop Epilepsy Prosthesis

Salam

Nguyen

2012

J. Emerg. Technol. Comput. Syst.

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In this article, we present an implantable closed-loop epilepsy prosthesis, which is dedicated to automatically detect seizure onsets based on intracerebral electroencephalographic (icEEG) recordings from intracranial electrode contacts and provide an electrical stimulation feedback to the same contacts in order to disrupt these seizures. A novel epileptic seizure detector and a dedicated electrical stimulator were assembled together with common recording electrodes to complete the proposed prosthesis. The seizure detector was implemented in CMOS 0.18-μm by incorporating a new seizure detection algorithm that models timeamplitude and -frequency relationship in icEEG. The detector was validated offline on ten patients with refractory epilepsy and showed excellent performance for early detection of seizures. The electrical stimulator, used for suppressing the developing seizure, is composed of two biphasic channels and was assembled with embedded FPGA in a miniature PCB. The stimulator efficiency was evaluated on cadaveric animal brain tissue in an in vitro morphologic electrical model. Spatial characteristics of the voltage distribution in cortex were assessed in an attempt to identify optimal stimulation parameters required to affect the suspected epileptic focus. The experimental results suggest that lower frequency stimulation parameters cause significant amount of shunting of current through the cerebrospinal fluid; however higher frequency stimulation parameters produce effective spatial voltage distribution with lower stimulation charge.

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“…The first scheme is capacitive feedback [4] of amplification that can remove the dc offset, but it increases input referred noise [5]. Thus, second scheme [5]- [6] is based on closed loop control of dc level. This scheme made of active components can provide elimination of low frequency noise and high input impedance.…”

Section: Introductionmentioning

confidence: 99%

A multichannel intracerebral EEG monitoring system for epilepsy presurgical evaluation

Salam

Nguyen

2011

2011 24th Canadian Conference on Electrical and Computer Engineering(CCECE)

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In this paper, we propose a multichannel monitoring system intended for chronic intracerebral EEG (icEEG) recording and automatic seizure onset detection for epilepsy presurgical evaluation. We present a method of recording, a noise reduction circuit design, followed by implementation, and validation of the icEEG monitoring system. The later includes the recording module and a seizure onset detection algorithm. The icEEG recording module has 3 stages for amplification and noise reduction. Initially, the input neural signal is recorded through an amplifier that has a feedback noise reduction circuit. Further, noises are removed by high and low pass filters. The present version of the system includes 6 channels. Each one features high amplification gain 60 dB, low noise (1 μVrms), and a high common mode rejection ratio 80dB. The total power consumption of the whole recording module is 12 mW. The proposed device was validated using icEEG recordings from two patients with drug-resistant epilepsy. The multichannel monitoring system suggested reasonable assumption about the epileptogenic zone.

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Epileptic seizure onset detection prior to clinical manifestation

Cited by 8 publications

References 7 publications

Improving early seizure detection

Improving early seizure detection

Implantable Closed-Loop Epilepsy Prosthesis

A multichannel intracerebral EEG monitoring system for epilepsy presurgical evaluation

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