Abstract: A patient support apparatus includes a bed including a frame. A mattress is supported by the frame. A respiratory therapy apparatus is supported by the frame. A pneumatic system is operable to inflate at least one bladder of the mattress and operable to deliver air to the respiratory therapy apparatus.

Abstract: An example method for estimating a disease state for a patient can include: capturing physiological data including images from the patient over time; processing the physiological data to detect a variability; comparing the variability to a baseline or a range; and estimating the disease state for the patient based upon the comparing of the variability to the baseline or the limit.

Abstract: A system is provided for monitoring a patient on an air support system. The system comprises a capacitive sensor system having a capacitive sensor positioned at the underside of an air filled mattress, and a respiration signal processing module that receives the output of the capacitive sensor system and is configured to monitor patient respiration. Respiration is monitored by: periodically sampling the capacitive sensor system output to obtain measurements of incremental body displacement; analyzing a plurality of the samples to determine one or more values for parameters of patient respiratory rate; and determining when one or more of the parameter values indicate abnormal respiration. A corresponding method and computer program are also provided.

Abstract: A method and related apparatus for deriving mean arterial pressure of a subject, including receiving data relating to at least one cardiac cycle of a bio-signal from the subject; normalizing the received data relating to the at least one cardiac cycle; calculating an area enclosed by the normalized received data to obtain a normalized area; calculating a heart rate of the subject from the at least one cardiac cycle; and deriving the mean arterial pressure from the normalized area and heart rate.

Abstract: Devices, systems, and methods for monitoring and determining characteristics of wounds on a subject are disclosed. A monitoring device includes an imaging component and a computing device communicatively coupled to the imaging component. The imaging component includes a light emitting component that emits light at a calibrated wavelength, a laser emitting device, and an imaging device. The computing device directs the light emitting component to emit the light at the calibrated wavelength, directs the imaging component to cause the laser emitting device to emit a laser projection toward the wound, receives, from the imaging component, image data captured by the imaging device, determines, from the image data, the characteristics of the wound, and scores the wound based on the characteristics of the wound to obtain a wound score. The characteristics include one or more of a size of the wound, a type of tissue, and an amount of exudate.

Abstract: A method (1500) for deriving a mental state of a subject is disclosed. The method comprises receiving (1502) a bio-signal from the subject; calculating respective statistical variations of at least two physiological parameters derived from the bio-signal; determining (1504) an arousal level of the subject based on the calculated statistical variations of the at least two physiological parameters; deriving a time-domain heart rate variability signal from the bio-signal for calculating at least two heart rate variability parameters; determining (1506) a valence level of the subject based on the at least two heart rate variability parameters; and deriving (1508) the mental state from the arousal level and valence level. A related apparatus is also disclosed.

Abstract: A method (1500) for deriving a mental state of a subject is disclosed. The method comprises receiving (1502) a bio-signal from the subject; calculating respective statistical variations of at least two physiological parameters derived from the bio-signal; determining (1504) an arousal level of the subject based on the calculated statistical variations of the at least two physiological parameters; deriving a time-domain heart rate variability signal from the bio-signal for calculating at least two heart rate variability parameters; determining (1506) a valence level of the subject based on the at least two heart rate variability parameters; and deriving (1508) the mental state from the arousal level and valence level. A related apparatus is also disclosed.

Abstract: A patient support apparatus includes a bed including a frame. A mattress is supported by the frame. A respiratory therapy apparatus is supported by the frame. A pneumatic system is operable to inflate at least one bladder of the mattress and operable to deliver air to the respiratory therapy apparatus.

Abstract: An example method for assisting a patient to conduct a physical therapy session can include: presenting information about the physical therapy session on a display, the information including one or more actions to be performed by the patient; capturing one or more images of the patient as the patient performs the one or more actions; detecting, by a computing device, a safety risk related to one or more medical devices associated with the patient during the physical therapy session; and providing feedback regarding the safety risk. Other methods can include: detecting, by a computing device, using the one or more images, a level of effort from the patient during the physical therapy session; and modifying a future physical therapy session for the patient based upon the level of effort; or allowing the patient to compete with other patients during the physical therapy session based upon the level of effort.

