Automatic detection of Alzheimer’s disease from EEG signals using an improved AFS–GA hybrid algorithm

Acharya UR, Fujita H, Sudarshan VK, Bhat S, Koh JE (2015) Application of entropies for automated diagnosis of epilepsy using eeg signals: A review. Knowl-Based Syst 88:85–96

Article  Google Scholar 

Akbari H, Ghofrani S, Ghofrani S (2019) Fast and accurate classification f and nf eeg by using sodp and ewt. Int J Image Graph Signal Process 11(11):29–35

Article  Google Scholar 

Akbari H, Sadiq MT, Payan M, Esmaili SS, Baghri H, Bagheri H (2021) Depression detection based on geometrical features extracted from sodp shape of eeg signals and binary pso. Traitement du Signal 38(1)

Akbari H, Sadiq MT, Payan M, Esmaili SS, Baghri H, Bagheri H (2021) Depression detection based on geometrical features extracted from sodp shape of eeg signals and binary pso. Traitement du Signal 38(1)

Alotaiby T, El-Samie FEA, Alshebeili SA, Ahmad I (2015) A review of channel selection algorithms for eeg signal processing. EURASIP J Adv Signal Process 2015:1–21

Article  Google Scholar 

Alotaiby T, El-Samie FEA, Alshebeili SA, Ahmad I (2015) A review of channel selection algorithms for eeg signal processing. EURASIP J Adv Signal Process 2015:1–21

Article  Google Scholar 

Al-Sharhan S, Karray F, Gueaieb W, Basir O (2001) Fuzzy entropy: a brief survey. In: 10th IEEE international conference on fuzzy systems.(Cat. No. 01CH37297), vol 3. IEEE, pp 1135–1139

Ando M, Nobukawa S, Kikuchi M, Takahashi T (2021) Identification of electroencephalogram signals in alzheimer’s disease by multifractal and multiscale entropy analysis. Front Neurosci 15:667614

Article  PubMed  PubMed Central  Google Scholar 

Aydın S, Güdücü Ç, Kutluk F, Öniz A, Özgören M (2019) The impact of musical experience on neural sound encoding performance. Neurosci Lett 694:124–128

Article  PubMed  Google Scholar 

Azami H, Daftarifard E, Humeau-Heurtier A, Fernandez A, Abasolo D, Rajji TK (2023) Assessment and comparison of nonlinear measures in resting-state magnetoencephalograms in alzheimer’s disease and mild cognitive impairment. J Alzheimer’s Dis (Preprint), 1–12

Bai R, Guo J, Ye X-Y, Xie Y, Xie T (2022) Oxidative stress: the core pathogenesis and mechanism of alzheimer’s disease. Ageing Res Rev 77:101619

Article  CAS  PubMed  Google Scholar 

Bavkar S, Iyer B, Deosarkar S (2019) Rapid screening of alcoholism: an eeg based optimal channel selection approach. IEEE Access 7:99670–99682

Article  Google Scholar 

Borde S, Ratnaparkhe V (2023) Optimization in channel selection for eeg signal analysis of sleep disorder subjects. J Integr Sci Technol 11(3):527–527

Google Scholar 

Cai L, Wei X, Wang J, Yu H, Deng B, Wang R (2018) Reconstruction of functional brain network in alzheimer’s disease via cross-frequency phase synchronization. Neurocomputing 314:490–500

Article  Google Scholar 

Cassani R, Falk TH, Fraga FJ, Kanda PA, Anghinah R (2014) The effects of automated artifact removal algorithms on electroencephalography-based alzheimer’s disease diagnosis. Front Aging Neurosci 6:55

Article  PubMed  PubMed Central  Google Scholar 

Cataldo A, Criscuolo S, De Benedetto E, Masciullo A, Pesola M, Picone J, Schiavoni R (2024) Eeg complexity-based algorithm using multiscale fuzzy entropy: towards a detection of alzheimer’s disease. Measurement 225:114040

Article  Google Scholar 

Çetin FH, Barış Usta M, Aydın S, Güven AS (2022) A case study on eeg analysis: embedding entropy estimations indicate the decreased neuro-cortical complexity levels mediated by methylphenidate treatment in children with adhd. Clin EEG Neurosci 53(5):406–417

Article  PubMed  Google Scholar 

Chen W, Zhuang J, Yu W, Wang Z (2009) Measuring complexity using fuzzyen, apen, and sampen. Med Eng Phys 31(1):61–68

Article  PubMed  Google Scholar 

Demuru M, La Cava SM, Pani SM, Fraschini M (2020) A comparison between power spectral density and network metrics: an eeg study. Biomed Signal Process Control 57:101760

Article  Google Scholar 

Doan DNT, Ku B, Choi J, Oh M, Kim K, Cha W, Kim JU (2021) Predicting dementia with prefrontal electroencephalography and event-related potential. Front Aging Neurosci 13:659817

Article  PubMed  PubMed Central  Google Scholar 

Echegoyen I, López-Sanz D, Martínez JH, Maestú F, Buldú JM (2020) Permutation entropy and statistical complexity in mild cognitive impairment and alzheimer’s disease: an analysis based on frequency bands. Entropy 22(1):116

Article  PubMed  PubMed Central  Google Scholar 

Ein Shoka AA, Alkinani MH, El-Sherbeny A, El-Sayed A, Dessouky MM (2021) Automated seizure diagnosis system based on feature extraction and channel selection using eeg signals. Brain Inform 8(1):1–16

