# Motor Imagery Decoding on GigaDB Dataset II Source: [Motor Imagery Decoding on GigaDB Dataset II]() Collection index: [llms.txt]() Data updated: 2026-03-26T15:18:01.506Z Evaluation of Motor Imagery Decoding performance on the GigaDB Dataset II, reporting accuracy metrics for individual subjects (1-10) and overall Kappa statistics. A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. | Scope | Recorded value | | --- | --- | | Task | Motor Imagery Decoding | | Dataset (including any stated split) | GigaDB Dataset II | | Metric | Subject 1 Accuracy | | Unit | PERCENT | | Direction | Higher is better | | Results loaded | 11 of 11 | | Coverage | All results currently returned for this benchmark | Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol. ## Metrics - [Subject 1 Accuracy](): Higher is better; unit: PERCENT. - [Subject 2 Accuracy](): Higher is better; unit: PERCENT. - [Subject 3 Accuracy](): Higher is better; unit: PERCENT. - [Subject 4 Accuracy](): Higher is better; unit: PERCENT. - [Subject 5 Accuracy](): Higher is better; unit: PERCENT. - [Subject 6 Accuracy](): Higher is better; unit: PERCENT. - [Subject 7 Accuracy](): Higher is better; unit: PERCENT. - [Subject 8 Accuracy](): Higher is better; unit: PERCENT. - [Subject 9 Accuracy](): Higher is better; unit: PERCENT. - [Subject 10 Accuracy](): Higher is better; unit: PERCENT. - [Average Accuracy](): Higher is better; unit: PERCENT. - [Kappa](): Higher is better; unit: SCALAR. ## Recorded results | Method | Subject 1 Accuracy | Result date | Report paper | | --- | --- | --- | --- | | BFM-MSDA | 80.52 | Not recorded | 68fa7a4b1e209131cea8244a | | ASJDA | 79.03 | Not recorded | 68fa7a4b1e209131cea8244a | | DJDAN | 78.36 | Not recorded | 68fa7a4b1e209131cea8244a | | JAN | 78.27 | Not recorded | 68fa7a4b1e209131cea8244a | | Conformer | 77.62 | Not recorded | 68fa7a4b1e209131cea8244a | | DJP-MMD | 76.31 | Not recorded | 68fa7a4b1e209131cea8244a | | GAT | 76.25 | Not recorded | 68fa7a4b1e209131cea8244a | | ShallowConvNet | 73.92 | Not recorded | 68fa7a4b1e209131cea8244a | | EEGNet | 66.57 | Not recorded | 68fa7a4b1e209131cea8244a | | CBraMod | 61.37 | Not recorded | 68fa7a4b1e209131cea8244a | | LaBraM | 56.72 | Not recorded | 68fa7a4b1e209131cea8244a | ### BFM-MSDA Subject 1 Accuracy: 80.52. Result ID: 69c54d9247f34ce924af7add. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### ASJDA Subject 1 Accuracy: 79.03. Result ID: 69c54d9247f34ce924af7ad9. [Reporting paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### DJDAN Subject 1 Accuracy: 78.36. Result ID: 69c54d9247f34ce924af7ada. [Reporting paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### JAN Subject 1 Accuracy: 78.27. Result ID: 69c54d9247f34ce924af7ad6. [Reporting paper]() [Method origin paper]() [Implementation]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### Conformer Subject 1 Accuracy: 77.62. Result ID: 69c54d9247f34ce924af7ad5. [Reporting paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### DJP-MMD Subject 1 Accuracy: 76.31. Result ID: 69c54d9247f34ce924af7ad7. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### GAT Subject 1 Accuracy: 76.25. Result ID: 69c54d9247f34ce924af7ad8. [Reporting paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### ShallowConvNet Subject 1 Accuracy: 73.92. Result ID: 69c54d9247f34ce924af7ad4. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### EEGNet Subject 1 Accuracy: 66.57. Result ID: 69c54d9247f34ce924af7ad3. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### CBraMod Subject 1 Accuracy: 61.37. Result ID: 69c54d9247f34ce924af7adc. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Classification Head":"Linear","Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. ### LaBraM Subject 1 Accuracy: 56.72. Result ID: 69c54d9247f34ce924af7adb. [Reporting paper]() [Method origin paper]() Recorded evaluation configuration: {"Classification Head":"Linear","Evaluation Protocol":"Cross-subject"}. This record does not assert independent reproduction. Page 1 of 1. This is an index page, not the full collection.