Historical sleep metrics are accessed. Historical sensor data is accessed. Incidences of low quality sleep experienced by the user are identified. Particular environmental conditions that affected the user during the incidences of low quality sleep are identified. A corrective plan that specifies a change to an environmental control system to reduce the particular environmental conditions is created. The behavior of the environmental control system is modified such that the environmental control system reduces the particular environmental conditions when the user sleeps in the bed.

A system for real-time monitoring of movement of a person on a mattress includes sensor devices positioned on one or more peripheral surfaces of the mattress and configured to sense motions of the one or more peripheral surfaces. The sensor devices includes at least first and second sensor devices positioned on a first side surface of the mattress. A processing subsystem is configured to receive signals indicative of the sensed motions of the peripheral surface(s) from the sensor devices, determine whether at least the sensed motions to one or more alert conditions, and selectively cause, or not cause, one or more visual and/or audio indicators to be generated based on whether at least the sensed motions correspond to the alert condition(s).

A breath detecting system and breath detecting mat thereof are disclosed. The breath detecting mat is placed under bed mattress and has a hollow board, a vibration sensor and a signal processing circuit. The vibration sensor and the signal processing circuit are mounted in the hollow board. The vibration sensor senses the micro-vibrations caused by the breathing of the person is lying on the bed mattress and outputs the breath sensing signal to the signal processing circuit. The signal processing circuit samples the sensing signal according to different moving average points to generate the fast-moving and slow-moving average signals. Since the first fast-moving and slow-moving average signals have many cross points, the signal processing circuit calculates each time difference between every two adjacent cross points. A present breath frequency is calculated according to the time differences. Therefore, the noises of the sensing signal are effectively removed.

The invention is a breath sensing device comprising a sensing pad, a plurality of coverage sensing units, and a signal processor, the coverage sensing units are disposed on the sensing pad, when a user lies down on the sensing pad, a plurality of coverage signals sensed by the coverage sensing units respectively produce a periodic change according to the deformation of a curve along the body of the user while breathing, the signal processor is electrically connected to the coverage sensing units to receive the coverage signals, and the signal processor calculates to obtain duration and proportion of the user's inspiration, expiration, and pause phase and depth information of breathing from a waveform of the coverage signals based on a signal-processing algorithm.

Provided are a method for managing bedsores based on an artificial intelligence model and an electronic device performing the same. According to an exemplary embodiment, a method for managing, by an electronic device, bedsores based on an artificial intelligence model may include: acquiring user information of a user who uses a smart mat connected to the electronic device; acquiring at least one type of sensor data from the smart mat connected to the electronic device; when at least one type of sensor data is input, acquiring the bedsores management contents for the user from the artificial intelligence model by inputting the sensor data into the artificial intelligence model that outputs the bedsores management contents for each user according to the user information; and outputting the acquired bedsores management contents.

A patient support apparatus, such as a bed, cot, stretcher, etc., for supporting a patient includes an exit detection system with multiple user-selectable modes of operation that each have different sensitivity levels for triggering an exit alert. The exit detection system also includes one or more non-user selectable modes of operation that are automatically implemented in response to a triggering action. For example, a transition mode may be automatically implemented when the user attempts to switch from a first user-selectable mode to a different user selectable mode, or a motion mode may be automatically implemented when movement of one or more components of the patient support apparatus occurs. In the transition mode, the exit detection system may use a least restrictive sensitivity level. In the motion mode, the exit detection system may inhibit exit alerts and/or change the criteria for issuing the exit alert.

A method of monitoring a patient's foot forms a thermogram of the sole of at least one foot of the patient, and determines whether the thermogram presents at least one of a plurality of prescribed patterns. The method also compares the thermogram against a prior thermogram of the same foot, and produces output information indicating the emergence of an ulcer on a given portion on the at least one foot as a function of 1) whether the thermogram is determined to present the at least one pattern, and 2) the comparison with the prior thermogram, which shows non-ulcerated tissue at the given location.

Embodiments of this disclosure are directed to an in-bed device having one or more substrates, a wireless transceiver, an antenna coupled to the wireless transceiver, and a control system. The one or more substrates are shaped to be positioned on a bed. The wireless transceiver is disposed on at least one of the one or more substrates, and configured to transmit and receive wireless pulses via the antenna. The control system is configured to cause the wireless transceiver to generate the wireless pulses and analyze the received wireless pulses to determine whether the bed is occupied by a user.

This invention relates to a prediction support system and associated methods for supporting prediction of the severity of a disease. The systems and methods may perform operations that include continuously detecting whether a patient with the disease is in bed, and acquiring, based on the detection result of the detecting, an in-bed pattern indicating, as a time series, whether the patient is in bed. The systems may include a detection device and an acquisition unit.

In accordance with an embodiment, a mobile infant care device includes a carrier having an inner space configured to hold an infant positioned therein, and driving wheels provided at a lower part of the carrier; a monitoring system affixed to the carrier and configured to monitor a state of the infant positioned in the inner space of the carrier; a driving system coupled to the driving wheels, the driving system configured to move a position of the carrier by driving the driving wheels; a communication system configured to wirelessly transmit a monitoring result of the monitoring system to a user terminal device or to wirelessly receive an operation input from the user terminal device; and a controller configured to cause the driving system to move the carrier based on the monitoring result of the monitoring system or the operation input received through the communication system.