In one embodiment, a method includes accessing, from a first sensor of a wearable device, motion data representing motion of a user and determining, from the motion data, an activity level of the user. The method includes selecting, based on the activity level, an activity-based technique for estimating the breathing rate of the user, which is used to determine a breathing rate of the user. The method further includes determining a quality associated with the breathing rate and comparing the determined quality with a threshold. If the determined quality is not less than the threshold, then the method includes using the determined breathing rate as a final breathing-rate determination for the user. If the determined quality is less than the threshold, then the method includes activating a second sensor of the wearable device and determining, based on data from the second sensor, a breathing rate for the user.

A monitoring system for measuring and monitoring a respiratory rate of a subject includes an optical projector configured to project an optical pattern and an image capturing module configured to capture images of the optical pattern reflecting from a surface. The monitoring system further comprises an alarm device, a processor, and a memory. The memory includes instructions that, when executed by the processor, cause the processor to monitor the respiration rate of the subject based on changes to the optical pattern reflected from the surface. The processor is further caused to determine if the monitored respiration rate is within a threshold variance and, upon a determination that the monitored respiration rate is outside of the threshold variance, generate a notification with the alarm device.

A monitoring system for measuring and monitoring a respiratory rate of a subject includes an optical projector configured to project an optical pattern and an image capturing module configured to capture images of the optical pattern reflecting from a surface. The monitoring system further comprises an alarm device, a processor, and a memory. The memory includes instructions that, when executed by the processor, cause the processor to monitor the respiration rate of the subject based on changes to the optical pattern reflected from the surface. The processor is further caused to determine if the monitored respiration rate is within a threshold variance and, upon a determination that the monitored respiration rate is outside of the threshold variance, generate a notification with the alarm device.

A swallowing medical device includes: an attachment unit configured to be attached to a target portion of a human body for a medical operation; a control unit configured to control the medical operation; and a storage configured to store use information regarding a use state over time of the attachment unit. The control unit executes a control for restricting use of the attachment unit on the basis of a fact that the use information does not satisfy a set condition for ensuring a characteristic of the attachment unit.

Embodiments detect obstructive sleep apnea (“OSA”) by a user. Embodiments receive audio data emanating from the user while the user is sleeping, the audio data including multiple distinct frequency bands. Embodiments analyze the audio data to detect patterns in frequency content that matches two or more formants of a plurality of formants, the two or more formants indicating a position of a tongue of the user. Based on the analyzing, embodiments determine when the tongue has moved from a forward position to a rear position in an oral cavity of the user. Embodiments generate a signal indicating an OSA episode when it is determined that the tongue has moved from a forward position to a rear position.

Embodiments detect obstructive sleep apnea (“OSA”) by a user. Embodiments receive audio data emanating from the user while the user is sleeping, the audio data including multiple distinct frequency bands. Embodiments analyze the audio data to detect patterns in frequency content that matches two or more formants of a plurality of formants, the two or more formants indicating a position of a tongue of the user. Based on the analyzing, embodiments determine when the tongue has moved from a forward position to a rear position in an oral cavity of the user. Embodiments generate a signal indicating an OSA episode when it is determined that the tongue has moved from a forward position to a rear position.

A method of monitoring respiration with an acoustic measurement device, the acoustic measurement device having a sound transducer, the sound transducer configured to measure sound associated with airflow through a mammalian trachea, the method includes correlating the measured sound into a measurement of tidal volume and generating at least one from the group consisting of an alert and an alarm if the measured tidal volume falls outside of a predetermined range.

A method of monitoring respiration with an acoustic measurement device, the acoustic measurement device having a sound transducer, the sound transducer configured to measure sound associated with airflow through a mammalian trachea, the method includes correlating the measured sound into a measurement of tidal volume and generating at least one from the group consisting of an alert and an alarm if the measured tidal volume falls outside of a predetermined range.

A system includes a memory, an optical subsystem, an audio system, a plurality of sensors outputting sensor data, a communication circuitry, and a processor. The processor is configured to input to a baby-specific educational machine learning model, image data, audio signal data, sensor data, baby personal data associated with a baby, and a visual image and a sound presented to the baby based on a baby-specific educational plan; to receive an output from the baby-specific educational machine learning model where the output includes an indication that the baby understood or did not understand the visual image and the sound associated with the baby-specific educational plan, and a baby-specific educational recommendation based on the indication; and to execute based on the baby-specific educational recommendation, a modification of the baby-specific educational plan, or a continued execution of the baby-specific educational plan.

A system includes a memory, an optical subsystem, an audio system, a plurality of sensors outputting sensor data, a communication circuitry, and a processor. The processor is configured to input to a baby-specific educational machine learning model, image data, audio signal data, sensor data, baby personal data associated with a baby, and a visual image and a sound presented to the baby based on a baby-specific educational plan; to receive an output from the baby-specific educational machine learning model where the output includes an indication that the baby understood or did not understand the visual image and the sound associated with the baby-specific educational plan, and a baby-specific educational recommendation based on the indication; and to execute based on the baby-specific educational recommendation, a modification of the baby-specific educational plan, or a continued execution of the baby-specific educational plan.