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The Journal of Supercomputing

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12-01-2022

Epileptic seizure endorsement technique using DWT power spectrum

Authors: Anand Ghuli, Damodar Reddy Edla, João Manuel R. S. Tavares

Published in: The Journal of Supercomputing | Issue 6/2022

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Abstract

EEG signals play significant role in the study of mental disorders. Epilepsy is one of the major mental disorders and need significant technological support in the treatment. A method proposed here is an endorsement technique for epileptic seizures using electroencephalogram (EEG) signals captured using non-invasive method. The method uses power spectrum density and discrete wavelet transformation (DWT). The impact of power spectral analysis along with the usage of EEG characteristics in endorsement of epilepsy is addressed here. A publicly available EEG epileptic dataset is processed using FIR filters along with DWT. The power spectrum density and its average were compared with specific spectrum to get the results and were compared against the standard EEG signal frequency range. It is found that the usage of DWT is more accurate and reliable to process and classify the EEG data for epilepsy endorsement.

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Brown EN, Lydic R, Schiff ND (2010) General anesthesia, sleep, and coma. N Engl J Med 363(27):2638–2650CrossRef

Abdulkader SN, Atia A, Mostafa MSM (2015) Brain computer interfacing: applications and challenges. Egypt Inform J 16(2):213–230CrossRef

Pattnaik PK, Sarraf J (2018) Brain Computer Interface issues on hand movement. J King Saud Univ-Comput Inform Sci 30(1):18–24

Guy V, Soriani MH, Bruno M, Papadopoulo T, Desnuelle C, Clerc M (2018) Brain computer interface with the P300 speller: usability for disabled people with amyotrophic lateral sclerosis. Ann Phys Rehab Med 61(1):5–11CrossRef

Van Dokkum LEH, Ward T, Laffont I (2015) Brain computer interfaces for neurorehabilitation–its current status as a rehabilitation strategy post-stroke. Ann Phys Rehab Med 58(1):3–8CrossRef

Chaudhary U, Birbaumer N, Curado MR (2015) Brain-machine interface (BMI) in paralysis. Ann Phys Rehab Med 58(1):9–13CrossRef

Miranda RA, Casebeer WD, Hein AM, Judy JW, Krotkov EP, Laabs TL, Weber DJ (2015) DARPA-funded efforts in the development of novel brain–computer interface technologies. J Neurosci Methods 244:52–67CrossRef

Hoffmann U, Vesin JM, Ebrahimi T (2007) Recent advances in brain-computer interfaces. In IEEE International Workshop on Multimedia Signal Processing (MMSP07) (No. CONF).

Sunny TD, Aparna T, Neethu P, Venkateswaran J, Vishnupriya V, Vyas PS (2016) Robotic arm with brain–computer interfacing. Procedia Technol 24:1089–1096CrossRef

10.

Kobler RJ, Sburlea AI, Müller-Putz GR (2018) Tuning characteristics of low-frequency EEG to positions and velocities in visuomotor and oculomotor tracking tasks. Sci Rep 8(1):1–14CrossRef

11.

Ofner P, Schwarz A, Pereira J, Wyss D, Wildburger R, Müller-Putz GR (2019) Attempted arm and hand movements can be decoded from low-frequency EEG from persons with spinal cord injury. Sci Rep 9(1):1–15CrossRef

12.

Willett FR, Young DR, Murphy BA, Memberg WD, Blabe CH, Pandarinath C, Sweet JA (2019) Principled BCI decoder design and parameter selection using a feedback control model. Sci Rep 9(1):1–17CrossRef

13.

Nagel S, Spüler M (2019) Asynchronous non-invasive high-speed BCI speller with robust non-control state detection. Sci Rep 9(1):1–9CrossRef

14.

Bablani A, Edla DR, Tripathi D, Kuppili V (2019) An efficient concealed information test: EEG feature extraction and ensemble classification for lie identification. Mach Vis Appl 30(5):813–832CrossRef

15.

Tiwari N, Edla DR, Dodia S, Bablani A (2018) Brain computer interface: a comprehensive survey. Biol Ins Cognitive Architect 26:118–129

16.

Velloso GT (2012) Brain-Computer Interface (BCI): a methodological proposal to assess the impacts of medical applications in 2022. Enterprise and Work Innovation Stud 8:57–81

17.

Choi BM (2017) Characteristics of electroencephalogram signatures in sedated patients induced by various anesthetic agents. J Dental Anes Pain Med 17(4):241–251CrossRef

18.

