*Result*: Energy-Efficient EEG-Based Autism Spectrum Disorder Detection Using a Hyperbolic Attention Neural Network.
Title:
Energy-Efficient EEG-Based Autism Spectrum Disorder Detection Using a Hyperbolic Attention Neural Network.
Authors:
S AA; John Cox Memorial CSI Institute of Technology, Thiruvananthapuram, Kerala, India., K P; Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India., Guganathan L; Department of Physics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Science (SIMATS), Chennai, India., J A; National Centre for Assistive Health Technologies (NCAHT), IIT Delhi (Senior Project Scientist), New Delhi, India.
Source:
Developmental neurobiology [Dev Neurobiol] 2026 Apr; Vol. 86 (2), pp. e70011.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Wiley Subscription Services, Inc Country of Publication: United States NLM ID: 101300215 Publication Model: Print Cited Medium: Internet ISSN: 1932-846X (Electronic) Linking ISSN: 19328451 NLM ISO Abbreviation: Dev Neurobiol Subsets: MEDLINE
Imprint Name(s):
Original Publication: Hoboken, NJ : Wiley Subscription Services, Inc.
MeSH Terms:
References:
Abedinzadeh Torghabeh, F., Y. Modaresnia, and M. H. Moattar. 2024. “Hybrid Deep Transfer Learning‐Based Early Diagnosis of Autism Spectrum Disorder Using Scalogram Representation of Electroencephalography Signals.” Medical & Biological Engineering & Computing 62, no. 2: 495–503.
Aghamaleki, J. A., and A. Ghorbani. 2023. “Image Fusion Using Dual Tree Discrete Wavelet Transform & Weights Optimization.” Visual Computer 39, no. 3: 1181–1191.
Alhassan, S., A. Soudani, and M. Almusallam. 2023. “Energy‐Efficient EEG‐Based Scheme for Autism Spectrum Disorder Detection Using Wearable Sensors.” Sensors 23, no. 4: 2228.
Al‐Qazzaz, N. K., A. A. Aldoori, A. K. Buniya, S. H. B. M. Ali, and S. A. Ahmad. 2024. “Transfer Learning & Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From Eeg Signals.” IEEE Access 12: 64510–64530.
Bouaouda, A., F. A. Hashim, Y. Sayouti, and A. G. Hussien. 2024. “Pied Kingfisher Optimizer: A New Bio‐Inspired Algorithm for Solving Numerical Optimization & Industrial Engineering Problems.” Neural Computing & Applications 36, no. 25: 15455–15513.
Brihadiswaran, G., D. Haputhanthri, S. Gunathilaka, D. Meedeniya, and S. Jayarathna. 2019. “EEG‐Based Processing and Classification Methodologies for Autism Spectrum Disorder: A Review.” Journal of Computer Science 15, no. 8: 1161–1183.
Chawla, P., S. B. Rana, H. Kaur, and K. Singh. 2024. “Diagnosis of Autism Spectrum Disorder Using EEMD & Multi‐Scale Fluctuation Based Dispersion Entropy With Bayesian Optimized Light GBM.” Multimedia Tools & Applications 83, no. 24: 65341–65362.
Cheng, M., Y. Zhang, Y. Xie, et al. 2023. “Computer‐Aided Autism Spectrum Disorder Diagnosis With Behavior Signal Processing.” IEEE Transactions on Affective Computing 14, no. 4: 2982–3000.
Divya, B., N. Udayakumar, R. Yuvaraj, and A. Kavitha. 2023. “Classification of Low‐Functioning & High‐Functioning Autism Using Task‐Based EEG Signals.” Biomedical Signal Processing & Control 85: 105074.
Geng, X., X. Fan, Y. Zhong, et al. 2023. “Abnormalities of EEG Functional Connectivity & Effective Connectivity in Children With Autism Spectrum Disorder.” Brain Sciences 13, no. 1: 130.
Haputhanthri, D., G. Brihadiswaran, S. Gunathilaka, et al. 2019. “An EEG Based Channel Optimized Classification Approach for Autism Spectrum Disorder.” In 2019 Moratuwa Engineering Research Conference (MERCon). IEEE.
Haputhanthri, D., G. Brihadiswaran, S. Gunathilaka, et al. 2020. “Integration of Facial Thermography in EEG‐Based Classification of ASD.” International Journal of Automation and Computing 17, no. 6: 837–854.
