Abstract: The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.

Abstract: The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.

Abstract: Implementations described herein disclose a method of classifying oxygen level desaturation events. In one implementation, the method includes receiving input signal sequences, the input signals indicative of a physiological condition of a patient, generating an input sequence of oxygen saturation levels based on the input signal sequence, comparing the input sequence of oxygen saturation levels to a desaturation alarm threshold to determine a desaturation event, generating an input feature matrix based on at least one of the input signal sequences and the input sequence of oxygen saturation levels, and classifying based on the input feature matrix, using a neural network, the desaturation event being a severe desaturation event (SDE) or a non-severe desaturation event (non-SDE).

Abstract: Implementations described herein disclose a method of classifying oxygen level desaturation events. In one implementation, the method includes receiving input signal sequences, the input signals indicative of a physiological condition of a patient, generating an input sequence of oxygen saturation levels based on the input signal sequence, comparing the input sequence of oxygen saturation levels to a desaturation alarm threshold to determine a desaturation event, generating an input feature matrix based on at least one of the input signal sequences and the input sequence of oxygen saturation levels, and classifying based on the input feature matrix, using a neural network, the desaturation event being a severe desaturation event (SDE) or a non-severe desaturation event (non-SDE).

Abstract: The present technology relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient. In some embodiments, the systems, methods, and/or computer readable media can identify steep changes in depths. For example, the systems, methods, and/or computer readable media can identify large, inaccurate changes in depths that can occur at edge regions of a patient. In these and other embodiments, the systems, methods, and/or computer readable media can adjust the identified steep changes in depth before determining one or more patient respiratory parameters.

Abstract: The present technology relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient. In some embodiments, the systems, methods, and/or computer readable media can identify steep changes in depths. For example, the systems, methods, and/or computer readable media can identify large, inaccurate changes in depths that can occur at edge regions of a patient. In these and other embodiments, the systems, methods, and/or computer readable media can adjust the identified steep changes in depth before determining one or more patient respiratory parameters.

Abstract: The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.

Abstract: The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.

Abstract: Implementations described herein disclose a method of classifying oxygen level desaturation events. In one implementation, the method includes receiving input signal sequences, the input signals indicative of a physiological condition of a patient, generating an input sequence of oxygen saturation levels based on the input signal sequence, comparing the input sequence of oxygen saturation levels to a desaturation alarm threshold to determine a desaturation event, generating an input feature matrix based on at least one of the input signal sequences and the input sequence of oxygen saturation levels, and classifying based on the input feature matrix, using a neural network, the desaturation event being a severe desaturation event (SDE) or a non-severe desaturation event (non-SDE).

Abstract: Implementations described herein disclose a method of classifying oxygen level desaturation events. In one implementation, the method includes receiving input signal sequences, the input signals indicative of a physiological condition of a patient, generating an input sequence of oxygen saturation levels based on the input signal sequence, comparing the input sequence of oxygen saturation levels to a desaturation alarm threshold to determine a desaturation event, generating an input feature matrix based on at least one of the input signal sequences and the input sequence of oxygen saturation levels, and classifying based on the input feature matrix, using a neural network, the desaturation event being a severe desaturation event (SDE) or a non-severe desaturation event (non-SDE).

Abstract: The present technology relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient. In some embodiments, the systems, methods, and/or computer readable media can identify steep changes in depths. For example, the systems, methods, and/or computer readable media can identify large, inaccurate changes in depths that can occur at edge regions of a patient. In these and other embodiments, the systems, methods, and/or computer readable media can adjust the identified steep changes in depth before determining one or more patient respiratory parameters.

Abstract: The present technology relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient. In some embodiments, the systems, methods, and/or computer readable media can identify steep changes in depths. For example, the systems, methods, and/or computer readable media can identify large, inaccurate changes in depths that can occur at edge regions of a patient. In these and other embodiments, the systems, methods, and/or computer readable media can adjust the identified steep changes in depth before determining one or more patient respiratory parameters.

Abstract: According to an aspect, a method for determining an augmented vital sign, such as heart rate or heart rate variability, includes obtaining signals from a patient when the patient is both active and inactive. An activity signal is generated from the first signal, and a physiological signal is generated from the second signal. An activity weight factor is calculated from the activity signal, and a vital sign signal is calculated from the physiological signal. A mapping from the activity signal to the vital sign aids the determination of the vital sign through a motion period. The augmented vital sign is a result of the combination of first and second values, including the product of the activity weight factor and an activity derived vital sign, and the product of the vital sign signal and the activity weight factor less than one.

Abstract: Implementations described herein disclose a method of classifying oxygen level desaturation events. In one implementation, the method includes receiving input signal sequences, the input signals indicative of a physiological condition of a patient, generating an input sequence of oxygen saturation levels based on the input signal sequence, comparing the input sequence of oxygen saturation levels to a desaturation alarm threshold to determine a desaturation event, generating an input feature matrix based on at least one of the input signal sequences and the input sequence of oxygen saturation levels, and classifying based on the input feature matrix, using a neural network, the desaturation event being a severe desaturation event (SDE) or a non-severe desaturation event (non-SDE).

Abstract: The present technology relates to the field of medical monitoring. Patient monitoring systems and associated devices, methods, and computer readable media are described. In some embodiments, a patient monitoring system includes one or more sensors configured to capture first data related to a patient and a wearable wireless hub configured to receive the first data. In these and other embodiments, the patient monitoring system can include an image capture device configured to capture second data related to the patient. In these and still other embodiments, the patient monitoring system can determine one or more patient parameters based on the first and/or the second data. The patient monitoring system can monitor the one or more patent parameters and trigger an alert or alarm when a patient parameter abnormality is detected.

Abstract: The present technology relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient. In some embodiments, the systems, methods, and/or computer readable media can identify steep changes in depths. For example, the systems, methods, and/or computer readable media can identify large, inaccurate changes in depths that can occur at edge regions of a patient. In these and other embodiments, the systems, methods, and/or computer readable media can adjust the identified steep changes in depth before determining one or more patient respiratory parameters.

Abstract: The present invention relates to the field of medical monitoring, and, in particular, to non-contact detecting and monitoring of patient breathing. Systems, methods, and computer readable media are described for calculating a change in depth of a region of interest (ROI) on a patient and assigning one or more visual indicators to at least a portion of a graphic based on the calculated changes in depth and/or based on a tidal volume signal generated for the patient. In some embodiments, the systems, methods, and/or computer readable media can display the visual indicators overlaid onto at least the portion in real-time and/or can display the tidal volume signal in real-time. The systems, methods, and/or computer readable media can trigger an alert and/or an alarm when a breathing abnormality is detected.