Abstract: System and methods for personalizing an application include an application server for hosting an application that is executed on a wireless device, the server being configured to monitor usage of a user interface including an interaction between a user of the application and one or more user interface elements and present an updated user interface comprising one or more additional user-interface elements based on the usage.

Abstract: System and methods for personalizing an application include an application server for hosting an application that is executed on a wireless device, the server being configured to monitor usage of a user interface including an interaction between a user of the application and one or more user interface elements and present an updated user interface comprising one or more additional user-interface elements based on the usage.

Abstract: What is disclosed is a system and method for processing a video to extract a periodic signal which was captured by the video imaging device. One embodiment involves the following. First, a video of a subject in a scene is received. The video is acquired by a video imaging device. There is an underlying motion signal in the scene corresponding to cardiac or respiratory function. A time-series signal is generated for each pixel or for each group of pixels in a temporal direction across a plurality of image frames. Time-series signals of interest are selected. The selected time-series signals of interest are then processed to obtain a periodic signal corresponding to cardiac or respiratory function. The present method has a low computational complexity, is robust in the presence of noise, and finds its uses in applications requiring real-time motion quantification of a signal in a video.

Abstract: What is disclosed is a system and method for processing a video to extract a periodic signal which was captured by the video imaging device. One embodiment involves the following. First, a video of a subject in a scene is received. The video is acquired by a video imaging device. There is an underlying motion signal in the scene corresponding to cardiac or respiratory function. A time-series signal is generated for each pixel or for each group of pixels in a temporal direction across a plurality of image frames. Time-series signals of interest are selected. The selected time-series signals of interest are then processed to obtain a periodic signal corresponding to cardiac or respiratory function. The present method has a low computational complexity, is robust in the presence of noise, and finds its uses in applications requiring real-time motion quantification of a signal in a video.

Abstract: Embodiments of the present disclosure disclose a method and system for determining health condition of a subject. First step of the method comprises receiving, by a computing unit, a first oxygen saturation level and a second oxygen saturation level from at least two sensors placed on the subject. Second step of the method comprises determining cerebral extraction of oxygen using the first and second oxygen saturation levels. Third step of the method comprises comparing the cerebral extraction of oxygen with a threshold level. Fourth step of the method comprises identifying a mental fatigue level of the subject based on outcome of the comparison, wherein the mental fatigue level indicates the health condition of the subject.

Abstract: The present disclosure relates to a method and a system for authenticating a user. In one embodiment, one or more input and target data samples extracted from a plurality of physiological and movement signals of the user are processed to train one or more regression models. In real time authentication, the input and target data samples are extracted from the plurality of physiological and activity signals and mapped with trained regression models to determine a regression error. Based on the regression error, an appropriate authentication signal is then generated and transmitted to the user. Using dynamically selected multiple input and target data samples for user authentication increases the accuracy of authentication, thereby reducing possibilities of invalid authentication. Further, the power consumed by the sensors and computation load is reduced by dynamically powering up and powering down of the one or more sensors based on their usage during the authentication process.

Abstract: This disclosure relates generally to patient monitoring techniques, and more specifically to a method and a system to reduce false alarms generated by the patient monitoring system, the false alarms being associated with clinical condition of the patient. Disclosed herein is a patient monitoring method that includes monitoring one or more clinical parameters associated with condition of a patient, identifying a clinical condition based on deviation of the monitored one or more clinical parameters from corresponding one or more first predefined criteria, determining a status associated with one or more devices that monitor the deviated one or more clinical parameters, and generating a clinical alert based on the determined status not indicating an error by the one or more devices.

Abstract: This technology relates to a method and system for determining psychological disorder condition in a person and providing assistance to the person with the psychological disorder. One or more sensors are placed on the person to monitor the activities of the person. The one or more sensors provide sensor data associated with the monitored activities of the person to a computing unit. The computing unit detects the activities and identifies a recurring activity. For the recurring activity, the computing unit determines probability parameters and based on the probability parameters the probability of the psychological condition is determined. For providing assistance to the person with psychological disorder condition, the computing compares the activity with the disorder activities stored in the computing unit. If a match is found, then one or more indications are provided to the person to indicate that the activity has already been performed.