Kang, J., S. Lv, Y. Li, P. Hao, X. Li, and C. Gao. 2025. “The Effects of Neurofeedback Training on Behavior & Brain Functional Networks in Children With Autism Spectrum Disorder.” Behavioural Brain Research 481: 115425.
Lakhan, A., M. A. Mohammed, K. H. Abdulkareem, H. Hamouda, and S. Alyahya. 2023. “Autism Spectrum Disorder Detection Framework for Children Based on Federated Learning Integrated CNN‐LSTM.” Computers in Biology & Medicine 166: 107539.
Lalawat, R. S., and V. Bajaj. 2024. “An Automatic Framework for Detecting Autism Spectrum Disorder From Eeg Signals Using tfd.” IEEE Sensors Journal 24, no. 7: 10632–10639.
Lensink, K., B. Peters, and E. Haber. 2022. “Fully Hyperbolic Convolutional Neural Networks.” Research in the Mathematical Sciences 9, no. 4: 60.
Li, J., X. Jia, X. Chen, G. Li, and G. Ouyang. 2025. “LSTA‐CNN: A Lightweight Spatio‐Temporal Attention‐Based Convolutional Neural Network for ASD Diagnosis Using EEG.” In IEEE Transactions on Neural Systems & Rehabilitation Engineering. IEEE.
Lian, J., G. Hui, L. Ma, et al. 2024. “Parrot Optimizer: Algorithm & Applications to Medical Problems.” Computers in Biology & Medicine 172: 108064.
Loganathan, S., C. Geetha, A. R. Nazaren, and M. H. F. Fern&ez. 2023. “Autism Spectrum Disorder Detection & Classification Using Chaotic Optimization Based Bi‐GRU Network: An Weighted Average Ensemble Model.” Expert Systems With Applications 230: 120613.
Lou, S., J. Deng, and S. Lyu. 2022. “Chaotic Signal Denoising Based on Simplified Convolutional Denoising Auto‐Encoder.” Chaos, Solitons & Fractals 161: 112333.
Meera, S. 2025. “An Enhanced Detection System of Autism Spectrum Disorder Using Thermal Imaging & Deep Learning.” SN Computer Science 6, no. 2: 169.
Neurazum. Disorders and Diagnosis EEG Dataset ‐ v5, Jul 2025. https://www.kaggle.com/datasets/eyppler/disorders‐and‐diagnosis‐eeg‐dataset‐v5.
Peketi, S., and S. B. Dhok. 2023. “Machine Learning Enabled p300 Classifier for Autism Spectrum Disorder Using Adaptive Signal Decomposition.” Brain Sciences 13, no. 2: 315.
PL, L., S. K. E, A. Radhakrishnan, and S. G. 2025. “Real‐Time Classification for EEG Data in Children With ASD Using Deep Learning Techniques.” Developmental Neurobiology 85, no. 4: e23009.
Radhakrishnan, M., V. Govindan, K. Ramamurthy, and S. Saranya. 2024. “Graphical Attention Networks for Autism Spectrum Disorder Classification.” Proceedings of the Indian National Science Academy 91: 581–588.
Saranya, S., and R. Menaka. 2025. “An Explainable Machine Learning Network for Classification of Autism Spectrum Disorder Using Optimal Frequency B& Identification From Brain EEG.” IEEE Access 13: 32016–32030.
Senthilkumar, R. 2025. “DSVTN‐ASD: Detection of Stereotypical Behaviors in Individuals With Autism Spectrum Disorder Using a Dual Self‐Supervised Video Transformer Network.” Neurocomputing 624: 129397.
Shinde, A. V., and D. D. Patil. 2023. “A Multi‐Classifier‐Based Recommender System for Early Autism Spectrum Disorder Detection Using Machine Learning.” Healthcare Analytics 4: 100211.
Siddiqui, U. A., F. Ullah, A. Iqbal, et al. 2021. “Wearable‐Sensors‐Based Platform for Gesture Recognition of Autism Spectrum Disorder Children Using Machine Learning Algorithms.” Sensors 21, no. 10: 3319.
Singh, J. K., and D. Kakkar. 2024a. “Chronological Sewing Training Optimization Enabled Deep Learning for Autism Spectrum Disorder Using EEG Signal.” Multimedia Tools & Applications 83, no. 30: 74177–74204.
Singh, J. K., and D. Kakkar. 2024b. “Hybrid Similarity Based Feature Selection & Cascade Deep Maxout Fuzzy Network for Autism Spectrum Disorder Detection Using EEG Signal.” Computational Biology & Chemistry 113: 108177.
