Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method and system for low-distortion denoising of an ECG signal are disclosed. The method comprises determining at least one beat of the ECG signal for denoising using a beat selection logic and denoising the at least one beat using at least one ensemble averaging filter. The system includes a sensor to detect the ECG signal, a processor coupled to the sensor, wherein the processor includes a beat selection logic unit, 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 at least one beat of the ECG signal for denoising using a beat selection logic and to denoise the at least one beat using at least one ensemble averaging filter.

Abstract: A method and wireless sensor device for determining a time period a person is in bed. In one aspect, a method includes utilizing a wireless sensor device to obtain a plurality of acceleration samples in relation to at least one axis associated with a person's body over a predetermined time window. The method also includes calculating a polar angle for each acceleration sample within the predetermined time window. The method also includes calculating a fraction of an amount of time within the predetermined time window that the polar angle is greater than an angle threshold that indicates that the person is lying down, where if the fraction is greater than a predetermined threshold, the predetermined time window is marked as a period the person is lying down.

Abstract: 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.

Abstract: 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.

Abstract: Example systems and methods related to chatbot skills are described. In one implementation, a system initiates a session to create a new chatbot. The system receives a selection of a first chatbot skill associated with the new chatbot and a selection of a second chatbot skill associated with the new chatbot, where the first chatbot skill is different from the second chatbot skill. The system creates the new chatbot by importing the first chatbot skill and the second chatbot skill into the new chatbot.

Abstract: A finger-wearable blood pressure monitor device includes a cuff, a tactile sensor array, and control circuitry. The tactile sensor array is disposed on or adjacent to an inward facing surface of the cuff The tactile sensor array includes a plurality of sensors. The control circuitry is coupled to the tactile sensor array and includes logic that when executed by the control circuitry causes the finger-wearable blood pressure monitoring device to perform operations. The operations include monitoring, over a first time period, a pressure applied to each of the plurality of sensors by a digital artery of a finger. The operations also include generating a plurality of tactile waveforms in response to monitoring the pressure. Each of the plurality of tactile waveforms corresponds to the pressure applied to a respective one of the plurality of sensors over the first time period. The operations further include estimating blood pressure based, at least in part, on the plurality of tactile waveforms.

Abstract: Example natural language processing systems and methods are described. In one implementation, a system receives a request from a remote system, where the request includes text data or voice data. The system analyzes the text data or voice data to determine an intent associated with the request. Based on the intent associated with the request, the system generates a response to the request and communicates the response to the remote system.

Abstract: A method and system for low-distortion denoising of an ECG signal are disclosed. The method comprises determining at least one beat of the ECG signal for denoising using a beat selection logic and denoising the at least one beat using at least one ensemble averaging filter. The system includes a sensor to detect the ECG signal, a processor coupled to the sensor, wherein the processor includes a beat selection logic unit, 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 at least one beat of the ECG signal for denoising using a beat selection logic and to denoise the at least one beat using at least one ensemble averaging filter.

Abstract: 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.

Abstract: 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.

Abstract: A method for determining blood pressure is disclosed. The method comprises determining a plurality of heart sounds using a microphone of a handheld device and determining a pulse wave using a camera of the handheld device. The method includes determining an ejection time (ET), a vascular transit time (VTT), and a heart rate from any of the plurality of heart sounds and the pulse wave. The method includes performing regression analysis on received user-specific data, the ET, the VTT, and the heart rate to determine the blood pressure.

Abstract: A method and wireless sensor device for determining step count is disclosed. In one aspect, a method includes receiving sensor data. The method 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 and determining step count based on classification of the activity.

Abstract: A method and system for filtering a detected ECG signal are disclosed. In a first aspect, the method comprises filtering the detected ECG signal using a plurality of digital filters. The method includes adaptively selecting one of the plurality of digital filters to maintain a minimum signal-to-noise ratio (SNR). 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.

Abstract: A method and system for determining psychological acute stress are disclosed. In a first aspect, the method comprises detecting a physiological signal using a wireless sensor device, determining a stress feature using a normalized heart rate and a plurality of heart rate variability (HRV) features, wherein the normalized heart rate and the plurality of heart rate variability features are calculated using the detected physiological signal, and determining a stress level using the stress feature to determine the psychological acute stress. In a second aspect, the system comprises a wireless sensor device that 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 wireless sensor device to carry out the steps of the method.