A micropower EEG detection system applicable for paralyzed hand artifical control

Abdallah, Aisha; Diab, Maha S.; Mahmoud, Soliman A.

doi:10.1109/tsp.2017.8076017

Cited by 6 publications

(3 citation statements)

References 9 publications

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“…The starting frequency of the high-pass filter is generally set at about 0.5 Hz, and is usually realized by an active filter. The band-pass amplitude and cut-off frequency of the active filter will not change due to different loads, and it can also dynamically compensate reactive power [49,50] .…”

Section: Filtermentioning

confidence: 99%

A review of automatic detection of epilepsy based on EEG signals

Ren,

Sun,

et al. 2023

J. Semicond.

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Epilepsy is a common neurological disorder that occurs at all ages. Epilepsy not only brings physical pain to patients, but also brings a huge burden to the lives of patients and their families. At present, epilepsy detection is still achieved through the observation of electroencephalography (EEG) by medical staff. However, this process takes a long time and consumes energy, which will create a huge workload to medical staff. Therefore, it is particularly important to realize the automatic detection of epilepsy. This paper introduces, in detail, the overall framework of EEG-based automatic epilepsy identification and the typical methods involved in each step. Aiming at the core modules, that is, signal acquisition analog front end (AFE), feature extraction and classifier selection, method summary and theoretical explanation are carried out. Finally, the future research directions in the field of automatic detection of epilepsy are prospected.

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Section: Filtermentioning

confidence: 99%

A review of automatic detection of epilepsy based on EEG signals

Ren,

Sun,

et al. 2023

J. Semicond.

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“…Various integrated circuits are used for biomedical signals such as EEG signals. These circuits are in many structures, such as OP-AMP based [5], CMOS-based [6], time-frequency based [7], and computer interface based [8]. In this study, a new current-controlled current conveyor (CCCII+) low-pass filter circuit is designed for EEG signals.…”

Section: Introductionmentioning

confidence: 99%

Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals

TEKİN,

GÜLER

2023

Turkish Journal of Science and Technology

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EEG signals are noisy signals that allow brain activity to be analyzed. In recent years, it has been seen that current conveyor-based circuits, which have many advantages such as wide bandwidth, high linearity, low power consumption, have been used instead of operational amplifiers in the analysis of these signals. In this study, a second-generation current controlled current conveyor (CCCII+) low pass filter circuit with a cut-off frequency of 100 Hz has been presented for the analysis of EEG signals. The simulation of the circuit was carried out with the Orcad pspice program. In addition, the application circuit of this low-pass filter circuit has been made and oscilloscope images have been obtained for some frequency values. AD844 IC is used as current conveyor in the application circuit. The data of epilepsy patients and normal people taken from the University of Bonn were applied to the CCCII+ low pass filter circuit and the frequency bands of these signals were examined. It has been predicted that if this CCCII+ low pass filter circuit is used in EEG measurements, it will give good results in the diagnosis of neurological diseases such as epilepsy.

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“…Günümüzde EEG ölçümleri ve EEG sinyallerinden gürültüleri arındırmak için tasarlanan pek çok devre vardır. Bu devreler; OP-AMP tabanlı [4], CMOS tabanlı [5], zaman frekans tabanlı [6], bilgisayar arayüzü tabanlı [7] gibi birçok çeşitte olduğu görülmüştür. Bu çalışmada ise, yeni bir akım kontrollü akım taşıyıcı (CCCII+) ile bant geçiren filtre ve OP-AMP ile bant geçiren filtre tasarlanmıştır.…”

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EEG Analizi için CCCII+ Tabanlı Bant Geçiren Filtre Tasarımı

Tekin

Güler

2022

Fırat Üniversitesi Mühendislik Bilimleri Dergisi

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Öz: Biyomedikal sinyaller, küçük genlikli ve spektrumu alçak frekanslar bölgesinde olan gürültülü işaretlerdir. Biyomedikal sinyallerin analizinde genellikle işlemsel kuvvetlendiriciler (OP-AMP) ile tasarlanan aktif filtreler kullanılmaktadır. Günümüzde OP-AMP'ların alternatifi olarak akım taşıyıcılar sunulmuş ve akım taşıyıcıların OP-AMP'lara göre birçok avantajı olduğu saptanmıştır. Bu çalışmada ise bir EEG sinyali için hem OP-AMP hem de ikinci nesil akım kontrollü akım taşıyıcı (CCCII+) kullanılarak iki farklı bant geçiren filtre tasarlanmıştır. Bant geçiren filtre devreleri için bant aralığı 0,5-30 Hz seçilmiştir. Bu devrelerin tasarımı için ORCAD Pspice programı kullanılmış olup benzetim sonuçları elde edilmiştir. Tasarlanan filtrelerin girişine Boon Üniversitesinden alınan epilepsi hastalarına ve sağlıklı kişilere ait ham EEG verileri uygulanmıştır. EEG sinyalinin tasarlanan iki filtreye uygulanması sonucunda sinyallere Fourier Analizi uygulanmış olup sinyallerdeki değişimler ve EEG dalgaları (δ, θ, α, β, γ) incelenmiştir. Her iki sinyal için de OP-AMP devresine göre CCCII+ ile tasarlanan filtrede sönümlemenin daha iyi olduğu saptanmıştır. Bu tasarlanan iki filtre devresi, EEG ölçümlerinde kullanılması durumunda CCCII+ filtre devresinin epilepsi gibi hastalıkların tanısında daha iyi sonuçlar vereceği öngörülmüştür.

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A micropower EEG detection system applicable for paralyzed hand artifical control

Cited by 6 publications

References 9 publications

A review of automatic detection of epilepsy based on EEG signals

A review of automatic detection of epilepsy based on EEG signals

Second Generation Current Controlled Current Conveyor Based Low Pass Filter Design For The Processing of EEG Signals

EEG Analizi için CCCII+ Tabanlı Bant Geçiren Filtre Tasarımı

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