Article  PubMed  PubMed Central  Google Scholar 

Gao Z, Dang W, Wang X, Hong X, Hou L, Ma K, Perc M (2021) Complex networks and deep learning for eeg signal analysis. Cogn Neurodyn 15:369–388

Article  PubMed  Google Scholar 

Ghosh M, Guha R, Alam I, Lohariwal P, Jalan D, Sarkar R (2019) Binary genetic swarm optimization: a combination of ga and pso for feature selection. J Intell Syst 29(1):1598–1610

Google Scholar 

Hadoush H, Alafeef M, Abdulhay E (2019) Automated identification for autism severity level: Eeg analysis using empirical mode decomposition and second order difference plot. Behav Brain Res 362:240–248

Article  PubMed  Google Scholar 

Hadoush H, Alafeef M, Abdulhay E (2019) Automated identification for autism severity level: Eeg analysis using empirical mode decomposition and second order difference plot. Behav Brain Res 362:240–248

Article  PubMed  Google Scholar 

Holland JH (1992) Genetic algorithms. Sci Am 267(1):66–73

Article  Google Scholar 

Hsu CF, Chao H-H, Yang AC, Yeh C-W, Hsu L, Chi S (2020) Discrimination of severity of alzheimer’s disease with multiscale entropy analysis of eeg dynamics. Appl Sci 10(4):1244

Article  Google Scholar 

Jellinger KA (2020) Neuropathology of the alzheimer’s continuum: an update. Free Neuropathol 1

Jie X, Cao R, Li L (2014) Emotion recognition based on the sample entropy of eeg. Bio-Med Mater Eng 24(1):1185–1192

Article  Google Scholar 

Karasu S, Altan A (2022) Crude oil time series prediction model based on lstm network with chaotic henry gas solubility optimization. Energy 242:122964

Article  Google Scholar 

Kira K, Rendell LA (1992) A practical approach to feature selection. In: Machine learning proceedings 1992. Elsevier, pp 249–256

Lambora A, Gupta K, Chopra K (2019) Genetic algorithm-A literature review. In: 2019 international conference on machine learning, big data, cloud and parallel computing (COMITCon). IEEE

Li X-l (2002) An optimizing method based on autonomous animats: fish-swarm algorithm. Syst Eng Theory Pract 22(11):32–38

Google Scholar 

Li M, Liu H, Zhu W, Yang J (2017) Applying improved multiscale fuzzy entropy for feature extraction of mi-eeg. Appl Sci 7(1):92

Article  CAS  Google Scholar 

Li P, Karmakar C, Yearwood J, Venkatesh S, Palaniswami M, Liu C (2018) Detection of epileptic seizure based on entropy analysis of short-term eeg. PLoS ONE 13(3):0193691

Article  Google Scholar 

Li J, Xu C, Zhang J, Jin C, Shi X, Zhang C, Jia S, Xu J, Gui X, Xing L et al (2021) Identification of mirna-target gene pairs in the parietal and frontal lobes of the brain in patients with alzheimer’s disease using bioinformatic analyses. Neurochem Res 46:964–979

Article  CAS  PubMed  Google Scholar 

Li F, Jiang L, Liao Y, Si Y, Yi C, Zhang Y, Zhu X, Yang Z, Yao D, Cao Z et al (2021) Brain variability in dynamic resting-state networks identified by fuzzy entropy: a scalp eeg study. J Neural Eng 18(4):046097

Article  Google Scholar 

Liu Q, Liu Y, Chen K, Wang L, Li Z, Ai Q, Ma L (2021) Research on channel selection and multi-feature fusion of eeg signals for mental fatigue detection. Entropy 23(4):457

Article  PubMed  PubMed Central  Google Scholar 

Luan X-Y, Li Z-P, Liu T-Z (2016) A novel attribute reduction algorithm based on rough set and improved artificial fish swarm algorithm. Neurocomputing 174:522–529

Article  Google Scholar 

Monllor P, Cervera-Ferri A, Lloret M-A, Esteve D, Lopez B, Leon J-L, Lloret A (2021) Electroencephalography as a non-invasive biomarker of alzheimer’s disease: a forgotten candidate to substitute csf molecules? Int J Mol Sci 22(19):10889

Article  CAS  PubMed  PubMed Central  Google Scholar 

Ngian Z-K, Tan Y-Y, Choo C-T, Lin W-Q, Leow C-Y, Mah S-J, Lai MK-P, Chen CL-H, Ong C-T (2022) Truncated tau caused by intron retention is enriched in alzheimer’s disease cortex and exhibits altered biochemical properties. Proc Natl Acad Sci 119(37):2204179119

Article  Google Scholar 

Niotis K, Akiyoshi K, Carlton C, Isaacson R (2022) Dementia prevention in clinical practice. In: Seminars in neurology, vol 42. Thieme Medical Publishers, Inc. 333 Seventh Avenue, 18th Floor, New York, NY, pp 525–548

Özçelik YB, Altan A (2023) A comparative analysis of artificial intelligence optimization algorithms for the selection of entropy-based features in the early detection of epileptic seizures. In: 2023 14th international conference on electrical and electronics engineering (ELECO). IEEE, pp 1–5

Özçelik YB, Altan A (2023) Overcoming nonlinear dynamics in diabetic retinopathy classification: a robust ai-based model with chaotic swarm intelligence optimization and recurrent long short-term memory. Fractal Fract 7(8):598

Article  Google Scholar 

Pachori RB, Patidar S (2014) Epileptic seizure classification in eeg signals using second-order difference plot of intrinsic mode functions. Comput Methods Programs Biomed 113(2):494–502

Article 

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