Motor-Processed

Processed HDF5 export of the Wu et al. 2020 in-ear / scalp EEG motor dataset — paired in-ear EEG + high-density scalp EEG recorded while 6 subjects performed a 2-class left / right hand grasp task. This repo holds the two processed HDF5 files (one per modality); the raw Curry-7 recordings live on IEEE DataPort.

• Paper: Wu, Zhang, Fu, Cheung, Chan (2020). An investigation of in-ear sensing for motor task classification. J. Neural Eng. 17 066010. 10.1088/1741-2552/abc1b6
• Source (raw) dataset: IEEE DataPort 10.21227/j7rq-2p11. License: see the DataPort record.
• Participants: 6 adults (2 M / 4 F, ages 22–28), all right-handed. Approved by the City University of Hong Kong ethics committee (ref. 2-25-201602_01).

Files

File	Channels	Shape (N, C, T)
motor-in-ear-eeg.h5	LF, LB, LOU, LOD, RF, RB, ROU, ROD (8 in-ear)	(1114, 8, 3000)
motor-scalp-eeg.h5	122 scalp EEG (Quik-Cap C190, extended 10-05)	(1114, 122, 3000)

T = 3000 is one 3-second epoch at 1000 Hz. N = 1114 is the total number of trials — one sample per trial. The two files are strictly row-aligned: sample i is the same trial in both, so the in-ear and scalp views share label, trial_id, split_group_id, and window bounds. For an ear-EEG foundation-model benchmark the 8 in-ear channels are the payload and the 122 scalp channels are the gold-standard reference.

Label distribution (identical for both modalities):

left	right
557	557

Preprocessing

Generated with Ear-EEG-FM-Benchmark/dataset/preprocess_motor.py (schema/eegfm version 0.5.0), reading the raw Curry-7 files directly via MNE read_raw_curry:

• one trial = one sample. Each trial has a single arrow cue; it is extracted as one 3-second epoch spanning [−1 s, +2 s] around arrow onset — the classifier epoch used by the paper. At the native 1000 Hz this is T = 3000 samples.
• 0.1–100 Hz band-pass + 50 Hz notch, applied to the full continuous recording before slicing (avoids per-window filter edge effects).
• no re-referencing, no resampling (kept at 1000 Hz), original channel names preserved (no near-ear renaming). Two modality groups only: 8 in-ear + 122 scalp.
• labels from the Curry event code: 1 → left (0), 2 → right (1); Curry system markers (codes ≥ 1e5) are dropped. The Trigger and REF channels are used only to read events and are never stored as data.
• bad channels are recorded, not repaired: subject-4's known-broken FP1 is kept as-is and listed in the known_bad_channels_json file attribute. Any real non-finite samples are preserved (gaps interpolated only on a temporary filter copy, then the original NaN mask restored) and reported in nan_fraction / channel_nan_fraction.

Task and labels

Each trial (10 s): a fixation cross (3 s; a warning beep 2 s after cross onset) → an arrow pointing left or right (pseudo-random) for 4 s, during which the subject grasps (clenches) the cued hand. The stored epoch is aligned to the arrow onset (= start of the grasp).

Event code	Class	label
1	left hand	0
2	right hand	1

The 1 = left, 2 = right mapping is stated explicitly in the IEEE DataPort record.

Channels

The raw recording has 132 channels = 122 scalp EEG + 8 in-ear + Trigger + REF; the processed files keep only the 122 scalp and 8 in-ear signals (Trigger/REF dropped). The 8 in-ear electrodes:

Ear label	Position
LF, LB / RF, RB	left / right ear-canal, front & back
LOU, LOD / ROU, ROD	left / right concha (outer ear), upper & lower

The scalp montage is the Neuroscan Quik-Cap C190 (extended 10-05): T9, FT9, FTT9h, T7, TP7, … C3, Cz, C4 … T8, TP8 (see ch_names in the file). All ear + scalp channels were referenced to a shared scalp REF; scalp GRD was the ground.

Per-subject / per-run trial counts

Subjects 1, 5, 6 span several chronological runs (run-01 …, from the raw motorN recordings); subjects 2, 3, 4 are single-run. Counts parsed from the source event files:

Subject	Runs	Trials (L / R)	≈ blocks (÷16)
sub-01	3	240 (120 / 120)	15
sub-02	1	160 (80 / 80)	10
sub-03	1	160 (80 / 80)	10
sub-04	1	80 (40 / 40)	5
sub-05	4	234 (117 / 117)	~14.6 (irregular)
sub-06	3	240 (120 / 120)	15
Total	13	1114 (557 / 557)	—

One block = 16 trials; perfectly class-balanced overall.

HDF5 schema (v0.5)

/data                 (N, C, 3000) float32   # µV at 1000 Hz
/durations            (N,)         int64
/nan_fraction         (N,)         float32
/channel_nan_fraction (N, C)       float32
/labels               (N,)         int64      # 0=left, 1=right
/sample_id            (N,)         int64
/subject              (N,)         string     # 'sub-01' … 'sub-06'
/session              (N,)         string     # '' (no sessions)
/task                 (N,)         string     # 'grasp'
/acquisition          (N,)         string
/run                  (N,)         string     # 'run-01' …
/recording_id         (N,)         string
/trial_id             (N,)         int64      # arrow-event index within the run
/event_id             (N,)         int64      # Curry trigger code (1=left, 2=right)
/split_group_id       (N,)         int64      # unique per trial (trial-level splitting)
/window_start_sample  (N,)         int64      # epoch bounds in the continuous recording
/window_stop_sample   (N,)         int64
/ch_names             (C,)         string

Key attributes: sfreq (1000.0), class_names (['left','right']), unit (uV), eegfm_version (0.5.0), preprocess_config_json, split_group_kind (trial), event_id_kind, window_reference, and known_bad_channels_json ({"sub-04":["FP1"]}).

No block grouping is baked in (split_group_id is unique per trial); block structure is recoverable post-hoc from window_start_sample gaps (≈11 127-sample within-block cadence, larger gaps between blocks).

Known issues / caveats

• Task framing is described inconsistently across sources. The paper says subjects "make a fist" (motor execution); the IEEE DataPort record says "imagine and grasp". The task is stored under the neutral name grasp — do not hard-assert MI vs ME.
• subject-4 FP1 is a known-broken channel (kept, not repaired — see Preprocessing).
• subject-5 has 234 trials — not a clean multiple of the 16-trial block (split 80/60/30/64 across 4 runs).
• Block/subject counts in the paper / DataPort prose are unreliable (DataPort is marked "under construction" and disagrees with both the paper and the files). The counts here are parsed directly from the source event files.

Provenance

Trial counts, channel lists, and the 1 = left / 2 = right mapping were read from the raw .dap / .rs3 / .ceo files and cross-checked against the paper and the IEEE DataPort record. Processed with dataset/preprocess_motor.py at eegfm schema 0.5.0.