Electroencephalography TRIZ Cases

An abnormality prediction device detects biological and motion information to identify premonitory symptoms before actual health issues arise.

A threaded cranial implant captures neural signals via an epidural electrode and transmits data wirelessly.

A portable device delivers non-contact thermal stimulation to evoke neurological potentials for rapid assessment.

A neuroadaptive display controller adjusts stimulus load based on real-time brain activity metrics.

Referencing intracardiac signals to a common mode average suppresses mains interference while preserving signal morphology for accurate arrhythmia diagnosis.

Simultaneous electrical stimulation of brain tissue regions identifies functional areas through optical imaging comparison.

A medical parameter interpretation system analyzes capnograph data to diagnose respiratory conditions and provide immediate treatment guidance.

A textured cortical electrode surface increases malleability for brain conformance while a hinged inline connector joins the device to EEG machines.

A non-invasive neurostimulation device generates varying stimulus sequences to desynchronize pathological neuronal activity.

Segmenting microneedles into multiple electrically active sites increases recording resolution without increasing tissue insult from needle density.

Integrated brain and cardiac signal monitoring system calculates heart-rate variability to detect neurological events.

A flexible printed circuit board interposes between a thin film lead and an Advanced Lead Connector to establish reliable electrical connections.

Multi-scale decomposition and self-supervised learning separate unknown signal forms from interference, enabling accurate neurological disorder diagnosis.

Segmented microelectrodes penetrate the pia mater to stabilize recordings against cerebrovascular pulsations while delivering agents.

A multimodal probe array integrates electrical and chemical sensing capabilities within a single neural interface structure.

An implantable neurostimulator detects epileptiform activity patterns to predict impending seizures.

Physical assessment sensors collect cognitive workload data to generate composite profiles for neurotechnology device adjustment.

A drug sensitivity index predicts individual patient responses to anesthetics by correlating demographic data with effect site concentrations.

Frequency-multiplexed synthetic sound-speech stimuli simultaneously activate multiple auditory levels.

A wearable headset records and transmits EEG signals from behind the ear to an external device.

Periodic feedback stimulation decouples pathological neural activity, reducing energy consumption and eliminating depth electrode implantation risks.

A brainwave monitoring system determines user attention levels to identify potential cheating events during assessments.

Disc-shaped electrode with concave surface adapts to skull curvature for stable electrical contact.

Segmenting the probe and transmitter reduces surgical invasiveness while maintaining high resolution and sensitivity for deep brain region monitoring.

A rigid-flex circuit substrate distributes physical stress across electrode modules to maintain structural and electrical integrity.

Stochastic Gabor Function electrical impedance spectroscopy applies dual energy pulses to measure brain tissue properties.

Apertures in the skull channel electrical fields to target brain areas, resolving diffusion issues inherent in non-invasive neuromodulation.

A portable biosignal detector system collects bioelectrical datasets to generate personalized behavior change suggestions.

Spiral wrapping a thin film distal extension around a carrier core prevents delamination and maintains bond integrity without adhesive bonding.

Rear-mounted electrode control circuits resolve spacing conflicts to enable dense bioelectrode arrays in living bodies.

A seizure detection algorithm extracts spectral power ratios from EEG signals to classify neurological events with high sensitivity.

A functional skin patch integrates a thermo harvester with a stacked antenna unit for efficient energy conversion.

Segmented EEG signal processing filters suppressed waveforms to isolate valid measurement data for real-time analysis.

Folded conductive outer layer protects gel from drying while maintaining electrical conductivity for defibrillation.

Computerized scoring replaces manual visual inspection with normalized feature extraction, reducing inter-scorer variability and time consumption.

A system extracts ballistocardiogram timing directly from EEG recordings using a Left-Mean-Right-Mean signal derived from facial artery-proximal electrodes.

Inward-facing thermal cameras capture facial temperature changes to identify user stress levels and gaze patterns.

A phase-locked loop synchronizes acoustic pulses with brain rhythms to generate K-complex waves during non-REM sleep.

Wearable glasses with EEG sensors detect eating states via brain waves, replacing manual logging that suffers from low compliance and human error.

State-dependent magnetic blocking synchronizes stimuli with activity states to modulate neural efficacy while avoiding numbness and autonomic interference.

Iterative electrical stimulation resolves EEG inverse problem ambiguity by verifying source locations against measured neural responses.

Flexible branches position dry electrodes on the scalp, eliminating hair-induced impedance and motion artifacts.

Switchable electrodes enable simultaneous stimulation and measurement, eliminating separate device setups and reducing system complexity.

A movement pattern measuring apparatus normalizes EEG and EMG signals using a pattern normalizing unit to estimate user motion via artificial neural networks.

Log-log spectrogram slope analysis of EEG and EMG signals resolves CNS interference to accurately determine patient awareness levels.

Acquisition unit captures biological data while guide unit directs users to specific physiological states for reference calibration.

A systolic random-logic-macro array combines neural signal data with a transformation matrix to generate reduced datasets.

Segmenting electrode arrays into hierarchical groups reduces noise accumulation and ADC bit resolution requirements, enabling higher sensor density.

A noninvasive brain-computer interface decodes neural activity from observed movements using time-domain EEG analysis.

A composite dissimilarity metric analyzes phase space data to generate timely visual or audible signals.