Subudhi, A. K., M. Mohanty, S. K. Sahoo, S. K. Mohanty, and B. Mohanty. 2023. “Automated Delimitation & Classification of Autistic Disorder Using EEG Signal.” IETE Journal of Research 69, no. 2: 951–959.
Tawhid, M. N. A., S. Siuly, K. Wang, and H. Wang. 2024. “GENet: A Generic Neural Network for Detecting Various Neurological Disorders From EEG.” IEEE Transactions on Cognitive and Developmental Systems 16, no. 5: 1829–1842.
Toranjsimin, A., S. Zahedirad, and M. H. Moattar. 2024. “Robust Low Complexity Framework for Early Diagnosis of Autism Spectrum Disorder Based on Cross Wavelet Transform & Deep Transfer Learning.” SN Computer Science 5, no. 2: 231.
Ullah, F., N. A. AbuAli, A. Ullah, R. Ullah, U. A. Siddiqui, and A. A. Siddiqui. 2023. “Fusion‐Based Body‐Worn IoT Sensor Platform for Gesture Recognition of Autism Spectrum Disorder Children.” Sensors 23, no. 3: 1672.
Wadhera, T., J. Bedi, and S. Sharma. 2023. “Autism Spectrum Disorder Prediction Using Bidirectional Stacked Gated Recurrent Unit With Time‐Distributor Wrapper: An EEG Study.” Neural Computing & Applications 35, no. 13: 9803–9818.
Wen, Z., W. Lin, T. Wang, and G. Xu. 2023. “Distract Your Attention: Multi‐Head Cross Attention Network for Facial Expression Recognition.” Biomimetics 8, no. 2: 199.
Xu, Y., Z. Yu, Y. Li, Y. Liu, Y. Li, and Y. Wang. 2024. “Autism Spectrum Disorder Diagnosis With EEG Signals Using Time Series Maps of Brain Functional Connectivity & a Combined CNN–LSTM Model.” Computer Methods & Programs in Biomedicine 250: 108196.
Aghamaleki, J. A., and A. Ghorbani. 2023. “Image Fusion Using Dual Tree Discrete Wavelet Transform & Weights Optimization.” Visual Computer 39, no. 3: 1181–1191.
Alhassan, S., A. Soudani, and M. Almusallam. 2023. “Energy‐Efficient EEG‐Based Scheme for Autism Spectrum Disorder Detection Using Wearable Sensors.” Sensors 23, no. 4: 2228.
Al‐Qazzaz, N. K., A. A. Aldoori, A. K. Buniya, S. H. B. M. Ali, and S. A. Ahmad. 2024. “Transfer Learning & Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From Eeg Signals.” IEEE Access 12: 64510–64530.
Bouaouda, A., F. A. Hashim, Y. Sayouti, and A. G. Hussien. 2024. “Pied Kingfisher Optimizer: A New Bio‐Inspired Algorithm for Solving Numerical Optimization & Industrial Engineering Problems.” Neural Computing & Applications 36, no. 25: 15455–15513.
Brihadiswaran, G., D. Haputhanthri, S. Gunathilaka, D. Meedeniya, and S. Jayarathna. 2019. “EEG‐Based Processing and Classification Methodologies for Autism Spectrum Disorder: A Review.” Journal of Computer Science 15, no. 8: 1161–1183.
Chawla, P., S. B. Rana, H. Kaur, and K. Singh. 2024. “Diagnosis of Autism Spectrum Disorder Using EEMD & Multi‐Scale Fluctuation Based Dispersion Entropy With Bayesian Optimized Light GBM.” Multimedia Tools & Applications 83, no. 24: 65341–65362.
Cheng, M., Y. Zhang, Y. Xie, et al. 2023. “Computer‐Aided Autism Spectrum Disorder Diagnosis With Behavior Signal Processing.” IEEE Transactions on Affective Computing 14, no. 4: 2982–3000.
Divya, B., N. Udayakumar, R. Yuvaraj, and A. Kavitha. 2023. “Classification of Low‐Functioning & High‐Functioning Autism Using Task‐Based EEG Signals.” Biomedical Signal Processing & Control 85: 105074.
Geng, X., X. Fan, Y. Zhong, et al. 2023. “Abnormalities of EEG Functional Connectivity & Effective Connectivity in Children With Autism Spectrum Disorder.” Brain Sciences 13, no. 1: 130.