Abstract: A method of determining respiratory rate from a photoplethysmograph signal includes filtering the photoplethysmograph signal to create a filtered photoplethysmograph signal. The method also includes detecting peaks and valleys in the filtered photoplethysmograph signal to extract predetermined features from the filtered photoplethysmograph signal. The method also includes obtaining variation waveforms from the predetermined features. The method also includes removing outliers from each of variation waveforms. The method also includes interpolating for the outliers removed from each of the variation waveforms to acquire a frequency estimation of each of the variation waveforms. The method also includes determining a respiratory rate based on the frequency estimation of each of the variation waveforms. The method also includes determining a weighted average of the respiratory rate the variation waveforms to determine an estimated respiratory rate.

Abstract: A patient support apparatus includes a frame and a mattress positioned on the frame. A respiratory therapy device is coupled to the frame. The respiratory therapy device includes a blower having an inlet and an outlet, a patient interface, and a valve including a valve member that is rotatable through a first angular displacement in a first direction from a first position to a second position. The outlet of the blower is coupled to the patient interface so that positive pressure is provided to a patient's airway via the patient interface when the valve member is in the first position. The inlet of the blower is coupled to the patient interface so that negative pressure is provided to the patient's airway via the patient interface when the valve member is in the second position.

Abstract: A respiratory acoustic analysis system for sensing and analyzing respiratory sounds of a patient may include a High Frequency Chest Wall Oscillation (HFCWO) vest, at least one sensor coupled with the HFCWO vest, and an algorithm stored in a processor for processing sensed data from the at least one acoustic sensor to provide processed data describing the respiratory sounds of the patient, in a form that can be used by a physician or other user.

Abstract: An example method for estimating a disease state for a patient can include: capturing physiological data including images from the patient over time; processing the physiological data to detect a variability; comparing the variability to a baseline or a range; and estimating the disease state for the patient based upon the comparing of the variability to the baseline or the limit.

Abstract: An example method for estimating a disease state for a patient can include: capturing physiological data including images from the patient over time; processing the physiological data to detect a variability; comparing the variability to a baseline or a range; and estimating the disease state for the patient based upon the comparing of the variability to the baseline or the limit.

Abstract: A system includes a controller with one or more processors and memory configured to store one or more sets of program instructions. The one or more processors are configured to execute the one or more sets of program instructions. The one or more sets of program instructions are configured to cause the one or more processors to apply filtering to a semiconductor wafer map; separate the filtered semiconductor wafer map into a plurality of dies; generate a set of die comparison statistics for the plurality of dies; generate at least one excursion map by applying at least one inspection threshold to the set of die comparison statistics; and detect at least one excursion within the at least one excursion map.

Abstract: Device and method for classifying the activity and/or counting steps of a user. A method for classifying the activity of a user can comprise measuring accelerometer data for a plurality of axes; identifying a most active one of the plurality of axes based on the accelerometer data; and classifying the activity of the user based on a signal amplitude of the accelerometer data for the most active axis and one or more threshold values.

Abstract: A stress level monitoring system includes a controller and a pulse oximeter electrically coupled to the controller. The pulse oximeter measures a photoplethysmograph signal. The controller determines a stress level of a patient from the photoplethysmograph signal.

Abstract: An example method for detecting a sleep apnea event can include: capturing a plurality of infrared images of an individual breathing; developing a spatial template based upon the infrared images, the spatial template defining at least a normal breathing pattern; using the spatial template to analyze further infrared images of the individual during sleep; and detecting a sleep apnea event using the spatial template and the further infrared images.

Abstract: Device and method for classifying the activity and/or counting steps of a user. A method for classifying the activity of a user can comprise measuring accelerometer data for a plurality of axes; identifying a most active one of the plurality of axes based on the accelerometer data; and classifying the activity of the user based on a signal amplitude of the accelerometer data for the most active axis and one or more threshold values.

Abstract: A system includes a controller with one or more processors and memory configured to store one or more sets of program instructions. The one or more processors are configured to execute the one or more sets of program instructions. The one or more sets of program instructions are configured to cause the one or more processors to apply filtering to a semiconductor wafer map; separate the filtered semiconductor wafer map into a plurality of dies; generate a set of die comparison statistics for the plurality of dies; generate at least one excursion map by applying at least one inspection threshold to the set of die comparison statistics; and detect at least one excursion within the at least one excursion map.