{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a33bf","dataset_id":"ds005178","associated_paper_doi":null,"authors":["Yousef Rezaei Tabar","Kaare Mikkelsen","Laura Birch","Nelly Shenton","Simon L Kappel","Astrid R Bertelsen","Reza Nikbakht","Hans O Toft","Chris H Henriksen","Martin C Hemmsen","Mike L Rank","Marit Otto","Preben Kidmose"],"bids_version":"1.9.0","contact_info":["kaare mikkelsen"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005178.v1.0.0","datatypes":["eeg"],"demographics":{"subjects_count":10,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005178","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"9f081db7da274a7e63a0364d477f49c12b3075e880bf06490d1692de038b9a44","license":"CC0","n_contributing_labs":null,"name":"Ear-EEG Sleep Monitoring 2023 (EESM23)","readme":"Ear-EEG Sleep Monitoring 2023 (EESM23) data set\n**Overview**\nThis dataset was collected as part of a research project on ear-EEG sleep monitoring which took place in 2020-2022.\nThe data set contains nightly EEG recordings from 10 healthy participants ('subjects'). The first two recordings consist of polysomnogrpahy (PSG) measurements and ear-EEG measurements. The remaining ten recordings consist of only ear-EEG measurements, though a few subjects were asked to repeat a recording. Only the accepted recordings can be found in the BIDS formatted data set.\nEach file consists of a video sequence followed by a sleep sequence. After the video sequence, the subject sent triggers to distinguish between the two sequences. Due to potential variability in triggering the device, the sequences remain in one file though it should be possible to manually sort the file into distinct video and sleep sequences.\nThere are no events.tsv files for Ear-EEG.\n**Task description**\nThe patient performed tasks prior to going to bed. These recordings are labeled with 'video' as task. After his, the real recording started, which took place during the night and began when the subject went to bed. These recordings are labeled as having task 'sleep'.\nFor the first two recordings, the recording equipment was mounted in the afternoon. For the remaining recordings, the subject mounted the ear-EEG equipment by themselves immediately prior to going to bed. All recordings took place at the subject's home.\nAs can be seen in the diaries accompanying the recordings, the subjects wrote down recording start, electrode test start, when they went to bed, lights-out and recording end, and marked these in the data files using the trigger button on the equipment.\n**Format**\nThe dataset is formatted according to the Brain Imaging Data Structure. See the 'dataset_description.json' file for the specific BIDS version used. The EEG data format chosen is the '.set' format of EEGLAB.\nFor more information, see the following link:\nhttps://bids-specification.readthedocs.io/en/stable/01-introduction.html\n**Contact**\nFor questions regarding this data set, contact:\nPreben Kidmose, pki@ece.au.dk, https://orcid.org/0000-0001-8628-8057\nKaare Mikkelsen, Mikkelsen.kaare@ece.au.dk, https://orcid.org/0000-0002-7360-8629","recording_modality":["eeg"],"senior_author":"Preben Kidmose","sessions":["001","002","003","004","005","006","007","008","009","010","011","012"],"size_bytes":27636341897,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["sleep"],"timestamps":{"digested_at":"2026-04-22T12:27:25.146569+00:00","dataset_created_at":"2024-05-24T08:18:02.675Z","dataset_modified_at":"2024-05-31T23:06:26.000Z"},"total_files":140,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005178","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","task-sleep_acq-earEEGRecordingFailures_events.json","task-sleep_acq-scoring_events.json"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"f758dcb9541165ca","model":"openai/gpt-5.2","tagged_at":"2026-01-20T17:41:59.083596+00:00"},"tags":{"pathology":["Healthy"],"modality":["Sleep"],"type":["Sleep"],"confidence":{"pathology":0.8,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"Most similar few-shot example is the \"Surrey cEEGrid sleep data set\" (Healthy / Sleep / Sleep): it is also an ear-adjacent wearable EEG sleep monitoring dataset with \"nightly EEG recordings\" and explicitly states \"performed no tasks\" beyond sleep. This guides the convention that such at-home night recordings are labeled with Modality=Sleep and Type=Sleep (rather than Resting State / Resting-state).","metadata_analysis":"Key facts from README: (1) Population: \"nightly EEG recordings from 10 healthy participants ('subjects')\". (2) Sleep context/modality: \"ear-EEG sleep monitoring\" and \"real recording started, which took place during the night\". (3) Task labeling: \"These recordings are labeled as having task 'sleep'.\" Also notes a pre-bed \"video\" task: \"patient performed tasks prior to going to bed... labeled with 'video' as task\", but the primary stated purpose is sleep monitoring across the night.","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata says \"10 healthy participants\"; few-shot pattern (Surrey cEEGrid sleep dataset) suggests Healthy for wearable sleep monitoring in healthy volunteers; ALIGN.\nModality: Metadata says \"sleep monitoring\" and \"task 'sleep'\" during night; few-shot pattern suggests Sleep for nightly PSG/ear-EEG recordings; ALIGN.\nType: Metadata emphasizes sleep monitoring (night recordings, diaries for lights-out/sleep timing) rather than cognition; few-shot pattern suggests Type=Sleep for sleep datasets; ALIGN.","decision_summary":"Pathology top-2: (A) Healthy — supported by \"10 healthy participants\". (B) Unknown — would apply if no recruitment info, but recruitment is explicit. Final: Healthy (clear explicit fact).\nModality top-2: (A) Sleep — supported by \"ear-EEG sleep monitoring\", \"took place during the night\", and \"task 'sleep'\". (B) Resting State — possible because sleep recordings can be confused with resting, but metadata explicitly frames sleep/night. Final: Sleep.\nType top-2: (A) Sleep — supported by repeated sleep-monitoring framing and task label \"sleep\". (B) Resting-state — weaker alternative if it were just eyes-closed rest, but it is overnight sleep. Final: Sleep.\nConfidence justification: multiple explicit quotes support each chosen label; strong few-shot analog to the Surrey cEEGrid sleep dataset."}},"computed_title":"Ear-EEG Sleep Monitoring 2023 (EESM23)","nchans_counts":[{"val":4,"count":120},{"val":13,"count":20}],"sfreq_counts":[{"val":250.0,"count":140}],"stats_computed_at":"2026-04-22T23:16:00.309070+00:00","total_duration_s":3645062.832,"canonical_name":null,"name_confidence":0.98,"name_meta":{"suggested_at":"2026-04-14T10:18:35.343Z","model":"openai/gpt-5.2 + openai/gpt-5.4-mini + deterministic_fallback"},"name_source":"canonical","author_year":"Tabar2024"}}