Cross-cut: `sensor-saline-eeg-electrode`

Axis: sensors

3 corpus entries disclose this tag.

Earliest disclosure: 2009-08

Listed in chronological order. Each entry’s prior_art_notes and disclosure_citation constitute the citeable prior art material.

CHB-MIT Scalp EEG Database (Shoeb, 2009) — benchmark seizure-detection dataset (2009-08)

id: chb-mit-scalp-eeg-database-2009
corpus: academic
form factor: other
creator: Ali H. Shoeb (MIT / Boston Children’s Hospital)
disclosure: Shoeb AH. ‘Application of Machine Learning to Epileptic Seizure Onset Detection and Treatment.’ PhD thesis, MIT, 2009 (the CHB-MIT Scalp EEG Database, distributed via PhysioNet, physionet.org/content/chbmit).
ip status: public-domain
sensors: sensor-eeg, sensor-saline-eeg-electrode
algorithms: algo-seizure-detection
prior art notes: Publishes a labelled scalp-EEG corpus and a machine-learning method for patient-specific seizure-onset detection, establishing the public benchmark and the patient-calibrated detection paradigm used by subsequent wearable seizure detectors. Relevant to seizure-detection-wearable claims reciting ‘a classifier trained on EEG to detect seizure onset’, particularly ‘patient-specific’ or ‘per-subject calibrated’ variants — the paradigm and a reference implementation were public by 2009. Anchor for the EEG × seizure-detection cross-cut; [[zanetti-aminifar-atienza-eglass-2025]] reports against it.

id: emotiv-epoc-2009
corpus: private
form factor: headband
creator: Emotiv Systems
disclosure: Emotiv Systems. ‘EPOC’ EEG headset, released December 2009 — a 14-channel (plus 2 reference) wireless headset with saline-felt electrodes covering frontal/temporal/parietal/occipital sites, with SDKs for mental-command, facial-expression and ‘affective’ detections.
ip status: patented
sensors: sensor-saline-eeg-electrode, sensor-eeg
algorithms: algo-cognitive-workload, algo-emotion-recognition, algo-bci-motor-imagery
prior art notes: Discloses a wireless multi-channel (14+2) consumer EEG headset with saline-wetted contact electrodes at standard scalp sites and on-device/SDK classifiers for mental commands, facial expressions, and affective states. Anticipates multi-channel consumer-EEG-headset claims combining ‘a wireless head-worn array of ≥8 contact electrodes’, ‘wet/saline electrode coupling’, and ‘classification of cognitive/affective state or intent’ from 2009. Product-side anchor for the headband/cap × EEG cross-cut.

id: openbci-cyton-2014
corpus: open
form factor: cap
creator: Joel Murphy / Conor Russomanno (OpenBCI)
disclosure: OpenBCI (Joel Murphy, Conor Russomanno). ‘OpenBCI: An Open Source Brain-Computer Interface For Makers.’ Kickstarter campaign launched 22 January 2014; hardware designs and firmware released open source at github.com/OpenBCI (Cyton board, Ganglion board, Ultracortex Mark IV 3D-printed headset).
ip status: open-permissive
sensors: sensor-saline-eeg-electrode, sensor-dry-eeg-electrode, sensor-emg, sensor-ecg
algorithms: algo-bci-p300, algo-bci-ssvep, algo-bci-motor-imagery
prior art notes: An openly-published, openly-licensed wearable biosignal acquisition system: a multi-channel ADS1299-based board, electrodes, and a 3D-printed head-worn frame for EEG/EMG/ECG, with reference firmware and BCI demonstrations. As open-hardware prior art it is unencumbered: any claim reciting a multi-channel head-worn biopotential acquisition device with the features published here (since 2014) reads on OpenBCI. Anchors the open bucket for biosignal wearables; relevant to headband/cap EEG and to EMG/ECG wearable claims.