A diagnostic device is disclosed for characterisation of particles from a patient's airways, such as a lung, when ventilated by a ventilator, and/or for control thereof, comprising a particle detecting unit configured to be connected to a conduit for passing expiration fluid from said patient, for obtaining data related to particles being exhaled from said patient's airways.

A diagnostic device is disclosed for characterisation of particles from a patient's airways, such as a lung, when ventilated by a ventilator, and/or for control thereof, comprising a particle detecting unit configured to be connected to a conduit for passing expiration fluid from said patient, for obtaining data related to particles being exhaled from said patient's airways.

A system and method for identifying sleep states of a subject are provided. In some aspects, the method includes acquiring physiological data from a subject over a sleep period using sensors positioned about the subject, and assembling the physiological data into time-series datasets. The method also includes selecting a temporal window in which signals associated with the time-series datasets are substantially stationary, computing a time bandwidth product based on a selected spectral resolution and the selected temporal window, and determining a number of tapers using the computed time bandwidth product. The method further includes computing a spectrogram using the determined number of tapers and the time-series datasets, analyzing the spectrogram to identify signatures of sleep in the subject, and generating, using the identified signatures, a report indicative of sleep states of the subject.

A system for carbon dioxide (CO2) removal from a circulatory system of a patient includes a medical device providing extracorporeal lung assist (ECLA) treatment to the patient through extracorporeal removal of CO2 from the patient's blood; at least one control unit controlling the operation of the medical device so as to control a degree of CO2 removal obtained by the ECLA treatment; and a bioelectric sensor detecting a bioelectric signal indicative of the patient's efforts to breathe. The at least one control unit is configured to control the operation of the medical device based on the detected bioelectric signal.

A leadwire for physiological patient monitoring is provided that transfers potentials received at a chest electrode to a data acquisition device. The leadwire includes an electrode end connectable to the chest electrode and a first conductive layer extending from the electrode end. The leadwire also has a device end connectable to a data acquisition device and a second conductive layer extending from the device end. The first conductive layer is galvanically isolated from the second conductive layer such that the first conductive layer and the second conductive layer form a capacitor.

Methods and apparatus for determining biological effects of environmental sounds are disclosed. An example apparatus includes a sound characteristic analyzer to identify a sound event based on audio data in an environment. The example apparatus includes a physiological data analyzer to identify a physiological event based on physiological response data collected from a user exposed to the sound event in the environment. The example apparatus includes a correlation identifier to identify a correlation between the sound event and the physiological event and a report generator to generate a report based on the correlation.

A method for continuous acoustic signature recognition and classification includes a step of obtaining an audio input signal from a resonant microphone array positioned proximate to a target, the audio input signal having a plurality of channels. The target produces characterizing audio signals depending on a state or condition of the target. A plurality of features is extracted from the audio input signal with a signal processor. The plurality of features is classified to determine the state of the target. An acoustic monitoring system implementing the method is also provided.

A method for continuous acoustic signature recognition and classification includes a step of obtaining an audio input signal from a resonant microphone array positioned proximate to a target, the audio input signal having a plurality of channels. The target produces characterizing audio signals depending on a state or condition of the target. A plurality of features is extracted from the audio input signal with a signal processor. The plurality of features is classified to determine the state of the target. An acoustic monitoring system implementing the method is also provided.

One aspect of the apparatus comprising, a sensor configured to acquire a biological signal of a user, and a controller configured to, determine whether the biological signal is continuously outside a predetermined range for a first time period, after determining that the biological signal has been continuously outside the predetermined range for the first time period, then determine whether the biological signal is inside the predetermined range, and activate an alarm if the controller has determined that (i) the biological signal has been outside the predetermined range for the first time period, and (ii) the biological signal has been continuously inside the predetermined range for a second time period, the second time period being longer than the first time period.

A physiological sensor device and system, and a correction method are provided. The physiological sensor device includes a physiological signal sensor, a first compensation sensor, and a signal processing device. The physiological signal sensor is attached to an object to be detected to sense a physiological signal value. The first compensation sensor is disposed on the physiological signal sensor. The signal processing device is coupled to the physiological signal sensor and the first compensation sensor. The signal processing device obtains through the first compensation sensor a failure region of the physiological signal sensor partially detached from the object to be detected and obtains a first failure compensation value according to the failure region, so as to compensate the physiological signal value sensed by the physiological signal sensor.