Linear and non-linear EEG analyses before and after psychosis in patients with epilepsy

Azuma, Hideki; Nagata, Hiroki; Akechi, Tatsuo

doi:10.3805/eands.11.20

Cited by 5 publications

(5 citation statements)

References 15 publications

(20 reference statements)

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“…Before selecting the EEG data, one of the authors (HA), who is a physician certified by the Japanese Society of Clinical Neurophysiology, interpreted the whole EEG and confirmed the background alpha rhythm when the participants rested with their eyes closed. Then, five sets of 3‐second EEG fragments with no overlap while resting with the eyes closed and awake EEG with no paroxysmal abnormalities including epileptic discharges, or no non‐paroxysmal abnormalities, and without contamination from the effects of alternating current interference, body motion artifacts, adhesive failure of the electrodes, or baseline fluctuations, were selected by unipolar montage 21 . We considered that a 3‐second EEG strip would satisfy the requirements of both fewer artifacts by visual inspection and a minimum number of data points for nonlinear analysis.…”

Section: Methodsmentioning

confidence: 99%

“…Then, five sets of 3‐second EEG fragments with no overlap while resting with the eyes closed and awake EEG with no paroxysmal abnormalities including epileptic discharges, or no non‐paroxysmal abnormalities, and without contamination from the effects of alternating current interference, body motion artifacts, adhesive failure of the electrodes, or baseline fluctuations, were selected by unipolar montage. 21 We considered that a 3‐second EEG strip would satisfy the requirements of both fewer artifacts by visual inspection and a minimum number of data points for nonlinear analysis. The selected EEG strips were then analyzed using an 18‐lead longitudinal bipolar montage: Fp1–F7, F7–T3, T3–T5, T5–O1, Fp1–F3, F3–C3, C3–P3, P3–O1, Fz–Cz, Cz–Pz, Fp2–F4, F4–C4, C4–P4, P4–O2, Fp2–F8, F8–T4, T4–T6, and T6–O2.…”

Section: Methodsmentioning

confidence: 99%

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EEG correlates of quality of life and associations with seizure without awareness and depression in patients with epilepsy

Azuma

Akechi

2022

Neuropsychopharm Rep

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Epilepsy is a neurological disorder characterized by the unpredictable occurrence of seizures. In most patients, seizures are controlled using antiepileptic drugs (AEDs). Despite treatment with AEDs, some patients still experience uncontrolled seizures. Patients with epilepsy whose seizures are either controlled or uncontrolled tend to be under psychological distress and carry a social burden, 1 which affects their quality of life (QOL).Therefore, QOL is an important issue for not only patients with epilepsy but also physicians. 2,3 Depression is a common comorbidity

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

EEG correlates of quality of life and associations with seizure without awareness and depression in patients with epilepsy

Azuma

Akechi

2022

Neuropsychopharm Rep

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“…A lower value of SampEn indicates more self‐similarity and regularity in the time series. SampEn ( N , r , m ) was calculated by means of the algorithm in PhysioNet . N is the length of data, m is the length of sequences to be compared, and r is the tolerance for accepting matches .…”

Section: Methodsmentioning

confidence: 99%

“…SampEn (N, r, m) was calculated by means of the algorithm in PhysioNet. [12][13][14][15] N is the length of data, m is the length of sequences to be compared, and r is the tolerance for accepting matches. 13 In the present study, N = 200 data points, m = 2, and r = 0.2 were used.…”

Section: Sampenmentioning

confidence: 99%

Intraclass correlations of seizure duration by wavelet transform, sample entropy, and visual determination in electroconvulsive therapy

Azuma

Ogawa

Suzuki

et al. 2019

Neuropsychopharm Rep

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Although electroconvulsive therapy seizure duration has been shown to have limited relevance to efficacy, seizure duration remains important for clinically valid stimulus efficiency. There has been no report on seizure duration using sample entropy with Thymatron (Somatics, Inc), which is widely used in Japan. Furthermore, wavelet transform analysis is also suitable for a seizure because of the wide range of dominant frequencies. Therefore, in this study with Thymatron, the intraclass correlations of seizure duration determined by sample entropy, wavelet transform, and visual determination were investigated to determine whether these methods were applicable for clinical use. Wavelet transform, sample entropy, and the human rater had high intraclass correlations for seizure duration. The present results indicate that wavelet transform and sample entropy can be useful in the clinical electroconvulsive therapy setting, and they may also be suitable for clinical research into the mechanisms of the generalized tonic‐clonic seizures related to the efficacy of electroconvulsive therapy.

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“…No literature on nonlinear EEG analysis for the diagnosis of comorbid psychiatric disorders with epilepsy has been published, and we only found a case series with nonlinear analysis of comorbid psychiatric symptoms with epilepsy. [82] Azuma reported that EEG was artifact free and had no paroxysmal abnormalities and that patients including controls had uncontrolled seizures before and after psychosis. SampEn may not only decrease in the right frontal and frontal-anterior temporal regions before psychosis, but it may also increase in the frontal and frontal-temporal regions during psychosis.…”

Section: Comorbid Psychiatric Disordersmentioning

confidence: 99%

Is EEG a Useful Examination Tool for Diagnosis of Epilepsy and Comorbid Psychiatric Disorders?

Azuma¹

2021

Epilepsy - Update on Classification, Etiologies, Instrumental Diagnosis and Treatment

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Diagnosis of epilepsy usually involves interviewing the patients and the individuals who witnessed the seizure. An electroencephalogram (EEG) adds useful information for the diagnosis of epilepsy when epileptic abnormalities emerge. EEG exhibits nonlinearity and weak stationarity. Thus, nonlinear EEG analysis may be useful for clinical application. We examined only about English language studies of nonlinear EEG analysis that compared normal EEG and interictal EEG and reported the accuracy. We identified 60 studies from the public data of Andrzejak 2001 and two studies that did not use the data of Andrzejak 2001. Comorbid psychiatric disorders in patients with epilepsy were not reported in nonlinear EEG analysis except for one case series of comorbid psychotic disorders. Using a variety of feature extraction methods and classifier methods, we concluded that the studies that used the data of Andrzejak 2001 played a valuable role in EEG diagnosis of epilepsy. In the future, according to the evolution of artificial intelligence, deep learning, new nonlinear analysis methods, and the EEG association with the rating scale of the quality of life and psychiatric symptoms, we anticipate that EEG diagnosis of epilepsy, seizures, and comorbid psychiatric disorders in patients with epilepsy will be possible.

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Linear and non-linear EEG analyses before and after psychosis in patients with epilepsy

Cited by 5 publications

References 15 publications

EEG correlates of quality of life and associations with seizure without awareness and depression in patients with epilepsy

EEG correlates of quality of life and associations with seizure without awareness and depression in patients with epilepsy

Intraclass correlations of seizure duration by wavelet transform, sample entropy, and visual determination in electroconvulsive therapy

Is EEG a Useful Examination Tool for Diagnosis of Epilepsy and Comorbid Psychiatric Disorders?

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