Electroencephalography TRIZ Cases

A seizure detection system analyzes inter-region neural correlations to identify transitions from hyposynchrony to hypersynchrony.

A predictive algorithm system characterizes patient neural state to generate personalized intervention recommendations.

Fixed-order ARMA model analyzes EEG signals to determine complex poles, resolving measurement precision limits in clinical monitoring.

A hardware-efficient non-linear SVM engine classifies multichannel EEG data to resolve the trade-off between detection latency and accuracy.

An integrated circuit digitizes neural signals and applies a digital line frequency filter algorithm to remove noise without complex hardware.

Replacing survey errors with EEG, GSR, and EKG measurements resolves the contradiction between collection ease and measurement precision.

Segmenting the ground across the PCB and accessory body resolves the conflict between quarter-wavelength length requirements and device miniaturization.

Automated electrode array switching based on detected device orientation eliminates manual alignment errors and improves measurement reliability.

Head-mounted outward-facing cameras capture user perspective data to resolve latency and restricted coverage limits in traditional external tracking systems.

Integrated conductive threads and EMI shielding in a wearable garment resolve skin irritation and lead tangling while maintaining signal quality.

EEG electrodes detect brain waves to switch hearing instruments between active and relaxation modes, eliminating manual adjustments.

Control circuitry delivers electrical therapy to synchronize brain areas in response to external sensory stimuli, avoiding independent activation.

Flexible textile electrodes enable self-operable bio-signal monitoring without medical assistance.

A biomarker fusion system processes ERP test results alongside other biomarker data to classify patients based on defined class and feature sets.

A closed-loop deep brain stimulation system detects hyperkinetic states via gamma oscillation monitoring.

Evaluating neuroplasticity via transcranial magnetic stimulation resolves the contradiction between diagnostic accuracy and early detection timing.

An active electrode coupler controls sensor current to match patient voltage, establishing a low impedance interface at the skin contact point.

A learning system detects user motivation via electroencephalogram event-related potentials to output break prompts when engagement drops.

A driving assistance device estimates driver concentration using biometric data to adjust vehicle support.

Piezoionic polymer electrodes in a sensor array generate electrical signals from mechanical deformation, eliminating the need for external excitation energy.

A cognitive-kinesthetic drawing method uses audio-haptic feedback to train spatial cognition and motor coordination through non-visual interaction.

High frequency oscillation analysis localizes seizure foci without invasive surgery, reducing hospitalization time and morbidity risks.

A brain wave measuring instrument isolates neural signals using frequency band segmentation and intermediary processing to extract energy distribution data.

Combining continuous pure tones with defined phases compensates cochlear delays to reduce stimulus artifacts.

Multi-index assessment system segments autonomic and neurologic data streams for precise comorbidity evaluation.

A system detects lateral brainstem response state development by repeatedly sending sound stimuli to evoke neuronal patterns.

Automated nonlinear time series analysis quantifies sleep architecture using EEG data and the largest Lyapunov exponent for objective pattern detection.

A wearable device infers sleep status to activate heart rate sensors only during rest periods.

A neurostimulator records neural responses to electrical stimuli for diagnostic monitoring.

A wearable device couples a curved body to a polygonal strap opening via interlocking features for secure attachment.

A remote processing system collects and analyzes electrophysiological data to generate diagnostic reports.

A tinnitus testing device measures electrical brain responses to sound patterns for objective auditory characteristic identification.

Ear canal sensors detect brain waves with high precision, resolving the trade-off between measurement accuracy and user comfort during audio playback.

Analyzes brain wave power spectrum fluctuations using PC techniques to extract detailed diagnostic parameters from electroencephalographic signals.

A biomedical sensor system filters continuous electrical signals to transmit only statistical data and anomaly detections via a wireless channel.

Repetitive transcranial magnetic stimulation synchronizes brain activity with biological metrics through frequency coupling.

Intermediary barrier materials and composite pads prevent needlestick injuries during patient positioning.

A computing device analyzes bio-signal data to guide users through meditation routines.

A data-oriented feedback controller adjusts wearable device parameters using biometric signals to enhance user comfort.

A system blends neuro-response data with user characteristics to determine priming levels for intracluster content selection.

Statistical baselines enable real-time detection of brain signal variations without retrospective data collection.

Annoyance judgment system measures electroencephalogram peak latency to assess user comfort during speech sound listening.

Segmented notches and asymmetric geometry guide correct placement, resolving the trade-off between ease of operation and signal quality.

High-impedance preamplifiers capture scalp potential through a hair and air interface, eliminating abrasive preparation while maintaining measurement precision.

Analyzing frontal EEG deviation signal frequency spectra detects hypoactive delirium with high sensitivity, overcoming low CAM-ICU assessment accuracy.

Neurological event detectors adjust detection thresholds using closed-loop feedback to match target rates.

Computes a data condition number over time windows to detect anomalies in multi-channel signals.

An EEG control system configures user preferences and hierarchies to enable real-time operation of lighting systems.

Monitoring brain impedance identifies pre-seizure physiological changes earlier than EEG, reducing therapy delivery delay while maintaining detection accuracy.

A targeted brain infusion system uses diffusion tensor imaging to plan precise therapeutic agent delivery paths.