Driver voice recordings are analyzed over time and frequency to enable rapid respiratory disease detection inside a motor vehicle.
Audio, accelerometer, and oxygen data enable low-complexity home monitoring of apnea, hypopnea, and sleep-position effects.
A cable-integrated processing module filters physiological sensor data before display, preserving mobile device performance and battery life.
An earplug sensor aimed at the tympanic membrane captures grinding and clenching sounds for reliable mobile bruxism detection.
Context-aware medical alarms adjust thresholds and alert patterns to patient characteristics, reducing alarm fatigue at emergency scenes.
Edge-cloud cough profiling separates a target user's cough from others while filtering sensitive sounds locally to improve privacy and efficiency.
A two-stage edge-cloud detector separates ambient coughs and verifies the target user, improving cough analysis accuracy while protecting privacy.
Distributed speakers and microphones track hip and head position through sound propagation, enabling non-obtrusive posture alerts.
Neural audio processing removes manual counting during exercises, helping users focus while adapting rhythm to their breathing.
Acoustic signal analysis identifies upper airway abnormalities during awake testing, resolving the trade-off between diagnostic accuracy and patient comfort.
Vibrating an acoustic sensor at its mechanical resonance frequency to detect heart sounds with high sensitivity.
A bed monitoring system integrates load, image, audio, and temperature detectors to track subject vital signs without physical contact.
Convolutional neural networks process dual respiratory signals to overcome limited information loss in conventional single-modality systems.
An implantable acoustic sensor detects heart and respiration sounds to differentiate physiological conditions.
A sensor device for electrical impedance tomography integrates spatial orientation data to adjust measured impedance distributions.
Digital signal processing analyzes lung sound features to identify diseases, overcoming the limited frequency range of human hearing.
A transducer-loudspeaker assembly hooks to traditional stethoscope eartips to capture and digitize acoustic signals.
An apnea episode determination device analyzes acoustic signals to distinguish breathing sounds from background noise during sleep.
An apnea analysis system combines photoplethysmographic and breath signals to classify respiratory events.
A wearable device merges acoustic breath sensors and pulse oximetry for continuous cardiopulmonary monitoring.
Analyzes pause intervals in tracheal acoustic signals to determine respiratory phases, improving detection accuracy when noise contaminates low-amplitude data.
Apparatus identifies sleep posture via reflection signals and breathing sounds, reducing data processing burden while maintaining detection accuracy.
Replacing mechanical sensors with thermal imaging and acoustic detection eliminates patient discomfort while maintaining cardiopulmonary measurement precision.
A piezoelectric baby breathing sensor uses a rubber mediating element to prevent surface erosion while maintaining detection accuracy.
A processing system extracts inter-beat intervals from non-ECG signals and calculates Poincare parameters to determine REM sleep stages.
A circadian rhythm oscillator calculates fatigue values by adjusting for sleep recovery and inertia to track user energy states.
A biological sound analyzing apparatus shifts reference spectra based on acquired frequency information to calculate the ratio of mixed breath sounds.
A sublingual sensor unit detects light from the tongue to generate signals for processing cardio-respiratory parameters.
A Warped Linear Prediction system generates an excitation signal to segment respiratory cycles, separating disordered breathing episodes from background noise.
Automated cough detection system analyzes acoustic energy distribution in the frequency-time domain using convolutional neural networks.
A sound sensor uses a pre-calculated transfer function to equate body-contact measurements with distance-based clinical criteria.
A sensor device records fetal movement data for later playback on external output devices.
A non-contact microphone captures airflow sounds to derive unmeasurable inspiration time through algorithmic processing.
A piezoelectric sensor analyzes chest vibration frequency amplitudes to classify acoustic events.
A compression module modifies acoustic sensor output signals to prevent saturation in downstream preamplifiers.
Automated breath sound analysis distinguishes obstructive and central sleep apnea using acoustic features.
An autonomous failure detection system monitors medical devices for unprogrammed shut-offs and electromagnetic interference.
A smartphone microphone captures respiratory sound data to determine respiration rate and tidal volume through local software analysis.
Computer system combines respiration rate sensors, activity monitors, and clinical questionnaires to determine a dyspnea value.
A wearable infant monitoring system detects sleep position, temperature, and carbon dioxide levels to identify modifiable environmental risk factors.
A force sensor uses conductive fabric and insulative mesh to detect pressure distribution, resolving accuracy limits in flexible auscultation training systems.