journal article·2025Open access

GACL-Net: Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

Chayut Bunterngchit, Laith H. Baniata, Mohammad H. Baniata, Ashraf ALDabbas, Mohannad A. Khair, Thanaphon Chearanai, Sangwoo Kang

Computers, Materials & Continua· Volume 83· Issue 1

Abstract

Stroke is a leading cause of death and disability worldwide, significantly impairing motor and cognitive functions. Effective rehabilitation is often hindered by the heterogeneity of stroke lesions, variability in recovery pa... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Stroke Rehabilitation and Recovery · Medical Imaging and Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (33)

Show source-provided references
1. Functional ability and health problems of stroke survivors: an explorative study
2. A review of online classification performance in motor imagery-based brain-computer interfaces for stroke neurorehabilitation10.3390/signals4010004 ↗
3. Enhanced EEG-fNIRS classification through concatenated convolutional neural network with band analysis
4. EEG- and EMG-driven poststroke rehabilitation: a review10.1109/JSEN.2022.3220930 ↗
5. The association between mental motor imagery and real movement in stroke10.3390/healthcare9111568 ↗
6. Recovery of neural dynamics criticality in personalized whole-brain models of stroke10.1038/s41467-022-30892-6 ↗
7. Electroencephalogram (EEG) with or without Transcranial Magnetic Stimulation (TMS) as biomarkers for post-stroke recovery: a narrative review10.3389/fneur.2022.827866 ↗
8. Cross-subject motor imagery decoding by transfer learning of tactile ERD10.1109/TNSRE.2024.3358491 ↗
9. EEG-based BCIs on motor imagery paradigm using wearable technologies: a systematic review10.3390/s23052798 ↗
10. AMFN: autoencoder-led multimodal fusion network for EEG-fNIRS classification10.1016/j.procs.2024.11.002 ↗
11. Motor imagery brain-computer interface rehabilitation system enhances upper limb performance and improves brain activity in stroke patients: a clinical study10.3389/fnhum.2023.1117670 ↗
12. Rehabilitation with brain-computer interface and upper limb motor function in ischemic stroke: a randomized controlled trial10.1016/j.medj.2024.02.014 ↗
13. Virtual reality assisted motor imagery for early post-stroke recovery: a review10.1109/RBME.2022.3165062 ↗
14. Improving motor imagery classification for stroke rehabilitation using a stroke-aware capsule attention network
15. EEG analytics: benefits and challenges of data driven EEG biomarkers for neurodegenerative diseases
16. Simultaneous EEG-fNIRS data classification through selective channel representation and spectrogram imaging10.1109/JTEHM.2024.3448457 ↗
17. Motor imagery EEG signal classification for stroke survivors rehabilitation
18. Identification of post-stroke EEG signal using wavelet and convolutional neural networks10.11591/eei.v9i5.2005 ↗
19. Deep learning based prediction of EEG motor imagery of stroke patients’ for neuro-rehabilitation application
20. Classification of left-versus right-hand motor imagery in stroke patients using supplementary data generated by CycleGAN10.1109/TNSRE.2021.3123969 ↗
21. Performance of EEG motor-imagery based spatial filtering methods: a BCI study on Stroke patients10.1016/j.procs.2020.09.270 ↗
22. Towards robust cross-subject EEG-fNIRS classification: a hybrid deep learning model with optimized feature selection
23. Motor imagery hand movement direction decoding using brain computer interface to aid stroke recovery and rehabilitation10.1109/TNSRE.2020.3039331 ↗
24. A transfer learning framework based on motor imagery rehabilitation for stroke10.1038/s41598-021-99114-1 ↗
25. Combining generative adversarial network and multi-output CNN for motor imagery classification
26. LSTM-based EEG classification in motor imagery tasks10.1109/TNSRE.2018.2876129 ↗
27. Deep convolution generative adversarial network-based electroencephalogram data augmentation for post-stroke rehabilitation with motor imagery10.1142/S0129065722500393 ↗
28. CNN models for EEG motor imagery signal classification10.1007/s11760-022-02293-1 ↗
29. An EEG motor imagery dataset for brain computer interface in acute stroke patients
30. Jia T. EEG data of motor imagery for stroke. figshare; 2019 [cited 2025 Jan 31]. Available from: https://figshare.com/articles/EEG_data_of_motor_imagery_for_stroke_patients/7636301/6.
31. Optimized deep learning model using modified whale’s optimization algorithm for EEG signal classification10.5755/j01.itc.52.3.33320 ↗
32. A geneticalgorithm-based feature selection
33. Temporal attention fusion network with custom loss function for EEG-fNIRS classification10.1088/1741-2552/ad8e86 ↗