Respiratory Organ Evaluation TRIZ Cases

An intermeshed conducting wire forms a gapless loop to eliminate electrical noise and improve signal-to-noise ratio for accurate respiratory volume measurement.

A millimeter-wave radar system estimates angle of arrival using phase difference calculations between two receiving antennas.

A measuring mat uses a piezoelectric sensor to detect patient vital signs through mechanical force conversion.

A micro-impulse radar system extracts physiological attributes from electromagnetic signals to monitor human stress conditions.

A skin-mountable nanosensor detects volatile organic compounds emitted from human skin, replacing complex laboratory equipment with disposable sensors.

A wearable magnet paired with a magnetic sensor determines distance and orientation metrics between body segments.

Optical ammonia breath sensing uses humidity conditioning and an indicator layer to eliminate water interference and improve detection accuracy.

Disposable graphene oxide sensors replace costly MRI scans to diagnose neurodegenerative diseases accurately.

A wearable breathing sensor detects apnea patterns in respiratory signals to identify swallowing events for food intake monitoring.

An external acceleration sensor measures endocardial acceleration peaks through the thoracic wall to detect respiratory events.

A capnographic system identifies breaths by analyzing carbon dioxide concentration troughs and plateaus.

Scalar product of normalized time derivatives determines inspiration expiration transitions, reducing false alarms in low-frequency radar monitoring.

An analytics engine adjusts physiological alarm limits on monitoring devices.

Continuous temperature monitoring identifies morphological features in physiological data to predict postpartum depression and anxiety.

Pressure sensors measure chest and abdomen movements to determine ventilation volume without invasive masks or high power consumption.

Segmented MRI sequences measure oxygen concentration to quantify ventilation-perfusion ratios without ionizing radiation exposure.

A multimodal signal processing system detects epileptic events by analyzing combined autonomic and neurologic data streams.

Segmented proximity sensors track distance changes across distinct body zones to distinguish normal breathing from external interference and false alarms.

A monitoring device separates ambient light from measurement signals using a transfer function model to generate accurate vital sign data.

A single infrared sensor detects respiratory CO2 levels using a tracking mechanism to identify baseline phases for processing circuitry.

A condensation nucleus counter measures particle concentration in exhaled breath without humidification.

Filter membrane extracts aerosol biomarkers from exhaled breath while removing oral contaminants to prevent sample dilution.

A wearable biometric monitor integrates multiple sensors to track physiological parameters and transmit data via a communications hub.

Reconstructs respiratory signals using empirical wavelet functions to isolate frequency components from piezoelectric sensor data.

A device generates nitrogen oxide calibration fluid via chemical reaction within a chamber to support respiratory gas analysis.

A gas sensor applies periodic physical variations to stabilize detection signals and differentiate mixture components with high selectivity.

Segmented breath-hold protocols capture dynamic gas exchange to determine net inhalation or exhalation states without hardware modifications.

Extracts vital signs from video signals using activity modeling and signal filtering to enable automated remote patient monitoring.

Automated biometric verification and compliance monitoring enforce strict subject eligibility, preventing non-user initiation while supporting cessation.

A channel regulator manages medical body area network spectrum usage by dynamically enabling or disabling access to predefined channels.

A positive airway pressure device delivers breathing cues to patients for central sleep apnea diagnosis.

An on-body biometric sensor integrates ECG, PPG, and temperature modules for continuous physiological parameter tracking.

Pneumatic system accumulates end-tidal gas samples to match neonatal breathing rates, preventing signal clipping during fast respiration cycles.

Processing circuitry adjusts garment compression based on bioelectrical signals to reduce motion noise and improve signal quality.

A medical monitoring system generates a two-dimensional footprint from respiration rate variability to detect disordered breathing patterns.

Multi-channel electromagnetic coils and magnetometers detect anatomical displacements, resolving interference issues from single-channel systems.

Rebreathing inert tracer gas reduces wash-in time and minimizes gas consumption while maintaining accurate lung clearance index determination.

An implanted electronic device uses GPS signals to track livestock location and guide animals within perimeter boundaries.

Dual signal processing extracts respiratory data from PPG waves, resolving reliability gaps in conventional oximeter monitoring.

Optical sensors analyze reflected light from skin tissue to predict hemoglobin concentration, eliminating invasive finger pricks for frequent monitoring.

Buckle detection circuitry couples respiratory effort sensing apparatus to a wearable monitoring device, triggering automatic power activation.

A sternum-mounted optical sensor detects reflected light to measure vascular blood flow and volume characteristics.

Regularized interaction matrices compute Riemannian distances between user signals, enabling real-time group biofeedback without outlier sensitivity.

Skin-contact electrode arrays in a wearable garment replace invasive needle sensors to measure muscle activity via electrical potentials.

Integrating a sensor receptacle into the handheld housing eliminates sample transfer delays that degrade detection accuracy.

Particle filtering adapts autoregressive parameters to extract respiratory rates from pulse oximeter signals under low signal-to-noise ratio conditions.

Digital demodulation correlates digitized bioimpedance response signals with reference waveforms to extract precise amplitude and phase data.

Frequency and time domain analysis filters cardiac artifacts to improve respiration rate measurement accuracy in patient monitoring.

A robotic platform integrates physiological sensors and a cloud cognitive engine to scan patients and identify health anomalies.