Sensors TRIZ Cases

Harness design resolves complexity trade-offs by enabling independent left and right lung hydration assessment alongside 12 lead ECG analysis.

A dual-echo MRI acquisition method optimizes slab boundary connectivity for simultaneous arteriogram and venogram generation.

A flexible support uses pincer extensions to clamp the ankle and position electrodes for accurate bio-impedance readings.

Flexible bioelectric sensors conform to patient anatomy via adjustable arms and alignment marks, resolving placement accuracy issues caused by rigid substrates.

A wearable device directs light output toward the outer ear to stimulate vagus nerve branches using LEDs.

A portable head coil apparatus uses a movable extension to position coil arrays adjacent the patient's head for magnetic resonance imaging.

A third-order derivative photoplethysmography signal imputes missing feature points in second-order derivative signals.

An adhesive layer stabilizes the probe against motion artifacts to improve measurement accuracy.

A polypropylene bracelet integrates a sodium acetate heating pack to warm the inner arm and dilate veins for easier blood draws.

A segmented electrode merges measurement and auxiliary contacts into one unit to simplify skin attachment.

A magnetic resonance imaging shim unit divides the examination area into sub-areas to apply specific parameter sets for dynamic field adjustment.

A medical device performs morphology analysis on cardiac signal segments to identify tachyarrhythmia patterns.

Composite fabric reinforcement allows thinner elastomeric liners, reducing heat buildup and skin breakdown risks.

Flexible capacitive pressure sensors replace subjective assessments by providing objective spasticity metrics.

Correlating optical and impedance measurements eliminates noise interference, enabling accurate non-invasive blood constituent analysis.

A scan condition determining device calculates matrix numbers and physical parameters for magnetic resonance imaging systems.

A transformer neural network converts multi-channel time-synchronized signals into image patches for classification.

Segmented electrode pieces conform to curved body surfaces, resolving adhesion trade-offs while maintaining signal integrity.

A pulse wave signal processing method limits amplitude values exceeding a threshold to generate a clean analysis signal for frequency spectrum output.

Six sensing electrodes on the upper arm feed a computing circuit to generate 12-lead electrocardiogram signals.

An electric apparatus attaches electrodes between a wearable item and skin to detect electrocardiogram signals via wireless transmission.

A multivariate spirometer captures time-series airflow, temperature, and CO2 data.

Switch-based isolation separates electrode impedance from total measurement to resolve accuracy errors caused by high contact resistance.

Optimized asymmetric windings reduce B1+ inhomogeneities and signal sensitivity outside the imaging field-of-view.

Conductive fabric sensors integrated into garments detect physiological signals without bulky cables.

Flexible abdominal RF coil assembly incorporates internal airflow passages to regulate operating temperature during magnetic resonance imaging.

Periodic sensor activation extends battery life while maintaining continuous hydration tracking through segmented bio-impedance measurements.

Evoked response audiometry analyzes brainstem patterns to monitor anesthesia depth and sensory function simultaneously.

Angled anchor structures on an implantable housing secure the device against the skull, reducing surgical invasiveness and patient discomfort.

A non-invasive glucose meter uses tongue electrodes to detect blood sugar levels instantly without finger pricking.

Optimized height prevents hair burial and buckling to ensure stable scalp contact.

Velocity signal processing determines local activation time in multi-channel electrograms, reducing procedure time and X-ray exposure during arrhythmia mapping.

A helical compliant portion within a syringe casing reduces needle insertion pressure through elastic deformation.

Copper oxide nanoparticles on a silver electrode catalyze glucose oxidation, eliminating oxygen dependence and enzyme instability for stable detection.

Event-based vision sensors detect body motion through luminance changes, reducing computational effort and power consumption for continuous health monitoring.

Processing circuitry estimates eddy magnetic fields using time-point data and gradient field differences to correct RF signal frequency or phase.

Operation processor optimizes physiological signals using pressure detector data to maintain measurement accuracy during continuous monitoring.

Ultrasonic welding joins lateral covers of wearable ring devices while shielding fragile printed circuit boards from ultrasonic wave damage.

Polyimide tape shields conductive Schanz screws from radiofrequency heating, preventing tissue damage while maintaining structural strength.

A handheld blood collection device uses a position detection system to guide needle insertion into veins for precise sample acquisition.

Segmenting pulse, respiration, and motion artifacts into independent mathematical models creates realistic physiological simulations for diagnostic testing.

Segmented slice acquisition estimates induced currents on deep brain stimulation leads to mitigate RF heating risks during magnetic resonance imaging.

Synchronizing impedance cardiography with electrocardiography signals reduces patient auxiliary current exposure while maintaining measurement accuracy.

A Doppler radar motion detector identifies temporary quiescence in pulsating biological objects through electromagnetic signal reflection.

Comparing physiological signals from multiple wearable devices resolves single-location tracking inaccuracies by adapting sensor modes to specific body parts.

A skew-determining module calculates the first derivative of photoplethysmogram signals to extract a skew metric indicative of pulse wave morphology.

A T2* corrected two-point Dixon method reconstructs pure fat and water images from magnetic resonance tomography data.

A footwear system uses sensors and machine learning to detect falls and hazards.

A multi-task model shares features across related electrocardiogram abnormalities, reducing the need for balanced training data.