Abstract: A method and system for determining a signal quality metric of a cardiovascular time series utilizing a wireless sensor device are disclosed. In a first aspect, the method comprises determining subsequent values of the cardiovascular time series and comparing the determined subsequent values to a threshold value. 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 subsequent values of the cardiovascular time series and compare the determined subsequent values to a threshold value.

Abstract: 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.

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 determining a signal quality metric of a cardiovascular time series utilizing a wireless sensor device are disclosed. In a first aspect, the method comprises determining subsequent values of the cardiovascular time series and comparing the determined subsequent values to a threshold value. 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 subsequent values of the cardiovascular time series and compare the determined subsequent values to a threshold value.

Abstract: An example of a digital artery blood pressure monitor may include a tactile sensor array disposed on an inner surface of a cuff, the tactile sensor array including a plurality of capacitive sensors to detect pressure changes within a digital artery of a finger due to blood flow, where the pressure changes cause changes to capacitance values of one or more capacitive sensors of the tactile sensor array, and control circuitry coupled to the tactile sensor array to receive the capacitance values from the tactile sensor array, and determine a blood pressure based on the capacitance values.

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 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.

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 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.

Abstract: A transmitter including a transmit section and a frame formatter. The transmit section is to generate a stream of data to be transmitted using a plurality of antennas and separate the stream of data into a plurality of substreams corresponding to respective ones of the plurality of antennas. The frame formatter is to form respective frames of data from the plurality of substreams. Each of the frames of data includes a short preamble including short training symbols, a long preamble including long training symbols, and a signal field indicating a quantity of the plurality of antennas. The transmit section is further to transmit the frames of data using respective ones of the plurality of antennas.

Abstract: A method and system for measuring respiratory rate are disclosed. In a first aspect, the method comprises measuring at least one respiration signal and filtering the respiration signal using a lowpass filter. The method includes peak-picking the respiration signal to determine the respiratory rate and determining a quality metric of the respiratory rate. 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 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 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 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.

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 system for measuring respiratory rate are disclosed. In a first aspect, the method comprises measuring at least one respiration signal and filtering the respiration signal using a lowpass filter. The method includes peak-picking the respiration signal to determine the respiratory rate and determining a quality metric of the respiratory rate. 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 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: The present invention generally relates to blood pressure monitoring. In some embodiments, methods and devices of measuring a mean arterial pressure are provided and/or monitoring blood pressure changes. A wrist-worn device may include a plurality of sensors backed by a plurality of actuators. Subsets of the plurality of sensors may be selectively actuateable against a wrist of a user using one or more of the plurality of actuators. A preferred sensor and location may be identified based on pressure signals received from each of the sensors. In some embodiments, devices may use a fluid bladder coupled with piezoelectric film sensors. A fluid bladder pressure sensor may be used to calibrate the piezoelectric film signal to provide a static and dynamic pressure reading. In yet another embodiment, a mean arterial pressure may be calculated by processing a swept pressure signal obtained as a sensor is swept through different heights.

Abstract: Wrist-worn devices and related methods measure a pulse transit time non-invasively and calculate a blood pressure value using the pulse transit time. A wrist-worn device include a wrist-worn elongate band, at least four EKG or ICG electrodes coupled to the wrist-worn device for detecting a ventricular ejection of a heart, a photo-plethysmogram (PPG) sensor coupled to the wrist-worn device for detecting arrival of a blood pressure pulse at the user's wrist, and a controller configured to calculate a pulse transit time (PTT) for the blood pressure pulse. The controller calculates one or more blood pressure values for the user based on the PTT.

Abstract: The present invention provides non-invasive devices, methods, and systems for determining a pressure of blood within a cardiovascular system of a user, the cardiovascular system including a heart and the user having a wrist covered by skin. More particularly, the present invention discloses a variety of wrist-worn devices having a variety of sensors configured to non-invasively engage the skin on the wrist of the user for sensing a variety of user signals from the cardiovascular system of the user. Generally, approaches disclosed herein may passively track blood pressure values without any interaction required on the part of the user or may allow for on demand or point measurements of blood pressure values by having a user actively interact with the sensors of the wrist-worn device.