Respiratory Organ Evaluation TRIZ Cases

Millimeter-wave radar sensor employs two-phase scanning with micro-Doppler measurements to distinguish humans from other moving objects.

Segmented channels and ratio-based estimation recover clipped physiological signals, maintaining measurement precision across high amplitude movement.

A bio-impedance measurement unit uses a baseline cancellation current circuit to subtract reference noise from the signal path.

A micro impulse radar transceiver circuit detects physiological parameters using ultra-wideband electromagnetic pulses.

Radar sensor system calculates autocorrelation of reflected signals to resolve phase lag measurement errors in non-invasive monitoring.

A wearable monitoring system integrates electrodes, piezoelectric sensors, and accelerometers to detect vital signs without direct contact.

Wireless sensor device detects respiratory signals using a patch form factor.

A peak expiratory flow apparatus uses a variable cross-sectional bypass channel to direct airflow and detect pressure changes.

Depth mapping monitors abdominal movement to detect respiratory arrest and rolling, replacing uncomfortable physical sensors with non-contact optical analysis.

Acoustic concentrators funnel low-frequency sounds onto sensors, resolving the trade-off between detection sensitivity and animal comfort.

A microwave sensor system calculates radar cross section values to estimate living body motion using antenna arrays.

Automated phase detection applies rule-based analysis to patient monitoring parameters, reducing manual assessment time and improving resource management.

A processor determines respiratory effort by smoothing relaxed and forced breathing signals with different averaging windows.

Heating the pneumatic circuit to 37°C prevents condensation, enabling reliable gas concentration measurements across multiple exhalation flows.

Dynamic time intervals adapt to instantaneous pulse rates, improving respiration rate accuracy by overcoming fixed interval limitations in photoplethysmography.

A gas sensor module uses a pump assembly to deliver breath samples through a fluid channel for consistent exposure.

Multi-sensor fusion in an intraoral device measures oropharyngeal strength to reduce aspiration risk while maintaining low power consumption.

Analyzing exhaled breath volatile organic markers enables non-invasive blood glucose determination without skin penetration.

A sigmoid function transforms electrical impedance tomography pixel values into absolute probability indicators for rapid lung visualization.

Sliding window segmentation isolates baseband signals to resolve movement artifacts that distort contactless heart and respiratory rate measurements.

Thermistor analyzes nasal airflow thermal cycles to detect apnea events, resolving false negatives from insensitive monitoring.

Segmented visual markers track intermediate respiratory states, improving radiotherapy accuracy.

An oral appliance with an airway resistor and pressure sensor measures ventilation airflow through localized pressure changes.

A non-invasive sensor detects skull deformation to produce digital intracranial pressure data for continuous monitoring.

A wearable sensor device measures respiratory rate and blood metrics using LED-based optical signals.

An acoustic system detects breathing motions using sound wave echoes to generate motion waveforms for medical analysis.

A smart glove integrates dual photoplethysmography sensors to estimate blood oxygen saturation and respiration rate.

Radio wave sensors monitor heart rate and breathing to prevent infant harm from invasive pulse oximeters.

Flow regulator separates inflow and outflow components to enable accurate zero point correction of pressure sensors despite gas flow disturbances.

Segmented loop parts tuned to specific frequencies resolve the trade-off between adaptability and measurement precision in inductive sensing.

Extracts shape-reference voltage waveforms using principal component analysis to measure tidal volume from electrical impedance tomography data.

A wearable neckband integrates acceleration sensors and a processor to detect user states like falls and monitor vital signs.

Detects volatile compounds in exhaled breath via sensors, enabling rapid diagnosis without invasive sampling or lengthy lab processes.

A vehicle cabin system measures upper body movement to derive breathing amplitude and rate for stress level determination.

An orally inserted probe uses extra-oral sensors to measure respiratory rate, heart rate, and oxygen saturation.

A unified monitoring interface displays maternal, fetal, and newborn parameters on a single screen.

Automated ABD event monitoring analyzes breathing volume signals only during specific bradycardia and desaturation windows to reduce false positives.

Unique pseudo-random codes encode exciting currents to reduce mutual inductance between coils and eliminate time synchronization requirements.

Bed-mounted seismic sensors detect body vibrations to monitor heart rate and respiration without wearable devices.

Synchronizing neural stimulation pulses with respiratory cycles mitigates adverse effects on breathing functions while maintaining therapeutic effectiveness.

An implantable system detects apnea onset by accumulating respiration amplitude differences against a moving threshold for real-time therapy initiation.

Electromagnetic radar tracks location and vital signs without contact sensors or video surveillance.

A light field reflector attached to the patient body surface reflects gantry light for camera-based imaging.

A mobile hand-held computer communicates with a separate spirometer to collect and store lung function data via electronic signals.

System derives continuous dead space fraction from respiration data to resolve the trade-off between measurement accuracy and monitoring frequency.

A wearable device combines photoplethysmography and electrodermal activity signals to determine respiration state.

Analyzing vital sign homogeneity across spatially separated face regions distinguishes living tissue from spoofing attempts without human intervention.

Multitaper spectral analysis overcomes visual scoring subjectivity by computing spectrograms that reveal non-stationary dynamics and improve staging accuracy.

Segmented emitter and detector modules enable portable capnography, resolving the trade-off between measurement accuracy and operational freedom.

Millimeter wave mapping systems generate point clouds to determine human vital signs without capturing image data.