An example of a system for monitoring and treating respiratory distress in a patient may include signal inputs, a signal processing circuit, and a respiratory distress analyzer. The signal inputs may be configured to receive patient condition signals indicative of autonomic balance of the patient. The signal processing circuit may be configured to process the patient condition signals and to generate patient condition parameters indicative of the autonomic balance using the processed patient condition signals. The respiratory distress analyzer may be configured to determine a state of the respiratory distress using the patient condition parameters, and may include a parameter analysis circuit configured to analyze the autonomic balance of the patient and to determine the state of the respiratory distress using an outcome of the analysis.

A bed has a mattress. A sensor is configured to sense sleep readings of a user sleeping on the bed. An automation controller is configured to transmit the sleep readings to a cloud service. Hardware hosting the cloud service is configured to compare the sleep readings with trend data in order to generate adjustments to the user's sleep environment.

A health data management system includes a health data measurement apparatus and a health management server communicable therewith. The apparatus includes medical and health equipment that measures health data of a user and first circuitry that collects the health data. The management server includes a first memory that stores the health data from the apparatus and second circuitry. Based on the stored health data, the second circuitry generates health management data representing a health state of the user, and analyzes at least one of an item indicating a worsening health state of the user, an item with insufficient measurement data, or an item lacking measurement data as a required check item. When determined that the health management data includes the required check item, the second circuitry transmits to the apparatus a message prompting the user to take a measurement of the required check item, and requests the health data.

Some systems, devices and methods detailed herein provide a system for use in determining metrics of a subject. The system can provide, as an output, a function-metric value determined based on a defined relationship between physiological measures and a chronological age.

The present invention relates to a method for improving sleep quality, comprising the steps of measuring pressure by means of sensors in locations distributed by regions of a mattress; calculating the SQI based on the prominent movements detected depending on the time of night; calculating the mean pressure measured by each sensor; calculating the difference between the mean pressure and the pressure measured by that sensor when there is no user on the mattress; calculating the mean pressure difference for each region of the mattress; calculating a weight factor for each region of the mattress; comparing the weight factor with a reference value; varying the configuration of the mattress by increasing or reducing the support level in the regions. The present invention also relates to a related system and mattress.

The methods, systems and devices provided herein relate to sleep-aid. Some embodiments include a vibration source and/or a sound source. In some embodiments, the vibration source and/or sound source emit vibrations and/or sounds that stimulate a subject's vagus nerve, or another nerve, to induce sleep or relaxation in the subject.

A human body sensing mat for sensing the movement of a human body, comprises: a substrate; a sensor array including a plurality of fiber sensors for generating signals according to a distance to a specific object, and disposed on the substrate; and a driving unit for applying a voltage to the sensor array, wherein the sensor array includes a plurality of sensing lines arranged in parallel in a first direction, and regarding the plurality of sensing lines, a first distance between neighboring sensing lines connected to different electrodes is greater than a second distance between neighboring sensing lines connected to the same electrode. The human body sensing mat can analyze user's movements and biometric signals regardless of the user's posture.

A blood pressure measurement device measures a blood pressure of a subject by a blood pressure measurement unit, detects a body sound of the subject during blood pressure measurement by a sound detection unit. The measured blood pressure and the detected body sound are recorded in association with each other by time information. The factor for the increase of measured blood pressure value can be specified by showing the chronological blood pressure measurement result along with checking the presence or absence of a body sound such as snoring etc.

A control circuit for a wearable device includes: a power supply circuit, a DC blocking circuit, and a voltage comparison circuit. The power supply circuit is connected to a high voltage end, a low voltage end, a first signal input end, a second signal input end; the DC blocking circuit is connected to the first node, the second node, and a sensor in the wearable device; the voltage comparison circuit is connected to the first node, a reference voltage end and an output end, and configured to compare voltages of the first node and the reference voltage end; and output a first control signal through the output end when the voltage of the first node is smaller than the voltage of the reference voltage end, and output a second control signal through the output end when the voltage of the first node is larger than the voltage of the reference voltage end.

A fitness fatigue score for a user for a current day is provided. The fitness fatigue score can be determined based, at least in part, on first data obtained over a first period of time, second data obtained over a second period of time that is shorter in duration than the first period of time, and third data obtained over a third period of time that is longer in duration than the first period of time. The first data includes heart rate measurements for the user over the first period of time. The second data includes one or more sleep metrics for a plurality of sleep events for the user over the second period of time. The third data includes heart rate variability for the user over the third period of time. Additionally, a recommendation regarding exercise for the current day can be generated based on the fitness fatigue score.