Classical method

CCA: results on public EEG datasets

CCA-based SSVEP detection, proposed by Lin, Zhang, Wu and Gao (Tsinghua University; IEEE Transactions on Biomedical Engineering, 2006), computes the canonical correlation between multichannel EEG and sine–cosine reference signals at each candidate stimulus frequency and its harmonics. The frequency with the largest correlation is selected; the references are generated from the stimulus frequencies, not learned from recorded trials.

Also known as CCA · Standard CCA · canonical correlation analysis · Lin et al. 2006

Reference Lin Z, Zhang C, Wu W, Gao X. Frequency recognition based on canonical correlation analysis for SSVEP-based BCIs. IEEE Transactions on Biomedical Engineering 53(12):2610–2614, 2006. ↗

Directory status: Evaluated · Implementation used here ↗ · Description sources pubmed.ncbi.nlm.nih.gov · pubmed.ncbi.nlm.nih.gov · doi.org · doi.org · pmc.ncbi.nlm.nih.gov · github.com · iopscience.iop.org

Published results

Grouped by dataset. Compare figures within a group only: across groups the task, cohort, chance level and electrode layout all change.

BETA · Core matrix · SSVEP, 8 channels

Read with its protocol: Core matrix (home page) · Chance level 2.5% · experiments.json

Method	Condition	Metric	Value	People
Standard CCA	40 visual targets · 8 posterior electrodes	Balanced accuracy	63.1%57.2%–69.0%	70

BETA · Core matrix · SSVEP, 4 channels

Read with its protocol: Core matrix (home page) · Chance level 2.5% · experiments.json

Method	Condition	Metric	Value	People
Standard CCA	40 visual targets · 4 posterior electrodes	Balanced accuracy	57.6%51.8%–63.5%	70

Wearable SSVEP BCI dataset (dry and wet electrodes) · Dry vs. wet sensor transfer

Read with its protocol: Dry vs. wet electrodes · deployment-topics.json

CCA · Wet recording · no source training

81.6% (77.7%–85.1%)

CCA · Dry recording · no source training

65.5% (60.6%–70.2%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
CCA	Wet recording · no source training	Balanced accuracy	81.6%77.7%–85.1%	102
CCA	Dry recording · no source training	Balanced accuracy	65.5%60.6%–70.2%	102

Wearable SSVEP BCI dataset (dry and wet electrodes) · Calibration budget · eTRCA and CCA

Read with its protocol: How much calibration? · deployment-topics.json

CCA · No calibration · dry

65.1% (60.0%–70.0%)

CCA · No calibration · wet

81.1% (77.2%–84.8%)

Balanced accuracy, 2 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
CCA	No calibration · dry	Balanced accuracy	65.1%60.0%–70.0%	102
CCA	No calibration · wet	Balanced accuracy	81.1%77.2%–84.8%	102

Mobile BCI dataset (SSVEP and ERP paradigms) · Movement · SSVEP, 5-second windows

Read with its protocol: On the move · deployment-topics.json

Author-style CCA · Standing · scalp · 8 ch

88.7% (80.0%–95.9%)

Author-style CCA · Slow walk · 0.8 m/s · scalp · 8 ch

82.9% (74.3%–90.4%)

Author-style CCA · Fast walk · 1.6 m/s · scalp · 8 ch

80.9% (72.0%–88.8%)

Author-style CCA · Standing · ear · 14 ch

53.1% (47.4%–59.6%)

Author-style CCA · Slow walk · 0.8 m/s · ear · 14 ch

43.4% (39.6%–47.8%)

Author-style CCA · Fast walk · 1.6 m/s · ear · 14 ch

39.1% (36.7%–41.8%)

Balanced accuracy, 6 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
Author-style CCA	Standing · scalp · 8 ch	Balanced accuracy	88.7%80.0%–95.9%	23
Author-style CCA	Slow walk · 0.8 m/s · scalp · 8 ch	Balanced accuracy	82.9%74.3%–90.4%	23
Author-style CCA	Fast walk · 1.6 m/s · scalp · 8 ch	Balanced accuracy	80.9%72.0%–88.8%	23
Author-style CCA	Standing · ear · 14 ch	Balanced accuracy	53.1%47.4%–59.6%	23
Author-style CCA	Slow walk · 0.8 m/s · ear · 14 ch	Balanced accuracy	43.4%39.6%–47.8%	23
Author-style CCA	Fast walk · 1.6 m/s · ear · 14 ch	Balanced accuracy	39.1%36.7%–41.8%	23

Mobile BCI dataset (SSVEP and ERP paradigms) · Movement · SSVEP, 2-second windows

Read with its protocol: On the move · deployment-topics.json

Author-style CCA · Standing · scalp · 8 ch

82.3% (74.6%–89.4%)

Author-style CCA · Slow walk · 0.8 m/s · scalp · 8 ch

70.7% (62.3%–78.6%)

Author-style CCA · Fast walk · 1.6 m/s · scalp · 8 ch

68.6% (60.1%–76.7%)

Balanced accuracy, 3 configurations. Dot: the estimate; line: 95% interval; dashed line: chance level where the payload records one.

Method	Condition	Metric	Value	People
Author-style CCA	Standing · scalp · 8 ch	Balanced accuracy	82.3%74.6%–89.4%	23
Author-style CCA	Slow walk · 0.8 m/s · scalp · 8 ch	Balanced accuracy	70.7%62.3%–78.6%	23
Author-style CCA	Fast walk · 1.6 m/s · scalp · 8 ch	Balanced accuracy	68.6%60.1%–76.7%	23

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