Abstract: The present disclosure relates to a method and a system for authenticating a user. In one embodiment, one or more input and target data samples extracted from a plurality of physiological and movement signals of the user are processed to train one or more regression models. In real time authentication, the input and target data samples are extracted from the plurality of physiological and activity signals and mapped with trained regression models to determine a regression error. Based on the regression error, an appropriate authentication signal is then generated and transmitted to the user. Using dynamically selected multiple input and target data samples for user authentication increases the accuracy of authentication, thereby reducing possibilities of invalid authentication. Further, the power consumed by the sensors and computation load is reduced by dynamically powering up and powering down of the one or more sensors based on their usage during the authentication process.

Abstract: Embodiments of the present disclosure disclose a method and system for determining health condition of a subject. First step of the method comprises receiving, by a computing unit, a first oxygen saturation level and a second oxygen saturation level from at least two sensors placed on the subject. Second step of the method comprises determining cerebral extraction of oxygen using the first and second oxygen saturation levels. Third step of the method comprises comparing the cerebral extraction of oxygen with a threshold level. Fourth step of the method comprises identifying a mental fatigue level of the subject based on outcome of the comparison, wherein the mental fatigue level indicates the health condition of the subject.

Abstract: Embodiments of the present disclosure provide a method of determining discharge readiness condition for a patient. The sensors are placed on patient to monitor the physiological condition of the patient and to transmit physiological data to computing device. The patient also provides non-physiological data using mobile device to computing device. The processor configured in computing unit assigns predefined weighted ratio to each of the physiological data and non-physiological data to generate weighted physiological and non-physiological data. The processor generates recovery score using the weighted physiological data and the non-physiological data and compares the recovery score with reference recovery score. The reference recovery score is personalized for each patient using weighted personal reference score and weighted EMR reference score.

Abstract: Embodiments of the present disclosure provide a method of improving breathing performance of a user using an electronic device. In an embodiment, the method of the present disclosure comprises creating a profile of a user by using personal information of the user, determining one or more threshold values corresponding to one or more levels based on the user profile, receiving values associated with at least parameter from respiratory blows of the user, determining breathing performance of the user by comparing the values with a corresponding threshold value, displaying the breathing performance of the user and adjusting the threshold values for successive levels based on the breathing performance.

Abstract: Embodiments of the present disclosure provide a method and a computing unit to monitor health condition of a subject. The computing unit receives physiological signals from a plurality of sensors placed on the subject. The computing unit detects a work-type based on the physiological signals received from the plurality of sensors and assigns a weight to each of the plurality of sensors based on the work-type. Thereafter, the computing unit generates a fatigue score using the physiological signals and the weight of the plurality of sensors. The fatigue score indicates the health condition of the subject.

Abstract: This disclosure relates generally to patient monitoring techniques, and more specifically to a method and a system to reduce false alarms generated by the patient monitoring system, the false alarms being associated with clinical condition of the patient. Disclosed herein is a patient monitoring method that includes monitoring one or more clinical parameters associated with condition of a patient, identifying a clinical condition based on deviation of the monitored one or more clinical parameters from corresponding one or more first predefined criteria, determining a status associated with one or more devices that monitor the deviated one or more clinical parameters, and generating a clinical alert based on the determined status not indicating an error by the one or more devices.

Abstract: A method, non-transitory computer readable medium, and a mobility program adherence device that obtains a mobility program for a patient including instructions for physical activities and an expected duration during a time period that the patient is to perform each of the physical activities. Data from an accelerometer of a patient monitoring device associated with the patient is received during at least a portion of the time period. The obtained data is processed to identify one or more of the physical activities performed by the patient. A duration the patient has performed the identified physical activities is determined. A graphical display including the determined duration the patient performed each of the physical activities during the at least a portion of the time period and an indication of the expected duration that the patient is to perform each of the physical activities during the time period is generated and output.