Cross-cut: `algo-bci-motor-imagery`

Axis: algorithms

3 corpus entries disclose this tag.

Earliest disclosure: 2002-06

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

Wolpaw et al. (2002) — ‘Brain-computer interfaces for communication and control’ (2002-06)

id: wolpaw-2002-bci-review
corpus: academic
form factor: other
creator: Jonathan R. Wolpaw et al.
disclosure: Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. ‘Brain-computer interfaces for communication and control.’ Clinical Neurophysiology 2002;113(6):767-791.
ip status: public-domain
sensors: sensor-eeg
algorithms: algo-bci-p300, algo-bci-ssvep, algo-bci-motor-imagery, algo-erp-classification
prior art notes: Canonical review establishing, as of 2002, the major non-invasive EEG-based BCI paradigms (sensorimotor rhythms / motor imagery, P300 evoked potentials, SSVEP, slow cortical potentials) and the signal-processing pipeline for translating EEG into control output. Prior art for wearable-BCI claims reciting any of these paradigms with scalp EEG: the paradigms and methods were published and enabled by 2002. Anchor for the BCI algorithm cross-cuts.

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.