Haputhanthri, D., G. Brihadiswaran, S. Gunathilaka, et al. 2019. “An EEG Based Channel Optimized Classification Approach for Autism Spectrum Disorder.” In 2019 Moratuwa Engineering Research Conference (MERCon). IEEE.
Haputhanthri, D., G. Brihadiswaran, S. Gunathilaka, et al. 2020. “Integration of Facial Thermography in EEG‐Based Classification of ASD.” International Journal of Automation and Computing 17, no. 6: 837–854.
Kang, J., S. Lv, Y. Li, P. Hao, X. Li, and C. Gao. 2025. “The Effects of Neurofeedback Training on Behavior & Brain Functional Networks in Children With Autism Spectrum Disorder.” Behavioural Brain Research 481: 115425.
Lakhan, A., M. A. Mohammed, K. H. Abdulkareem, H. Hamouda, and S. Alyahya. 2023. “Autism Spectrum Disorder Detection Framework for Children Based on Federated Learning Integrated CNN‐LSTM.” Computers in Biology & Medicine 166: 107539.
Lalawat, R. S., and V. Bajaj. 2024. “An Automatic Framework for Detecting Autism Spectrum Disorder From Eeg Signals Using tfd.” IEEE Sensors Journal 24, no. 7: 10632–10639.
Lensink, K., B. Peters, and E. Haber. 2022. “Fully Hyperbolic Convolutional Neural Networks.” Research in the Mathematical Sciences 9, no. 4: 60.
Li, J., X. Jia, X. Chen, G. Li, and G. Ouyang. 2025. “LSTA‐CNN: A Lightweight Spatio‐Temporal Attention‐Based Convolutional Neural Network for ASD Diagnosis Using EEG.” In IEEE Transactions on Neural Systems & Rehabilitation Engineering. IEEE.
Lian, J., G. Hui, L. Ma, et al. 2024. “Parrot Optimizer: Algorithm & Applications to Medical Problems.” Computers in Biology & Medicine 172: 108064.
Loganathan, S., C. Geetha, A. R. Nazaren, and M. H. F. Fern&ez. 2023. “Autism Spectrum Disorder Detection & Classification Using Chaotic Optimization Based Bi‐GRU Network: An Weighted Average Ensemble Model.” Expert Systems With Applications 230: 120613.
Lou, S., J. Deng, and S. Lyu. 2022. “Chaotic Signal Denoising Based on Simplified Convolutional Denoising Auto‐Encoder.” Chaos, Solitons & Fractals 161: 112333.
Meera, S. 2025. “An Enhanced Detection System of Autism Spectrum Disorder Using Thermal Imaging & Deep Learning.” SN Computer Science 6, no. 2: 169.
Neurazum. Disorders and Diagnosis EEG Dataset ‐ v5, Jul 2025. https://www.kaggle.com/datasets/eyppler/disorders‐and‐diagnosis‐eeg‐dataset‐v5.
Peketi, S., and S. B. Dhok. 2023. “Machine Learning Enabled p300 Classifier for Autism Spectrum Disorder Using Adaptive Signal Decomposition.” Brain Sciences 13, no. 2: 315.
PL, L., S. K. E, A. Radhakrishnan, and S. G. 2025. “Real‐Time Classification for EEG Data in Children With ASD Using Deep Learning Techniques.” Developmental Neurobiology 85, no. 4: e23009.
Radhakrishnan, M., V. Govindan, K. Ramamurthy, and S. Saranya. 2024. “Graphical Attention Networks for Autism Spectrum Disorder Classification.” Proceedings of the Indian National Science Academy 91: 581–588.
Saranya, S., and R. Menaka. 2025. “An Explainable Machine Learning Network for Classification of Autism Spectrum Disorder Using Optimal Frequency B& Identification From Brain EEG.” IEEE Access 13: 32016–32030.
Senthilkumar, R. 2025. “DSVTN‐ASD: Detection of Stereotypical Behaviors in Individuals With Autism Spectrum Disorder Using a Dual Self‐Supervised Video Transformer Network.” Neurocomputing 624: 129397.
Shinde, A. V., and D. D. Patil. 2023. “A Multi‐Classifier‐Based Recommender System for Early Autism Spectrum Disorder Detection Using Machine Learning.” Healthcare Analytics 4: 100211.
