Electrocardiography TRIZ Cases

Wavelet transform separates baseline drift from ECG signals, enabling accurate feature extraction while preserving clinically relevant waveform information.

Implantable cardiac devices filter detected intervals to estimate heart rate accurately.

Iterative threshold adjustment converges mean and median cycle lengths, reducing undersensing errors in atrial fibrillation detection.

A stimulation device applies low-frequency sound to maintain airway patency during apnea events.

Dual electric field sensors measure differences to detect patient coupling, preventing fluid waste from unnoticed tubing disconnections.

Stimulating the His bundle via a leadless device restores atrioventricular synchrony and reduces right ventricular pacing risks.

A combined ultrasound and electrocardiograph system generates mechanical motion markers to represent heart activity.

SAAH ECG device detects cardiac subwaveforms via band pass filters, revealing heart muscle tissue function lost in conventional single-band analysis.

A sleep optimization system generates sensory stimuli to guide subjects toward desired states.

Integrated sensor circuitry measures physiological parameters during exertion phases to resolve accuracy limitations in current fitness testing technologies.

A flexible insertion tube containing rigid tubular modules with internal grooves and an expander tube with external grooves.

An implantable heart sound sensor analyzes acoustic signals to determine blood glucose levels, eliminating invasive finger prick testing.

Amplitude normalization and dynamic coefficient adjustment enable accurate pulse rate extraction despite motion artifacts.

Processor detects hyperkalemia by monitoring pacing threshold changes during therapy delivery, enabling early arrhythmia intervention without complex hardware.

Embedded bellows generate rhythmic movements mimicking caregiver contact while maintaining incubator sterility and thermal stability.

External electrodes monitor cardiac electrical activity to adjust left ventricular assist device output parameters, reducing right ventricular failure risk.

Segmenting blood pressure signals into stress and fluid responsiveness categories resolves complexity trade-offs in ICU monitoring.

A breast shield embeds a photoplethysmographic sensor to detect milk flow changes in breast tissue.

A multi-sensor module consolidates sensor leads into a single cable, eliminating respiratory effort belts to improve patient comfort during sleep studies.

A real-time signal segmentation framework aligns fiducial points across biosignal segments using dynamic time warping.

A cardiac signal processing system extracts feature points and computes parameter values using signal-to-noise ratio validation.

A method reconstructs surface electrocardiograms using endocardial vectograms and angular rescaling for remote cardiac monitoring.

A cardiac signal analyzer synchronizes electrophysiological data across P and R waves to extract amplitude and duration changes from successive heart cycles.

Deriving a noise model from signal segments without physiological activity to identify genuine cardiac potentials.

Electronic device distinguishes on-therapy from off-therapy physiological data to quantify sleep measures and improve user adherence.

Segmented cluster electrodes adapt to individual brain anatomy variations, eliminating extensive experimentation to determine optimal measurement locations.

Measuring myocardial mechanical dispersion via strain echocardiography to assess regional heterogeneity in ventricular contraction.

Integrating sensors into bed linens captures biometric data to verify patient identity, eliminating errors from removable wearable devices.

A drug delivery system adapts insulin dosage and timing based on real-time physiological stress detection.

A processor-controlled electromechanical mechanism drives an air pump to push fluid through a microneedle array into skin.

Integrates electrocardiography signals with acoustic heart sounds to identify impedance cardiography fiducial points.

Electronic fetal monitoring assessment tools overlay graphic indicators on heart rate tracings to visualize baseline, variability, and acceleration patterns.

A hand-held device merges ECG electrodes with Doppler radar sensors to capture simultaneous electrical and mechanical cardiac signals.

Hilbert transform creates orthogonal partial state space to detect arrhythmias with fewer leads, reducing false positives and storage needs.

Analyzes cardiac electrogram signal morphology to classify heart rhythms without relying on depolarization intervals.

Three-dimensional electrogram surfaces generate velocity vector maps to detect cardiac rhythm disorder sources.

Autocorrelation analysis of RR intervals detects pathological oscillations, eliminating complex polysomnography requirements.

Decomposing inter-beat intervals into subcomponents and computing an envelope reduces computational load while distinguishing AF from other arrhythmias.

An implantable medical device analyzes electrogram morphology to classify cardiac rhythms as treatable or non-treatable.

Segmenting sensor activation by heart rate thresholds reduces battery drain while maintaining detection accuracy for ASD episodes.

A flush snap and electrode assembly integrates into heart rate monitor belts using a conductive wire spring to resolve bulky protrusion issues.

A pad tray holds electrode pads in a recessed region to simplify attachment and detachment from electrodes.

Electrograms measure voltage reduction and signal fractionation to locate the fossa ovalis, reducing procedure time and cost compared to ultrasound guidance.

A semi-automated device manages medication reservoirs and pumps to deliver precise treatments during cardiac arrest events.

A wearable device detects electrocardiographic lead inversion by analyzing P-wave amplitude and R-wave magnitude relative to QRS components.

Replacing complex imaging equipment, this optical sensor enables frequent home monitoring of abdominal aortic aneurysms to prevent rupture.

An IoT hub monitors sleep patterns to generate control signals that adjust light therapy output.

A scent diffuser linked to physiological sensors triggers a conditioned reflex for sleep initiation.

A cardiac impulse sensor detects human presence through electric field variations caused by muscle movement during respiration and heartbeat.

An implantable cardiac device detects T-wave alternans by measuring metrics following premature ventricular contractions.