Umair R (2020) EEG Signal Analysis ( https://www. mathworks.com / matlabcentral / fileexchange/ 71322-eeg-signal-analysis ), MATLAB Central File Exchange. Retrieved Apr 23, 2020.

19.

Vijay D (2020). EEG ANALYSIS AND CLASSIFICATION (https:// www.mathworks.com / matlabcentral / fileexchange / 55112 – eeg – analysis – and – classification ), MATLAB Central File Exchange. Retrieved Apr 23, 2020.

20.

Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adeli H (2018) Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals. Comput Biol Med 100:270–278CrossRef

21.

Hassan AR, Subasi A, Zhang Y (2020) Epilepsy seizure detection using complete ensemble empirical mode decomposition with adaptive noise. Knowl-Based Syst 191:105333CrossRef

22.

Boonyakitanont P, Lek-Uthai A, Chomtho K, Songsiri J (2020) A review of feature extraction and performance evaluation in epileptic seizure detection using EEG. Biomed Sig Process Control 57:101702CrossRef

23.

Rafik D, Larbi B (2019) Autoregressive Modeling Based Empirical Mode Decomposition (EMD) for Epileptic Seizures Detection Using EEG Signals Autoregressive Modeling Based Empirical Mode Decomposition (EMD) for Epileptic Seizures Detection Using EEG Signals.

24.

Li JW, Barma S, Mak PU, Pun SH, Vai MI (2019) Brain rhythm sequencing using EEG signals: a case study on seizure detection. IEEE Access 7:160112–160124CrossRef

25.

Al-Sharhan S, Bimba A (2019) Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification. Appl Soft Comput 75:575–587CrossRef

26.

Tawfik NS, Youssef SM, Kholief M (2016) A hybrid automated detection of epileptic seizures in EEG records. Comput Electr Eng 53:177–190CrossRef

27.

Raghu S, Sriraam N, Hegde AS, Kubben PL (2019) A novel approach for classification of epileptic seizures using matrix determinant. Expert Syst Appl 127:323–341CrossRef

28.

Swami P, Gandhi TK, Panigrahi BK, Tripathi M, Anand S (2016) A novel robust diagnostic model to detect seizures in electroencephalography. Expert Syst Appl 56:116–130CrossRef

29.

Aydemir E, Tuncer T, Dogan S (2020) A tunable-Q wavelet transform and quadruple symmetric pattern based EEG signal classification method. Med Hypotheses 134:109519CrossRef

30.

You Y, Chen W, Li M, Zhang T, Jiang Y, Zheng X (2020) Automatic focal and non-focal EEG detection using entropy-based features from flexible analytic wavelet transform. Biomed Sig Process Control 57:101761CrossRef

31.

Vanabelle P, De Handschutter P, El Tahry R, Benjelloun M, Boukhebouze M (2020) Epileptic seizure detection using EEG signals and extreme gradient boosting. J Biomed Res 34(3):226–237CrossRef

32.

Andrzejak RG, Lehnertz K, Mormann F, Rieke C, David P, Elger CE (2001) Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state. Phys Rev E 64(6):0619CrossRef

33.

Filip SI (2016) A robust and scalable implementation of the Parks-McClellan algorithm for designing FIR filters. ACM Trans Math Softw (TOMS) 43(1):1–24MathSciNetMATHCrossRef

34.

Schirner G, Erdogmus D, Chowdhury K et al (2013) The future of human-in-the-loop cyber-physical systems [J]. Computer 46(1):36–45CrossRef

35.

Wu X, Xiao L, Sun Y, et al. A Survey of Human-in-the-loop for Machine Learning [J]. arXiv preprint arXiv:2108.00941, 2021.

36.

Jotterand F, Bosco C (2020) Keeping the “human in the loop” in the age of artificial intelligence[J]. Sci Eng Ethics 26(5):2455–2460CrossRef

37.

Walsh C (2018) Human-in-the-loop development of soft wearable robots[J]. Nat Rev Mater 3(6):78–80CrossRef

38.

Li M, Chen W, Zhang T (2017) Classification of epilepsy EEG signals using DWT-based envelope analysis and neural network ensemble. Biomed Sig Proces 31:357–365CrossRef

39.

Prochazka A, Kukal J and Vysata O. Wavelet transform use for feature extraction and EEG signal segments classification. In: 3rd international symposium on communications, control and signal processing, 2008 (ISCCSP 2008), St Julians, 12–14 March 2008. New York: IEEE.

Title: Epileptic seizure endorsement technique using DWT power spectrum
Authors: Anand Ghuli
Damodar Reddy Edla
João Manuel R. S. Tavares
Publication date: 12-01-2022
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 6/2022
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-021-04196-3

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