# Respiratory sound classification

Researchers developed a flexible wireless wearable stethoscope based on a 25-element circular aluminum nitride (AlN) piezoelectric micromachined ultrasonic transducer (PMUT) array that achieves a packaged sensitivity of −167.5 dB, an operating bandwidth of 10 Hz–10 kHz, and a frequency-response flatness of ±0.5 dB; across multiple participants it acquired heart sounds at five standard auscultation sites with temporal correspondence to reference ECG and chest-motion signals, tracked heart rate continuously during dynamic activities such as walking and stair climbing, and, coupled with a residual neural network, classified five respiratory states (awake, asleep, apnea, rhonchi, and wheeze) with 98.7% accuracy.

Researchers developed a flexible wireless wearable stethoscope based on a 25-element circular aluminum nitride (AlN) piezoelectric micromachined ultrasonic transducer (PMUT) array that achieves a packaged sensitivity of −167.5 dB, an operating bandwidth of 10 Hz–10 kHz, and a frequency-response flatness of ±0.5 dB; across multiple participants it acquired heart sounds at five standard auscultation sites with temporal correspondence to reference ECG and chest-motion signals, tracked heart rate continuously during dynamic activities such as walking and stair climbing, and, coupled with a residual neural network, classified five respiratory states (awake, asleep, apnea, rhonchi, and wheeze) with 98.7% accuracy.