Abstract:
The present invention relates to advanced signal processing methods including digital wavelet transformation to analyze heart-related electronic signals and extract features that can accurately identify various states of the cardiovascular system. The invention may be utilized to estimate the extent of blood volume loss, distinguish blood volume loss from physiological activities associated with exercise, and predict the presence and extent of cardiovascular disease in general.
Abstract:
Embodiments relate generally to a wearable device implementing a touch-sensitive interface in a metal pod cover and/or bioimpedance sensing to determine physiological characteristics, such as heart rate. According to an embodiment, a wearable device and method includes determining a drive current signal magnitude for a bioimpedance signal to capture data representing a physiological-related component, and selecting the drive current signal magnitude as a function of an impedance of a tissue. Further, the method can include driving the bioimpedance signal to that are configured to convey the bioimpedance signal to the tissue. Also, the method can receive the sensor signal from the tissue, adjust a gain for an amplifier, and apply the gain to data representing the physiological-related component. The method can include generating an amplified signal to include a portion of the physiological-related signal component that includes data representing a physiological characteristic.
Abstract:
One or more wearable devices may measure real-time blood pressure in a body using signals from multiple sensors including but not limited to a multi-axis accelerometer, a bioimpedance (BI) sensor, a capacitive touch sensor, an electrocardiography sensor (ECG), a ballistocardiograph sensor (BCG), a photoplethysmogram (PPG), a pulse oximetery sensor, and a phonocardiograph sensor (PCG), for example. Accelerometry data (e.g., from a multi-axis accelerometer or BCG sensor) may be used to derive effects of acceleration (e.g., gravity) on changes in blood pressure (e.g., due to changes in blood volume as measured using BI signals). The accelerometry data may be used to determine a baseline value for BI voltage signals that are indicative of diastolic and systolic blood pressure (e.g., in mmHg).
Abstract:
A strap band including a flexible wire bus having electrodes and wires coupled with the electrodes is described. The strap band may be coupled with a device that includes circuitry to drive signals on electrodes and receive signals from pickup electrodes. Driven electrodes are coupled with drive signals at different frequencies that may be varied to increase or decrease signal penetration depth to sense different body structures positioned at different depths in a body portion be sensed. Different frequencies for different types of measurements may be selected to optimize sensing different biometric parameters, such as bio-impedance, galvanic skin response, hear rate, respiration, heart rate variability, hydration, inflammation, stress, and arousal in sympathetic nervous system at different depths (e.g., layers or strata) in the body portion, for example. A first set of driven/pickup electrodes may sense different biometric parameters than a second set of driven/pickup electrodes.
Abstract:
The present invention relates to advanced signal processing methods including digital wavelet transformation to analyze heart-related electronic signals and extract features that can accurately identify various states of the cardiovascular system. The invention may be utilized to estimate the extent of blood volume loss, distinguish blood volume loss from physiological activities associated with exercise, and predict the presence and extent of cardiovascular disease in general.
Abstract:
One or more wearable devices may measure real-time blood pressure in a body using signals from multiple sensors including but not limited to a multi-axis accelerometer, a bioimpedance (BI) sensor, a capacitive touch sensor, an electrocardiography sensor (ECG), a ballistocardiograph sensor (BCG), a photoplethysmogram (PPG), a pulse oximetery sensor, and a phonocardiograph sensor (PCG), for example. Accelerometry data (e.g., from a multi-axis accelerometer or BCG sensor) may be used to derive effects of acceleration (e.g., gravity) on changes in blood pressure (e.g., due to changes in blood volume as measured using BI signals). The accelerometry data may be used to determine a baseline value for BI voltage signals that are indicative of diastolic and systolic blood pressure (e.g., in mmHg).
Abstract:
A strap band including a flexible wire bus having electrodes and wires coupled with the electrodes is described. The strap band may be coupled with a device that includes circuitry to drive signals on electrodes and receive signals from pickup electrodes. Driven electrodes are coupled with drive signals at different frequencies that may be varied to increase or decrease signal penetration depth to sense different body structures positioned at different depths in a body portion be sensed. Different frequencies for different types of measurements may be selected to optimize sensing different biometric parameters, such as bio-impedance, galvanic skin response, hear rate, respiration, heart rate variability, hydration, inflammation, stress, and arousal in sympathetic nervous system at different depths (e.g., layers or strata) in the body portion, for example. A first set of driven/pickup electrodes may sense different biometric parameters than a second set of driven/pickup electrodes.
Abstract:
Embodiments relate generally to a wearable device implementing a touch-sensitive interface in a metal pod cover and/or bioimpedance sensing to determine physiological characteristics, such as heart rate. According to an embodiment, a wearable device and method includes determining a drive current signal magnitude for a bioimpedance signal to capture data representing a physiological-related component, and selecting the drive current signal magnitude as a function of an impedance of a tissue. Further, the method can include driving the bioimpedance signal to that are configured to convey the bioimpedance signal to the tissue. Also, the method can receive the sensor signal from the tissue, adjust a gain for an amplifier, and apply the gain to data representing the physiological-related component. The method can include generating an amplified signal to include a portion of the physiological-related signal component that includes data representing a physiological characteristic.