Siddiqui, U. A., F. Ullah, A. Iqbal, et al. 2021. “Wearable‐Sensors‐Based Platform for Gesture Recognition of Autism Spectrum Disorder Children Using Machine Learning Algorithms.” Sensors 21, no. 10: 3319.
Singh, J. K., and D. Kakkar. 2024a. “Chronological Sewing Training Optimization Enabled Deep Learning for Autism Spectrum Disorder Using EEG Signal.” Multimedia Tools & Applications 83, no. 30: 74177–74204.
Singh, J. K., and D. Kakkar. 2024b. “Hybrid Similarity Based Feature Selection & Cascade Deep Maxout Fuzzy Network for Autism Spectrum Disorder Detection Using EEG Signal.” Computational Biology & Chemistry 113: 108177.
Subudhi, A. K., M. Mohanty, S. K. Sahoo, S. K. Mohanty, and B. Mohanty. 2023. “Automated Delimitation & Classification of Autistic Disorder Using EEG Signal.” IETE Journal of Research 69, no. 2: 951–959.
Tawhid, M. N. A., S. Siuly, K. Wang, and H. Wang. 2024. “GENet: A Generic Neural Network for Detecting Various Neurological Disorders From EEG.” IEEE Transactions on Cognitive and Developmental Systems 16, no. 5: 1829–1842.
Toranjsimin, A., S. Zahedirad, and M. H. Moattar. 2024. “Robust Low Complexity Framework for Early Diagnosis of Autism Spectrum Disorder Based on Cross Wavelet Transform & Deep Transfer Learning.” SN Computer Science 5, no. 2: 231.
Ullah, F., N. A. AbuAli, A. Ullah, R. Ullah, U. A. Siddiqui, and A. A. Siddiqui. 2023. “Fusion‐Based Body‐Worn IoT Sensor Platform for Gesture Recognition of Autism Spectrum Disorder Children.” Sensors 23, no. 3: 1672.
Wadhera, T., J. Bedi, and S. Sharma. 2023. “Autism Spectrum Disorder Prediction Using Bidirectional Stacked Gated Recurrent Unit With Time‐Distributor Wrapper: An EEG Study.” Neural Computing & Applications 35, no. 13: 9803–9818.
Wen, Z., W. Lin, T. Wang, and G. Xu. 2023. “Distract Your Attention: Multi‐Head Cross Attention Network for Facial Expression Recognition.” Biomimetics 8, no. 2: 199.
Xu, Y., Z. Yu, Y. Li, Y. Liu, Y. Li, and Y. Wang. 2024. “Autism Spectrum Disorder Diagnosis With EEG Signals Using Time Series Maps of Brain Functional Connectivity & a Combined CNN–LSTM Model.” Computer Methods & Programs in Biomedicine 250: 108196.
Contributed Indexing:
Keywords: Pied Kingfisher Optimization Algorithm; autism spectrum disorder detection; deep learning; electroencephalography (EEG) signal; parrot optimization; wearable sensors
Entry Date(s):
Date Created: 20260129 Date Completed: 20260129 Latest Revision: 20260129
Update Code:
20260130
DOI:
10.1002/dneu.70011
PMID:
41607078
Database:
MEDLINE
*Further Information*
*Long-term physiological monitoring using wearable wireless systems represents a paradigm change in next-generation e-health applications. Specifically, electroencephalography (EEG) represents a noninvasive and trustworthy way of recording brain activity and is a likely candidate for the early diagnosis of autism spectrum disorder (ASD). Yet, conventional methods involving the streaming of raw EEG signals to outside servers for classification consume significant energy and drastically shorten the operational life of wearable sensors. In response to these gaps, this research introduced an energy-aware, sensor-based scheme for ASD detection during early childhood from EEG signals. The system exploits on-node signal denoising via chaotic signal models, feature extraction by dual tree discrete wavelet transform (DT-DWT), and lightweight feature selection by parrot optimization (PO). The core detection is executed via a new Hyperbolic Cross-Head Attention-Based Neural Network (HyperCrossNet) that proposes deep reversible learning in conjunction with spatial and channel-oriented attention mechanisms. The network weights are then optimized by the Pied Kingfisher Optimization Algorithm (PKO) for improved accuracy. Experimental outcomes indicate 99.92% classification, 99.91% recall, and a 99.90% F1-score not mentioning that it has lowered considerably the amount of energy used to transmit the raw data. This effective design enables real-time wearable detection useful and applicable to long-term monitoring.
(© 2026 Wiley Periodicals LLC.)*