Abstract: A system adapted to assisting patients manage asthma includes a wearable sensor for detection of asthma symptoms and inhaler use, having a microphone capable of generating an electrical signal indicative of asthma symptoms or inhaler use; a processor with firmware adapted to process the electrical signal to determine potential asthma symptoms and inhaler use; and store the electrical signal in the memory when the electrical signal potentially corresponds asthma symptoms or inhaler use. In particular embodiments, the system includes an electronic asthma diary including detected asthma symptoms and detected inhaler usage, both with timestamps, and a prescribed treatment protocol. Protocol firmware processes detected asthma symptoms an inhaler usage recorded in the asthma diary to determine if asthma is controlled, and if asthma is not determined controlled determines if a treatment change is authorized; if treatment change is authorized the treatment change is displayed in human-readable form.

Abstract: A monitoring device has microphones, an ADC; a digital radio; and a processor with firmware. The firmware includes code for digitizing audio from the microphones into time-domain audio, performing FFT to provide frequency-domain audio, running a first neural network on time domain and frequency-domain audio to extract features, executing a classifier on the features to identify candidate events, and using the digital radio to upload candidate events and features. A pressure sensor awakens the processor from a low-power state. In particular embodiments, the first neural network is an embedded Gated Recurrent Unit having weights trained to extract features of use in the classifier; and candidate events include normal inhalation and exhalation breathing sounds, crackles, wheezes, coughs, snoring, gasping, choking, and speech sounds and in some embodiments heart sounds. A method of monitoring breathing during sleep includes attaching the device to, or embedding the device within, a pillow.

Abstract: A system adapted to assisting patients manage asthma includes a wearable sensor for detection of asthma symptoms and inhaler use, having a microphone capable of generating an electrical signal indicative of asthma symptoms or inhaler use; a processor with firmware adapted to process the electrical signal to determine potential asthma symptoms and inhaler use; and store the electrical signal in the memory when the electrical signal potentially corresponds asthma symptoms or inhaler use. In particular embodiments, the system includes an electronic asthma diary including detected asthma symptoms and detected inhaler usage, both with timestamps, and a prescribed treatment protocol. Protocol firmware processes detected asthma symptoms an inhaler usage recorded in the asthma diary to determine if asthma is controlled, and if asthma is not determined controlled determines if a treatment change is authorized; if treatment change is authorized the treatment change is displayed in human-readable form.

Abstract: A device for detecting and quantifying lung function includes a piezoelectric sensor configured for attachment to a mammalian chest wall and to feed signals to an ADC providing digitized signals to a processor. The processor firmware extracts inspiration and expiration times from the digitized signals and generates an I/E ratio from them. The processor has firmware to detect wheezing sounds in the signals. The device has an analog event detector configured to wake-up the processor upon detection of candidate wheeze sounds in the signals. In embodiments, the analog event detector includes bandpass filters coupled to a modeling circuit feeding a correlation circuit, the filters having bandpass adjusted by feedback from a circuit within the analog event detector. In an embodiment, the device uses an FFT with a gated recurrent unit (GRU) with partial reset (GRUPR) neural network to detect wheezes.

Abstract: A monitoring device has microphones, an ADC; a digital radio; and a processor with firmware. The firmware includes code for digitizing audio from the microphones into time-domain audio, performing FFT to provide frequency-domain audio, running a first neural network on time domain and frequency-domain audio to extract features, executing a classifier on the features to identify candidate events, and using the digital radio to upload candidate events and features. A pressure sensor awakens the processor from a low-power state. In particular embodiments, the first neural network is an embedded Gated Recurrent Unit having weights trained to extract features of use in the classifier; and candidate events include normal inhalation and exhalation breathing sounds, crackles, wheezes, coughs, snoring, gasping, choking, and speech sounds and in some embodiments heart sounds. A method of monitoring breathing during sleep includes attaching the device to, or embedding the device within, a pillow.

Abstract: A system adapted to assisting patients manage asthma includes a wearable sensor for detection of asthma symptoms and inhaler use, having a microphone capable of generating an electrical signal indicative of asthma symptoms or inhaler use; a processor with firmware adapted to process the electrical signal to determine potential asthma symptoms and inhaler use; and store the electrical signal in the memory when the electrical signal potentially corresponds asthma symptoms or inhaler use. In particular embodiments, the system includes an electronic asthma diary including detected asthma symptoms and detected inhaler usage, both with timestamps, and a prescribed treatment protocol. Protocol firmware processes detected asthma symptoms an inhaler usage recorded in the asthma diary to determine if asthma is controlled, and if asthma is not determined controlled determines if a treatment change is authorized; if treatment change is authorized the treatment change is displayed in human-readable form.