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.