SSVEP and ERP while standing, walking and running

Mobile BCI dataset (SSVEP and ERP paradigms): EEG decoding results

Name: BCI Report: results on Mobile BCI dataset (SSVEP and ERP paradigms)
Creator: BCI Report
License: https://creativecommons.org/licenses/by/4.0/

Scalp- and ear-EEG dataset from Korea University (Lee et al., Scientific Data, 2021): 24 participants (23 for SSVEP) performed ERP and SSVEP BCI tasks on a treadmill while standing, walking and slightly running (0 to 2.0 m/s), recorded with 32-channel scalp-EEG, 14-channel ear-EEG, EOG and IMUs. Original release on OSF; NEMAR nm000201 (ERP) and nm000125 (SSVEP) are BIDS derivatives.

Also known as Mobile BCI dataset · Lee2021 · Lee2021Mobile · NEMAR nm000201 · NEMAR nm000125 · OSF r7s9b

Description sources pmc.ncbi.nlm.nih.gov · osf.io · nemar.org · nemar.org · doi.org · doi.org

Where it appears

Does EEG decoding still work while walking or running?

Published results

Every figure below is copied from a reviewed download, not recomputed for this page. Read each group with its protocol on the linked page.

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%)

Spectral ridge · Standing · scalp · 8 ch

85.0% (77.0%–92.0%)

Spectral ridge · Slow walk · 0.8 m/s · scalp · 8 ch

79.2% (70.1%–87.5%)

Spectral ridge · Fast walk · 1.6 m/s · scalp · 8 ch

77.2% (67.7%–85.7%)

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%)

Spectral ridge · Standing · ear · 14 ch

52.0% (46.9%–57.8%)

Spectral ridge · Slow walk · 0.8 m/s · ear · 14 ch

45.4% (40.7%–51.2%)

Spectral ridge · Fast walk · 1.6 m/s · ear · 14 ch

40.0% (36.4%–43.7%)

Balanced accuracy, 12 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
Spectral ridge	Standing · scalp · 8 ch	Balanced accuracy	85.0%77.0%–92.0%	23
Spectral ridge	Slow walk · 0.8 m/s · scalp · 8 ch	Balanced accuracy	79.2%70.1%–87.5%	23
Spectral ridge	Fast walk · 1.6 m/s · scalp · 8 ch	Balanced accuracy	77.2%67.7%–85.7%	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
Spectral ridge	Standing · ear · 14 ch	Balanced accuracy	52.0%46.9%–57.8%	23
Spectral ridge	Slow walk · 0.8 m/s · ear · 14 ch	Balanced accuracy	45.4%40.7%–51.2%	23
Spectral ridge	Fast walk · 1.6 m/s · ear · 14 ch	Balanced accuracy	40.0%36.4%–43.7%	23

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%)

Spectral ridge · Standing · scalp · 8 ch

78.7% (70.7%–86.1%)

Spectral ridge · Slow walk · 0.8 m/s · scalp · 8 ch

69.9% (61.2%–78.1%)

Spectral ridge · Fast walk · 1.6 m/s · scalp · 8 ch

68.6% (60.4%–76.3%)

LaBraM · Standing · scalp · 8 ch

59.5% (53.6%–65.5%)

LaBraM · Slow walk · 0.8 m/s · scalp · 8 ch

54.7% (49.5%–60.1%)

LaBraM · Fast walk · 1.6 m/s · scalp · 8 ch

47.8% (43.3%–52.3%)

CBraMod · Standing · scalp · 8 ch

59.9% (54.3%–65.4%)

CBraMod · Slow walk · 0.8 m/s · scalp · 8 ch

46.2% (41.1%–51.4%)

CBraMod · Fast walk · 1.6 m/s · scalp · 8 ch

46.0% (42.2%–49.6%)

Balanced accuracy, 12 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
Spectral ridge	Standing · scalp · 8 ch	Balanced accuracy	78.7%70.7%–86.1%	23
Spectral ridge	Slow walk · 0.8 m/s · scalp · 8 ch	Balanced accuracy	69.9%61.2%–78.1%	23
Spectral ridge	Fast walk · 1.6 m/s · scalp · 8 ch	Balanced accuracy	68.6%60.4%–76.3%	23
LaBraM	Standing · scalp · 8 ch	Balanced accuracy	59.5%53.6%–65.5%	23
LaBraM	Slow walk · 0.8 m/s · scalp · 8 ch	Balanced accuracy	54.7%49.5%–60.1%	23
LaBraM	Fast walk · 1.6 m/s · scalp · 8 ch	Balanced accuracy	47.8%43.3%–52.3%	23
CBraMod	Standing · scalp · 8 ch	Balanced accuracy	59.9%54.3%–65.4%	23
CBraMod	Slow walk · 0.8 m/s · scalp · 8 ch	Balanced accuracy	46.2%41.1%–51.4%	23
CBraMod	Fast walk · 1.6 m/s · scalp · 8 ch	Balanced accuracy	46.0%42.2%–49.6%	23

Movement · ERP

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

Method	Condition	Metric	Value	People
Temporal-feature L2 logistic regression	Standing · scalp · 32 ch	ROC AUC	0.8590.820–0.897	24
Temporal-feature L2 logistic regression	Slow walk · 0.8 m/s · scalp · 32 ch	ROC AUC	0.7400.703–0.777	24
Temporal-feature L2 logistic regression	Fast walk · 1.6 m/s · scalp · 32 ch	ROC AUC	0.6350.602–0.673	24
Temporal-feature L2 logistic regression	Running · 2.0 m/s · scalp · 32 ch	ROC AUC	0.5860.561–0.613	17
Temporal-feature L2 logistic regression	Standing · ear · 14 ch	ROC AUC	0.7340.694–0.774	24
Temporal-feature L2 logistic regression	Slow walk · 0.8 m/s · ear · 14 ch	ROC AUC	0.6280.595–0.661	24
Temporal-feature L2 logistic regression	Fast walk · 1.6 m/s · ear · 14 ch	ROC AUC	0.5630.540–0.587	24
Temporal-feature L2 logistic regression	Running · 2.0 m/s · ear · 14 ch	ROC AUC	0.5170.491–0.541	17

Source and licence

Mobile BCI dataset (SSVEP and ERP paradigms)

Credit Lee, Y., Shin, G., Lee, M., & Lee, S. (2026). Lee2021 – SSVEP paradigm of the Mobile BCI dataset (Version v1.0.2) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000125 · Lee, Y., Shin, G., Lee, M., & Lee, S. (2026). ERP paradigm of the Mobile BCI dataset (Version v1.0.2) [Data set]. NEMAR. https://doi.org/10.82901/nemar.nm000201

CC BY 4.0 · Dataset record ↗ · nemar.org ↗ · doi.org ↗

BCI Report does not redistribute any recording. These are aggregate measurements computed by BCI Report under the licence above; the data belong to the people credited.

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