Abstract: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: In one embodiment, a method for creating a blood oxygen saturation (SpO2) value, the method comprises receiving one or more photoplethysmography (PPG) signals for SpO2 detection from one or more PPG sensors; receiving one or more PPG signals for characterizing a heart rate from the one or more PPG sensors; using the one or more PPG signals for SpO2 detection, forming one or more SpO2 datasets wherein the SpO2 datasets respectively comprise one or more noise components; removing the one or more noise components from the one or more SpO2 datasets that are inconsistent with a feature of the one or more PPG signals characterizing the heart rate to produce one or more filtered SpO2 datasets; and using the one or more filtered SpO2 datasets, creating and storing the SpO2.

Abstract: In one embodiment, a method for creating a blood oxygen saturation (SpO2) value, the method comprises receiving one or more photoplethysmography (PPG) signals for SpO2 detection from one or more PPG sensors; receiving one or more PPG signals for characterizing a heart rate from the one or more PPG sensors; using the one or more PPG signals for SpO2 detection, forming one or more SpO2 datasets wherein the SpO2 datasets respectively comprise one or more noise components; removing the one or more noise components from the one or more SpO2 datasets that are inconsistent with a feature of the one or more PPG signals characterizing the heart rate to produce one or more filtered SpO2 datasets; and using the one or more filtered SpO2 datasets, creating and storing the SpO2.

Abstract: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: In one embodiment, a method for creating a blood oxygen saturation (SpO2) value, the method comprises receiving one or more photoplethysmography (PPG) signals for SpO2 detection from one or more PPG sensors; receiving one or more PPG signals for characterizing a heart rate from the one or more PPG sensors; using the one or more PPG signals for SpO2 detection, forming one or more SpO2 datasets wherein the SpO2 datasets respectively comprise one or more noise components; removing the one or more noise components from the one or more SpO2 datasets that are inconsistent with a feature of the one or more PPG signals characterizing the heart rate to produce one or more filtered SpO2 datasets; and using the one or more filtered SpO2 datasets, creating and storing the SpO2.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: Some embodiments relate to a device, method, and/or computer-readable medium storing processor-executable process steps for processing a photoplethysmographic (“PPG”) signal in a monitoring device that monitors a property of blood flow. In some embodiments, the processing includes obtaining a first digital signal representing a detected light signal having a non-pulsatile (e.g., DC) component and a pulsatile component (e.g., AC). An offset control signal is generated from an estimation of the non-pulsatile component and a second digital signal is generated after subtracting the offset control signal from the detected light signal and applying a gain to the subtracted signal. A reconstructed signal is generated that is calculated from the gain and one or more of (i) the first digital signal, and (ii) the second digital signal and the offset control signal.

Abstract: Approaches to determining a sleep fitness score for a user are provided, such as may be based upon monitored breathing disturbances of a user. The system receives user state data generated over a time period by a combination of sensors provided via a wearable tracker associated with the user. A system can use this information to calculate a sleep fitness score, breathing disturbance score, or other such value. The system can classify every minute within the time period as either normal or atypical, for example, and may provide such information for presentation to the user.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: Some embodiments relate to a device, method, and/or computer-readable medium storing processor-executable process steps for processing a photoplethysmographic (“PPG”) signal in a monitoring device that monitors a property of blood flow. In some embodiments, the processing includes obtaining a first digital signal representing a detected light signal having a non-pulsatile (e.g., DC) component and a pulsatile component (e.g., AC). An offset control signal is generated from an estimation of the non-pulsatile component and a second digital signal is generated after subtracting the offset control signal from the detected light signal and applying a gain to the subtracted signal. A reconstructed signal is generated that is calculated from the gain and one or more of (i) the first digital signal, and (ii) the second digital signal and the offset control signal.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: The disclosure relates to methods, devices, and systems to identify a user of a wearable fitness monitor using data obtained using the wearable fitness monitor. Data obtained from motion sensors of the wearable fitness monitor and data obtained from heartbeat waveform sensors of the wearable fitness monitor may be used to identify the user.

Abstract: Processing a photoplethysmographic (“PPG”) signal in a monitoring device that monitors a property of blood flow. A switching component is operated to select between at least a first light source when the mode selection signal specifies the first mode of operation and a second light source when a mode selection signal specifies the second mode of operation. A selected one of the first light source and the second light source, as selected by the switching component, is then operated. A first digital signal representing a detected light signal from the selected light source is obtained, and a second digital signal is generated from the first digital signal based at least in part on the selected mode of operation. The second digital signal is provided to a processor for use by the processor in measuring a property of blood flow.