The invention provides a body-worn system that continuously measures pulse oximetry and blood pressure, along with motion, posture, and activity level, from an ambulatory patient. The system features an oximetry probe that comfortably clips to the base of the patient's thumb, thereby freeing up their fingers for conventional activities in a hospital, such as reading and eating. The probe secures to the thumb and measures time-dependent signals corresponding to LEDs operating near 660 and 905 nm. Analog versions of these signals pass through a low-profile cable to a wrist-worn transceiver that encloses a processing unit. Also within the wrist-worn transceiver is an accelerometer, a wireless system that sends information through a network to a remote receiver, e.g. a computer located in a central nursing station.

A brainwave signal collecting device includes a main part and an elastic sleeve having a first opening. The main part is installed on the elastic sleeve, and the elastic sleeve can be positioned by suction on a user's head through the first opening after being pressed. The main part is in contact with the head to collect brainwave signals. The brainwave signal collecting device has an elastic sleeve serving as a flexible piece. When the brainwave signal collecting device is worn, the elastic sleeve can be pressed to partly exhaust the air therein so as to be positioned by suction on the head by the first opening of the elastic sleeve, which can improve the comfort of the head in contact with the elastic sleeve; and the position and angle at which the main part contacts the head can be adjusted through the deformation of the elastic sleeve.

An electronic apparatus includes an output interface and a controller. The output interface is configured to output a signal on the basis of scattered light from a measured part. The controller is configured to calculate a temporal change of a power spectrum on the basis of the signal and detect noise included in the signal on the basis of the temporal change of the power spectrum.

A method and system for determining a respiratory rate of a user using an electrocardiogram (ECG) segment of the user are disclosed. The method comprises decomposing the ECG segment into a plurality of functions and evaluating the plurality of functions to choose one of the plurality of functions based on a respiratory band power. The method includes determining the respiratory rate using the one of the plurality of functions and a domain detection.

A patient support apparatus comprises a support structure comprising a base and a patient support surface to support a patient. An actuator system facilitates movement of the patient support surface relative to a floor surface. One or more sensors are responsive to changes in position of the patient support surface caused by the actuator system. A controller is operably coupled to the one or more sensors and the actuator system. The controller is configured to operate the actuator system to move the patient support surface and to monitor the movement of the patient support surface by sensing positions of the patient support surface over time. The controller is further configured to identify a frictional load event on the actuator system during movement in a present cycle and associate the frictional load event with a sensed position of the patient support surface in the present cycle.

The present disclosure relates to a method and system for processing a photoplethysmogram (PPG) signal to improve accuracy of measurement of physiological parameters of a subject. The method may include removing a baseline drift from the PPG signal; obtaining a drift removed signal; filtering the drift removed signal; obtaining a filtered signal; performing motion artifact correction on the filtered signal; and obtaining a corrected signal.

The disclosure extends to methods, devices, and systems for removing speckle from a coherent light source, such as laser light. The methods, devices, and systems help eliminate or reduce speckle introduced from a coherent light source, such as laser light, by utilizing the teachings and principles of the disclosure.

A computer implemented method for determining accuracy of heart rate variability is proposed. The method comprises the following steps: a) providing at least one photoplethysmogram obtained by at least one portable photoplethysmogram device (110); b) Determining at least one signal feature by evaluating the photoplethysmogram; c) Determining the accuracy of heart rate variability by using at least one trained model, wherein the signal features determined in step b) are used as input for the trained model.

A patient monitoring device initiates an interval mode that includes measuring blood pressure at predetermined intervals over a predetermined period of time. The device takes a first blood pressure measurement at one of the predetermined intervals, and determines whether the first blood pressure measurement is abnormal. The device takes a second blood pressure measurement after a predetermined delay when the first blood pressure measurement is determined abnormal. The device compares the first and second blood pressure measurements to confirm whether the first blood pressure measurement is abnormal. The device triggers an alarm when the first blood pressure measurement is confirmed as abnormal.

In some examples, a method includes receiving a signal indicative of a blood pressure of a patient and identifying at least one first portion of the signal comprising a first characteristic of the signal exceeding a first threshold. The method also includes identifying at least one first portion of the signal comprising a second characteristic of the signal exceeding a second threshold, the first characteristic being different than the second characteristic. The method further includes determining a filtered signal indicative of the blood pressure of the patient by excluding the at least one first portion and the at least one second portion from the signal. The method includes determining a set of mean arterial pressure values based on the filtered signal and determining an autoregulation status of the patient based on the set of mean arterial pressure values.