Electrocardiography TRIZ Cases

A medical sensor system uses learning-based algorithms to verify proper patient application through physiological data analysis.

A tachycardia detection algorithm uses dual-vector EGM sensing to estimate heart rates and apply beat-by-beat rules for rhythm classification.

A multifunction electrode pad uses a composite metal/metal chloride coating to conduct electrical energy efficiently.

A spiral transmit receive coil contours to a subject to enhance magnetic resonance signal detection in low field systems with weak signals.

Electrophysiology catheter with isolated electrode bands determines roll angle via tissue contact signals.

Computes actigraphy signals from physiological parameter data using local signal variance and wavelet transforms.

A hardware-assisted noise detection system identifies external interference types in real-time to improve biosignal recording quality.

Multi-stage filtering removes noise from electrocardiogram signals while preserving critical diagnostic features.

Automated head up CPR system integrates chest compression and positive pressure ventilation to elevate the patient's upper body.

A control module derives and evaluates parameters to detect leading indicators in implantable medical devices.

A cardiac function characterization system collects dynamic impedance data along venous return and right ventricular vectors to derive physiological indicators.

A relaxation system processes electrocardiogram signals to compute a stress index and delivers real-time biofeedback via multimedia devices.

A processing system derives dynamic impedance values from endogenous cardiac electrical signals using an artificial neural network for noise compensation.

A hand-held vital signs monitor uses a finger-attached sensor to detect optical, electrical, and acoustic signals for blood pressure measurement.

Automated MRI systems calculate spatial positional information for heart reference sections to streamline imaging setup.

An automated algorithm classifies cardiac events using abrupt onset detection and A/V ratio analysis.

EEG electrodes measure brain activity to quantify sleep performance scores, replacing subjective reports with objective deep sleep metrics.

Grooved core wires accommodate multiple optical sensors within a 0.89 mm diameter, maintaining stiffness for TAVI support while reducing tissue trauma.

A processor-implemented method detects sleep disordering events by applying computed features from multiple physiological signals to a trained classifier.

A cardiac pacing system analyzes electrogram morphology to verify ventricular capture status.

A system evaluates candidate sensing vectors by generating signal intensity and interference indicators to rank electrode configurations.

Medical device senses heart rate turbulence via cardiac contractility to predict arrhythmias.

An internet-based system evaluates T waves within ECG waveforms to identify cardiac abnormalities using specialized algorithms.

Implantable sensors monitor Q-T interval changes to prevent ventricular tachycardia risk from prolonged intervals.

An adaptive algorithm combining empirical mode decomposition and least mean square filtering extracts ventricular fibrillation signals from electrocardiogram recordings.

Active device sets connector potential equal to projected sensor voltage, reducing impedance sensitivity and eliminating cable artifacts.

An implantable heart monitoring device analyzes atrio-ventricular conduction time variability to quantify congestive heart failure severity.

Analyzing motion patterns before disconnection differentiates intentional from accidental removal, reducing alarm fatigue in ICU monitoring systems.

Registers 2D fluoroscopy images with 3D mapping data to resolve catheter orientation challenges during electrophysiological procedures.

A concurrent impedance plethysmograph system processes ECG and waveform buffers simultaneously to increase data acquisition speed.

A retractable wire mechanism adjusts the linear distance between electrodes on a portable cardiac monitor.

A wearable device captures physiological and non-physiological measurements to identify abnormal sleep conditions.

A pacemaker analyzes endocardial electrogram signals to monitor cardiac changes.

An expression evaluator generates user-defined biometric parameters from monitored data within a medical monitoring system.

An implantable cardiac monitor links detected arrhythmias with myocardial ischemic episodes using temporal proximity analysis.

Radial electrode arrays improve signal fidelity during atrial fibrillation mapping while maintaining stable reference potentials.

Dynamic impedance data characterizes chamber-specific cardiac function to adjust pacemaker timing parameters.

Classifying arrhythmias with impedance minima prevents unnecessary shocks, preserving battery life and patient safety.

Sewing a peeled digital yarn portion onto a fabric sensor prevents cloth damage and discoloration from metal connectors.

Segmented signal paths resolve bandwidth overlap between ECG noise and pacemaker pulses, enabling precise pulse detection without cross-interference.

A control unit evaluates ECG signal differences to filter artifacts and maintain synchronization with the cardiac cycle.

A vehicle seat sensor system combines piezoelectric and capacitive sensing to measure occupant biometrics.

A robotic catheter system uses anatomical model registration to linearly actuate steering wires for precise navigation.

A reciprocating intravascular pump uses a flexible membrane valve to propel blood downstream while minimizing upstream resistance.

An arrhythmia detection device integrates an ultrasound imaging unit to scan the heart when ECG monitoring detects potential irregularities.

A controller modulates pump speed to generate pulsatile flow, resolving the contradiction between rotary pump durability and physiological complications.

A patient care recommendation system produces derived physiological signals from raw inputs to generate clinical guidance.

A control unit modulates ultrafiltration rates and electrolyte concentrations in extracorporeal blood treatment systems.

A cardiac detection system calculates fractal dimension values from electrical signals to identify arrhythmias with high precision.

Automated framework segments cardiac waveforms into amplitude percentage categories to generate sequential morphological data series.