Vital Connect, Inc. Patent applications |
Patent application number | Title | Published |
20150190086 | AUTOMATED SLEEP STAGING USING WEARABLE SENSORS - A method and system for automated sleep staging are disclosed. The method comprises determining at least one physiological signal during a predetermined time period, extracting at least one feature from the at least one physiological signal, and classifying the at least one feature using a machine learning classifier to output at least one sleep stage. The system includes a sensor to determine at least one physiological signal during a predetermined time period, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to extract at least one feature from the at least one physiological signal and to classify the at least one feature using a machine learning classifier unit to output at least one sleep stage. | 07-09-2015 |
20150045628 | MULTI-LAYER PATCH FOR WIRELESS SENSOR DEVICES - A wireless sensor device is disclosed. In a first aspect, the wireless sensor device comprises a housing unit and a patch coupled to the housing unit, wherein the patch includes a removable adhesive and is repositionable. In a second aspect, the wireless sensor device comprises a housing unit and a patch coupled to the housing unit, wherein the patch includes a plurality of removable adhesive layers that are each composed of removable medical grade silicone pressure sensitive adhesive (PSA). | 02-12-2015 |
20150020571 | FALL DETECTION USING MACHINE LEARNING - A method and system for fall detection using machine learning are disclosed. The method comprises detecting at least one signal by a wireless sensor device and calculating a plurality of features from the at least one detected signal. The method includes training a machine learning unit of the wireless sensor device using the features to create a fall classification and a non-fall classification for the fall detection. The system includes a sensor to detect at least one signal, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to calculate a plurality of features from the at least one detected signal and to train a machine learning unit of the wireless sensor device using the features to create a fall classification and a non-fall classification for the fall detection. | 01-22-2015 |
20140276127 | CONTEXTUAL HEART RATE MONITORING - A method and system for contextual heart rate monitoring are disclosed. In a first aspect, the method comprises calculating a heart rate using a detected ECG signal and detecting an activity level. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to calculate a heart rate using a detected ECG signal and to detect an activity level. | 09-18-2014 |
20140275932 | DISPOSABLE BIOMETRIC PATCH DEVICE - A system and method for health monitoring are disclosed. The system includes a patch device and an electronic module coupled to the patch device. The method includes providing a patch device, coupling an electronic module to the patch device to provide a wearable device, and monitoring health of a user using the wearable device. | 09-18-2014 |
20140200474 | DETECTION OF SLEEP APNEA USING RESPIRATORY SIGNALS - A method and system for sleep apnea detection are disclosed. The method comprises detecting at least one respiratory signal and utilizing a detection algorithm to automatically detect at least one sleep apnea event from the at least one respiratory signal. The system includes a sensor to determine at least one respiratory signal, a processor coupled to the sensor, and a memory device coupled to the processor, wherein the memory device includes a detection algorithm and an application that, when executed by the processor, causes the processor to utilize the detection algorithm to automatically determine at least one sleep apnea event from the at least one respiratory signal. | 07-17-2014 |
20140128778 | DETERMINING BODY POSTURES AND ACTIVITIES - A method and wireless sensor device for determining body postures and activities. In one aspect, a method includes receiving sensor data. The method also includes detecting and classifying a body transition of a body based on the sensor data. The method also includes detecting if there is activity of the body based on the sensor data. If there is activity, the method also includes classifying the activity. If there is no activity, the method also includes classifying a rest position of the body based on the sensor data and based on a previous body transition. | 05-08-2014 |
20140121543 | MEASURING PSYCHOLOGICAL STRESS FROM CARDIOVASCULAR AND ACTIVITY SIGNALS - A method and system for measuring psychological stress disclosed. In a first aspect, the method comprises determining R-R intervals from an electrocardiogram (ECG) to calculate a standard deviation of the R-R intervals (SDNN) and determining a stress feature (SF) using the SDNN. In response to reaching a threshold, the method includes performing adaptation to update a probability mass function (PMF). The method includes determining a stress level (SL) using the SF and the updated PMF to continuously measure the psychological stress. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to carry out the steps of the method. | 05-01-2014 |
20140073982 | R-R INTERVAL MEASUREMENT USING MULTI-RATE ECG PROCESSING - A method and system for R-R interval measurement of a user are disclosed. In a first aspect, the method comprises detecting an electrocardiogram (ECG) signal of the user. The method includes performing QRS peak detection on the ECG signal to obtain a low resolution peak and searching near the low resolution peak for a high resolution peak. The method includes calculating the R-R interval measurement based upon the high resolution peak. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to carry out the steps of the method. | 03-13-2014 |
20140066795 | CONTINUOUS ASSESMENT OF ECG SIGNAL QUALITY - A method and system for assessing an electrocardiogram (ECG) signal quality are disclosed. In a first aspect, the method comprises determining a Kurtosis calculation of the ECG signal and determining whether the Kurtosis calculation satisfies a first threshold to continuously assess the ECG signal quality. In a second aspect, the system comprises a wireless sensor device coupled to a user via at least one electrode, wherein the wireless sensor device includes a processor and a memory device coupled to the processor, wherein the memory device stores an application which, when executed by the processor, causes the processor to determine a Kurtosis calculation of the ECG signal and to determine whether the Kurtosis calculation satisfies a first threshold to continuously assess the ECG signal quality. | 03-06-2014 |
20140019080 | CALIBRATION OF A CHEST-MOUNTED WIRELESS SENSOR DEVICE FOR POSTURE AND ACTIVITY DETECTION - A method and system for calibrating a wireless sensor device are disclosed. In a first aspect, the method comprises determining a vertical calibration vector and determining a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to determine a vertical calibration vector and to determine a rotation matrix using the vertical calibration vector to line up native axes of the wireless sensor device with body axes. | 01-16-2014 |
20140015687 | POSTURE CALIBRATION FOR ACTIVITY MONITORING - A method and system for activity monitoring of a user are disclosed. In a first aspect, the method comprises calibrating posture by the user to determine a calibration vector. The method includes validating the calibration vector by comparing an anteroposterior axis to a threshold, wherein activity of the user is monitored using the validated calibration vector. In a second aspect, a wireless sensor device comprises a processor and a memory device coupled to the processor, wherein the memory device includes an application that, when executed by the processor, causes the processor to receive a posture calibration request from the user and to determine a calibration vector based on the received request. The application, when executed by the processor, further causes the processor to validate the calibration vector by comparing an anteroposterior axis to a threshold, wherein activity of the user is monitored using the validated calibration vector. | 01-16-2014 |
20130120147 | FALL DETECTION USING SENSOR FUSION - A method and system for fall detection using sensor fusion are disclosed. In a first aspect, the method comprises in response to any of first and second acceleration magnitude thresholds being satisfied, determining whether a height difference before and after impact of a fall satisfies a threshold and whether an angle threshold between an acceleration vector and a calibration vector is satisfied. In a second aspect, the system comprises a processing system and an application coupled to the processing system, wherein the application carries out the steps of the method. | 05-16-2013 |
20130099937 | SYSTEM AND METHOD FOR RELIABLE AND SCALABLE HEALTH MONITORING - A health-monitoring system and method are disclosed. The health-monitoring system and method comprise a sensory system and a sensory to front-end communication (SFCM) protocol coupled to the sensory system. The health-monitoring system and method include a front-end system coupled to the sensory system and a front-end to back-end communication (FBCM) protocol coupled to the front-end system. The health-monitoring system and method include a back-end system. The SFCM protocol communicates with the front-end system using a first state awareness link and the FBCM protocol communicates with the back-end system using a second state awareness link. | 04-25-2013 |