Electrocardiography TRIZ Cases

A respiration rate estimation system segments physiological signals through cardiac, motion, and noise removal stages to generate accurate periodic data.

A bio-information analysis device calculates matching rates using biometric waveform shapes and magnitudes.

A detection system generates a predictor trend from physiological signals and transforms it into transformed indices using a codebook.

A device modulates kinesthetic stimulation energy based on detected sleep stages to interrupt apneas.

System monitors physiological signals to dynamically adjust audio volume, preventing energy waste and sleep disturbances.

A dynamically configurable adaptive digital filter tracks power line frequency variations to remove interference from electrocardiogram signals.

Recency-weighted alarm analytics calculate dynamic acuity scores to resolve alarm fatigue and prioritize critical patient conditions.

A signal processing system decomposes ECG signals into subcomponents to isolate noise and identify T-wave offset points for accurate QT interval measurement.

An implantable pacemaker uses ventricular acceleration signals to identify filling phases and adjust pacing intervals.

Dual-vector EGM sensing classifies tachycardia rhythms to prevent inappropriate high-voltage shocks and conserve battery charge.

A control device calculates scanning conditions based on time resolution rates to optimize image quality.

Replacing optical sensors with intra-aural vibration detection eliminates signal weakness from auricle shape variability and movement.

Interdigitated conductive regions in a non-conductive textile detect ECG and respiratory signals while eliminating magnetic field interference from metal lines.

A personal cloud case cover integrates modular components to enable portable computing services.

Continuous non-invasive estimates guide initial cuff inflation and step sizes, reducing patient discomfort while maintaining measurement accuracy.

Segmenting the reusable processing unit from disposable electrodes reduces bulk and infection risk, enabling cost-effective large-scale arrhythmia monitoring.

A cardiac monitor extracts sub-bandwidth signal components from electrocardiogram data to calculate energy ratios for abnormal heart activity identification.

Dual wrist smart bands with dry electrodes and digital switching resolve the trade-off between continuous monitoring reliability and wearer comfort.

A cryotherapy balloon catheter integrates mapping electrodes on its expandable surface to characterize tissue electrical properties.

A monopolar physiological signal detection device uses a differential amplifier and driven-body circuit to process electrical heartbeat signals.

Multi-stage amplification and band-pass filtering process for ECG signal acquisition resolves environmental interference in mobile detection systems.

A selectively deployable restrictor on an implantable catheter shaft controls lumen size to reduce pressure at the thoracic duct outflow.

A central controller synchronizes clocks and aligns coordinate systems across independent medical devices to merge imaging and mapping data into a single display.

Piezoelectric sensor detects inaudible S3 vibrations while signal processing transforms frequencies into perceivable outputs for heart failure assessment.

Integrating sensor lumens into a perfusion cannula records central vital parameters, resolving peripheral measurement inaccuracies during shock.

A hand-held device uses hybrid sensors with electrodes and light detectors to process user health signals.

A remote device uses a PPG circuit to emit light at multiple wavelengths and process spectral responses from skin.

A pacemaker signal detecting system calculates width, slew rate, and amplitude features to confirm signal authenticity.

A staged detection system processes physiological signals to identify acute myocardial infarction with high specificity.

A malleable shaft surgical clamp adapts to patient anatomy to reach inaccessible tissue areas for effective ablation.

Hierarchical algorithm calculates quantitative ECG and HRV parameters for cardiovascular diagnostics.

Multiple sensing vectors obtain intracardiac electrograms from various heart regions to determine evoked response metrics.

Adaptive ECG trigger signal compensates for processing delays using dynamic timing thresholds.

Biometric monitoring device combines heartbeat waveform and motion detecting sensors with adaptive filtering to remove motion artifacts from signal data.

A virtual reference electrode establishes a local origin near the medical device to reduce body resistance effects.

A respiratory ionization device generates negatively charged air to enhance oxygen affinity in breathable gas.

A cardiac rhythm management system dynamically adjusts arrhythmia detection durations using patient-specific hemodynamic performance data.

Ventricular depolarization stability analysis discriminates atrial tachyarrhythmias in implantable devices lacking dedicated atrial sensing circuits.

A control system incrementally increases sensory stimulation intensity during slow wave sleep episodes to boost physiological activity levels.

Synchronizing electrocardiograph and ballistocardiograph signals resolves insufficient diagnostic sensitivity in static records by aligning cyclical patterns.

An ST Map superimposes ischemia criteria on ECG data to generate a clear visual representation of diagnostic signals.

A morphology-based method estimates motion-induced noise in implantable photoplethysmography sensor signals by comparing signal portions to templates.

Adaptive temporal windowing adjusts the search range based on signal morphology to improve QRS detection accuracy without increasing computational complexity.

A probabilistic digital signal processor filters biomedical sensor data using dynamic state-space models and Bayesian inference.

An implantable optical perfusion sensor monitors blood oxygen saturation to detect physiological changes.

Selective activation of secondary cardiac rate measurements using spectral content corrects T-wave overdetection errors in rhythm management devices.

Assesses biphasic or monophasic cardiac signal characteristics to select optimal sensing vectors for implantable devices.

Automated vector flow mapping identifies cardiac rotor cores from spatially-distributed recordings to guide ablation therapy.