The present invention relates to a respiratory sensing device attached to a patient's body and configured to acquire information regarding the patient's respiratory condition by sensing a vibration generated due to the patient's respiration using the piezoelectric effect and a respiratory monitoring system configured to output the acquired information regarding the patient's respiratory state.

According to an embodiment, a bed system includes a plurality of bed devices and a first input/output device capable of communicating with the plurality of bed devices. The first input/output device implements a first operation. During the first operation, the first input/output device receives input of a first set value relating to a first item set in each of the plurality of bed devices. At least one of the first input/output device and the plurality of bed devices implements an operation corresponding to the first set value. Thus, a bed system having improved usability is provided.

A respiration rate detection device including a photoplethysmography (PPG) detector, an acceleration detector and a processing unit is provided. The processing unit calculates an acceleration peak frequency in an acceleration frequency spectrum, and takes a PPG acceleration peak frequency in a PPG frequency spectrum corresponding to the acceleration peak frequency as a respiration rate.

A micro impulse radar (MIR) system includes an MIR transceiver circuit configured to transmit, towards a subject, at least one transmitted radar signal, and receive at least one radar return signal. The system includes a control circuit configured to generate a control signal defining a radar signal parameter of the at least one transmitted radar signal, provide the control signal to the MIR transceiver circuit to cause the MIR transceiver circuit to transmit the at least one transmitted signal based on the radar signal parameter, and determine, based on the at least one radar return signal, a physiological parameter of the subject.

Devices and methods for generating synthetic cardio-respiratory signals from one or more ballistocardiogram (BCG) sensors. A method for determining item specific parameters includes obtaining ballistocardiogram (BCG) data from one or more sensors, where the one or more sensors capture BCG data for one or more subjects in relation to a substrate. For each subject, the captured BCG data is pre-processed to obtain cardio-respiratory BCG data. The cardio-respiratory BCG data is sub-sampled to generate the cardio-respiratory BCG data at a cardio-respiratory sampling rate conducive to cardio-respiratory signal generation. The sub-sampled cardio-respiratory BCG data is cardio-respiratory processed to generate a cardio-respiratory parameter set. A synthetic cardio-respiratory signal is generated from at least the cardio-respiratory parameter set and a cardio-respiratory event morphology template. A condition of the subject is determined based on the synthetic cardio-respiratory signal.

An inductive sensing system (8) has a resonator circuit (10) with an antenna (12) for simultaneously applying electro-magnetic signals to a body and sensing secondary electromagnetic signals returned from the body. The system includes signal sensing means (30) which is configured to detect a measure indicative of an imaginary part of an additional inductance component added to the resonator circuit by the secondary electromagnetic signals but which does not measure the real part. In particular, the signal sensing means may be configured to detect a measure indicative of damping in the resonator circuit (e.g. a damping factor), and comprises no means for detecting any measure indicative of variations in a natural frequency of the resonator circuit.

In one aspect, a computer-implemented method includes receiving a signal corresponding to impedance across a patient's chest cavity; filtering the signal using one or more filters that reduce noise and center the signal around a zero baseline; adjusting an amplitude of the filtered signal based on a threshold value; separating the amplitude-adjusted signal into component signals, where each of the component signals represents a frequency-limited band; detecting a fractional phase transition of a component signal of the component signals; selecting a dominant component signal from the component signals based on amplitudes of the component signals at a time corresponding to the detected fractional phase transition; determining a frequency of the dominant component signal at the time corresponding to the detected fractional phase transition; and determining a respiratory rate of the patient based on the determined frequency.

Embodiments of the present disclosure sets forth a computer-implemented method comprising receiving, from at least one sensor, sensor data associated with an environment, computing, based on the sensor data, a cognitive load associated with a user within the environment, computing, based on the sensor data, an affective load associated with an emotional state of the user, determining, based on both the cognitive load at the affective load, an affective-cognitive load, determining, based on the affective-cognitive load, a user readiness state associated with the user, and causing one or more actions to occur based on the user readiness state.

Aspects of the present disclosure provide methods, apparatuses, and systems for accurately determining sleep and wake onset based on a user's personalized physiological parameters for sleep and wake. First, a user is determined to be asleep using population level data. Thereafter, sensor collected data is used to determine the user's distribution of values of a physiological parameter when the user is asleep. This distribution of values is then used, instead of population-level data, to determine the user is asleep in real-time. As a result, the content and interventions are provided to help users get back to sleep. Further, the described techniques allow more accuracy in determining sleep statistics which can guide recommended interventions and therapies.

The invention relates to a control device for controlling a measurement system for measuring blood pressure and optionally hemodynamic parameters of a subject. In a first measurement time period T.sub.1, for measured pressure pulses, features are determined, which characterize the respective pressure pulse. Based on the features, start values are determined and, based on the start values, a start curve TPW_F-curve is formed. The measurement system is controlled such that, after the start curve has reached a first maximum, a second measurement time period T.sub.2 succeeds, wherein a blood pressure value is determined based on the pressure measured in the second measurement time period. It has been found that by using the maximum in the first measurement time period for defining a start point for the actual blood pressure measurement, a blood pressure value and optionally also hemodynamic parameters of a subject can be determined very accurately and fast.