Abstract: A flow generator for generating a mixed oxygen air flow, the flow generator including a body having a first inlet, a second inlet, an outlet, and one or more inner surfaces that define a first inner chamber in fluid communication with the first inlet and the second inlet, a second inner chamber in fluid communication with the first inner chamber, and a third inner chamber in fluid communication with the second chamber and the outlet of the body. The flow generator includes a connector disposed in the first inlet and a nozzle disposed within at least a portion of the connector and extending into the first inner chamber. The flow generator further includes an adapter engaged to the nozzle to form a fluid tight path such that the adapter connects to an external oxygen source and transports oxygen into the nozzle.

Abstract: A flow generator for generating a mixed oxygen air flow, the flow generator including a body having a first inlet, a second inlet, an outlet, and one or more inner surfaces that define a first inner chamber in fluid communication with the first inlet and the second inlet, a second inner chamber in fluid communication with the first inner chamber, and a third inner chamber in fluid communication with the second chamber and the outlet of the body. The flow generator includes a connector disposed in the first inlet and a nozzle disposed within at least a portion of the connector and extending into the first inner chamber. The flow generator further includes an adapter engaged to the nozzle to form a fluid tight path such that the adapter connects to an external oxygen source and transports oxygen into the nozzle.

Abstract: A computer-implemented system and method provide an audio label for a noise signal. The computer-implemented system and method include receiving an audio input and obtaining the noise signal from the audio input. The computer-implemented system and method include extracting audio features of the noise signal. The computer-implemented system and method include determining and outputting an audio label for the extracted audio features of the noise signal based on machine learning data.

Abstract: A system for monitoring dietary activity of a user includes a wearable device having at least one audio input unit configured to record an audio sample corresponding to audio from a user's neck. The system further includes a processor configured to execute programmed instructions stored in a memory to obtain an audio sample from the audio input unit of a wearable device, determine segmental feature values of a set of selected features from the audio sample by extracting short-term features in the set of selected features from the audio sample and determining the segmental feature values of the set of selected features from the extracted short-term features. The processor is further configured to, using a classifier, classify a dietary activity based on the determined segmental feature values of the audio sample and generate an output corresponding to the classified dietary activity.

Abstract: A method and system for detecting abnormal heart sounds in a phonocardiogram of a person are disclosed. At least one segmented cardiac cycle of the phonocardiogram is received at a processor. The processor decomposes the segmented cardiac cycle into a plurality of frequency sub-bands using a first convolutional neural network having, in particular a plurality of time-convolution layers (tConv). The kernel weights of each time-convolution layer are learned in a training process such that the time-convolution layers identify pathologically significant frequency sub-bands. The processor determines a probability that the segmented cardiac cycle contains an abnormal heart sound based on the plurality of frequency sub-band segments using at least one further neural network. In some embodiments, the time-convolution layers are configured to have a linear phase response (LP-tConv) or a zero phase response (ZP-tConv).

Abstract: A system for monitoring dietary activity of a user includes a wearable device having at least one audio input unit configured to record an audio sample corresponding to audio from a user's neck. The system further includes a processor configured to execute programmed instructions stored in a memory to obtain an audio sample from the audio input unit of a wearable device, determine segmental feature values of a set of selected features from the audio sample by extracting short-term features in the set of selected features from the audio sample and determining the segmental feature values of the set of selected features from the extracted short-term features. The processor is further configured to, using a classifier, classify a dietary activity based on the determined segmental feature values of the audio sample and generate an output corresponding to the classified dietary activity.

Abstract: A method for verifying that a person is registered to use a telemedical device includes identifying an unprompted trigger phrase in words spoken by a person and received by the telemedical device. The telemedical device prompts the person to state a name of a registered user and optionally prompts the person to state health tips for the person. The telemedical device verifies that the person is the registered user using utterance data generated from the unprompted trigger phrase, name of the registered user, and health tips.

Abstract: A method for verifying that a person is registered to use a telemedical device includes identifying an unprompted trigger phrase in words spoken by a person and received by the telemedical device. The telemedical device prompts the person to state a name of a registered user and optionally prompts the person to state health tips for the person. The telemedical device verifies that the person is the registered user using utterance data generated from the unprompted trigger phrase, name of the registered user, and health tips.

Abstract: A method for verifying that a person is registered to use a telemedical device includes identifying an unprompted trigger phrase in words spoken by a person and received by the telemedical device. The telemedical device prompts the person to state a name of a registered user and optionally prompts the person to state health tips for the person. The telemedical device verifies that the person is the registered user using utterance data generated from the unprompted trigger phrase, name of the registered user, and health tips.

Abstract: A method for verifying that a person is registered to use a telemedical device includes identifying an unprompted trigger phrase in words spoken by a person and received by the telemedical device. The telemedical device prompts the person to state a name of a registered user and optionally prompts the person to state health tips for the person. The telemedical device verifies that the person is the registered user using utterance data generated from the unprompted trigger phrase, name of the registered user, and health tips.