Electrocardiography TRIZ Cases

User equipment detects stable electrocardiogram and photoplethysmogram signals to enable blood pressure measurement.

Acoustic earphones detect respiration rate and adjust audio signals to match the user's breathing pattern.

Absolute calibrated tissue oxygen saturation measurements distinguish hemodynamic stability, reducing unnecessary shock therapies and conserving battery life.

A biosensing electronic device adjusts lighting output based on detected physiological parameters.

A fetal monitoring display system routes alarm-triggering events to user devices based on their physical location and designated permissions.

Computing apparatus analyzes cardiac electrograms to identify valid channels and eliminate artifacts.

Dynamic adherency adjustment resolves the trade-off between measurement precision and user comfort by moving sensors closer only when activated.

Analyzing ventricular cycles to detect atrial fibrillation without an atrial electrode.

An N-dimensional signal vector separates local activation from far-field activity, resolving measurement precision issues in complex rhythm disorders.

A multichannel photoplethysmographic sensor extracts features from optical signals to determine pulse arrival time values.

A detachable clamp uses magnetic fixing units to attach electrode sensing surfaces directly to fabric for wireless signal transmission.

A sensing catheter delivers controlled fluid infusion to open collapsed microvessels and restore coronary flow.

A catheter combines mapping electrodes with treatment elements to record local monophasic action potentials.

A self-contained infusion unit resembling an arm cast integrates the pump and reservoir to eliminate external tubing.

A Doppler apparatus computes a pulsation index from harmonic peaks to detect cardiac blood flow.

Multisite heart pacing activates natural heterogeneities in cardiac tissue using adjustable electric field pulses to terminate arrhythmias.

An ultrasonograph calculates and sets Doppler sweep rates based on measured heart rate for optimized image display.

Ultrasound imaging and magnetic field sensing track catheter tip location to eliminate confirmatory X-rays during needle insertion.

A normalized electrocardiogram generation method extracts and connects single-cycle signals to enhance personal identification accuracy.

An electrocardiograph system groups twelve leads into four anatomical subsets for sequential display.

Segmenting ballistocardiogram signals isolates cardiac energy from respiratory noise, enabling accurate arrhythmia detection in non-wearable monitoring systems.

A piezoelectric blood pressure cuff detects atrial fibrillation through RR interval analysis.

Closed-loop bilateral stimulation system adapts pulse patterns via real-time physiological feedback to treat insomnia without pharmacological side effects.

A mapping and ablation catheter uses a movable sheath to expose variable electrode lengths for precise signal sampling.

Aligning intracardiac electrograms determines optimal shock strength via upper limit of vulnerability, eliminating risky fibrillation testing.

A sound-induced sleep system selects acoustic stimuli based on real-time brainwave analysis to induce rest.

Analyzing apparent width of detected events in implantable cardiac devices to identify overdetection errors that cause incorrect heart rate calculation.

A computing device aligns direct electrocardiogram signals with indirect pulse oximeter data using cross-correlation to calculate heart rate variability.

A disposable electrode module integrates a flexible substrate with a communication-computation module to process physiological signals.

An electrolyte bridge transmits cardiac potential changes to verify catheter tip position, eliminating post-procedural imaging delays.

Extracting power and computing modules to a mobile phone reduces injection device weight while enabling precise dose timing.

An electrode clamp uses pivoting parts with an initial offset to secure snap and film electrodes for medical contact.

Implantable cardiac device tracks beat-by-beat intracardiac electrogram alterations to detect T-wave alternans patterns.

Expandable epicardial support members stabilize mapping electrodes to treat arrhythmias across all heart layers.

A multielectrode carrier arranges multiple recording pairs to capture bioelectrical potentials simultaneously.

Spectral dispersion metrics extract energy density profiles from electrocardiogram signals to classify heart rhythm states.

Integrating electrodes into the ultrasonic probe eliminates separate wiring steps, reducing setup time and system complexity during medical diagnostics.

Processes EKG axis vectors into component sequences to identify electrode reversal and prevent misdiagnosis.

Merges ECG electrodes and a pressure sensor to select the highest quality respiration signal, eliminating thoracic impedance artifacts and cardiac interference.

Automated scanning detects background grids to scale axes and extract waveforms, reducing manual digitization time.

A physiological signal patch uses a processing device to dynamically adjust electrode positions for optimal ECG capture.

A virtual reality headset paired with physiological sensors creates immersive 3D environments for clinical testing.

Premature atrial pacing blocks retrograde conduction to distinguish supraventricular from ventricular tachycardia, reducing false detections.

Implantable devices compare candidate atrial event characteristics against stored templates to detect hidden P-waves and eliminate mode switch oscillations.

A cardiac sensing apparatus aligns a known template with an unknown cycle signal using fourth order difference metrics to classify beats.

A wake-up system modulates light intensity and color to simulate sunrise based on user preferences.

Parallel ECG analysis suppresses CPR artifact noise, reducing hands-off time from ten seconds to five while maintaining decision accuracy.

Segmenting the motor from the collapsible housing reduces crossing profile and thrombosis risk while enabling real-time physiological parameter display.

Computes a cardiac risk metric by measuring the time difference between mechanical systole detected via acoustic vibrations and electrical systole from ECG signals.