Abstract: A strap band including a flexible wire bus having electrodes and wires coupled with the electrodes is described. The wire bus may be encapsulated in the strap band by a molding process. The wire bus may determine electrode positions relative to each other and other structure coupled with the strap band. The strap band may be coupled with a device that includes circuitry that drives signals on to some of the electrodes and receives signals from non-driven electrodes. The electrode spacing and strap band dimensions may be selected to form a strap band that may accommodate a wide range of user body sizes for a target region the electrodes are positioned in contact with.

Abstract: Device-based activity classification using predictive feature analysis is described, including receiving a signal from a sensor coupled to a device, the sensor being configured to sense the signal over a time period, evaluating the signal to generate data, the data being further evaluated to select a classifier, invoking the classifier, the classifier being configured to evaluate a predictive feature, the predictive feature invoking an application configured to determine a state using a feature interpreter, and processing the data using the application and the feature interpreter to generate information associated with a biological state, the information being configured to display on an interface associated with the device.

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 configured to drive signals on some of the electrodes and receive signals from non-driven electrodes. The signal frequency applied to driven electrodes may be varied to increase/decrease signal penetration depth to sense different body structures positioned at different depths in the body portion. Different frequencies for different types of measurements may be selected to optimize sensing of bio-impedance, galvanic skin response, hear rate, respiration, heart rate variability, hydration, inflammation, stress, and arousal in sympathetic nervous system. A system clock frequency may be one of the frequencies used. A magnitude of the drive signal, a gain on the received signal or both, may be adjusted based on the frequency selected and/or to sense signals from the body structure(s) of interest.

Abstract: Device-based activity classification using predictive feature analysis is described, including receiving a signal from a sensor coupled to a device, the sensor being configured to detect the signal over a time period and to detect motion, evaluating the signal to generate data, the data being used to indicate motion, the data being further evaluated to select a classifier based on whether the motion is detected, activating another sensor coupled to the device, the another sensor being configured to detect another signal that is substantially different than the signal, the another signal being used to generate other data associated with whether the motion is detected, invoking the classifier, the classifier being configured to evaluate a predictive feature to identify a type associated with whether the motion is detected, the predictive feature invoking an application configured to determine the type and a state using a feature interpreter, and processing the data using the application and the feature interpre

Abstract: Device-based activity classification using predictive feature analysis is described, including evaluating an indicator associated with a predictive feature, identifying an application, using the name, to be performed, and invoking the application, the application being configured to interpret the indicator to determine an operation to perform at one or more levels of a protocol stack using data generated from evaluating a signal detected by a sensor, the sensor being coupled to a wearable device, and the application being configured to perform the operation using other data generated from evaluating another signal detected by another sensor, the another sensor being substantially different than the sensor.

Abstract: Embodiments relate generally to electrical and electronic hardware, computer software, wired and wireless network communications, and computing devices, and, in particular, 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 includes a selectably opaque surface configured to emit arrangements of light to form a display, and a touch-sensitive I/O control circuit coupled to the selectably opaque surface to detect a capacitance value as an input signal to modify the display. Also, the wearable device can include one or more straps coupled to a wearable pod, at least one of the one or more straps including electrodes for sensing a physiological characteristic. A display controller can be configured to display a representation as a function of a value of the physiological characteristic via the selectably opaque surface.

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 configured to drive signals on some of the 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: A strap band including a flexible wire bus having electrodes and wires coupled with the electrodes is described. The wire bus may be include in a strap band formed by molding an inner strap, mounting the wire bus in the inner strap, and injection molding an outer strap over the inner strap and wire bus to form a strap band. The electrodes may be positioned on the inner strap to accommodate a target range of a body portion the strap band may be worn on. A material of the strap band and a material the wire bus may be selected to allow a low coefficient of friction between the wire bus and strap band so that loads applied to the strap band may not be coupled with the wire bus or cause damage to wires due to pull and/or torsional load forces applied to the strap band.

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 configured to drive signals on some of the electrodes and receive signals from non-driven electrodes. The electrode spacing and strap band dimensions may be selected to form a strap band that may accommodate a wide range of user body sizes for a target region the electrodes are positioned in contact with. The electrodes may be composite electrodes having multiple layers of conductive material in which an outermost layer is made from a material operative as an ion exchange layer. The ion exchange layer in contact with an electrolyte layer of a body portion may be operative to reduce motion artifact induced impedance and increase a signal to noise ratio for bio-impedance circuitry or other biometric circuitry coupled with the electrodes.

Abstract: Device-based activity classification using predictive feature analysis is described, including receiving a signal from a sensor configured to measure a heart rate coupled to a device, the sensor being configured to sense the signal over a time period, evaluating the signal to generate data associated with the heart rate, the data being further evaluated to select a classifier, invoking the classifier, the classifier being configured to evaluate the data to identify a predictive feature, the predictive feature invoking an application configured to determine a state using a feature interpreter, the application also being configured to evaluate other data from another signal, the signal being configured to detect a respiration rate, and processing the data and the other data using the application and the feature interpreter to generate information associated with sleep, the information being configured to display on an interface associated with the device.

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 method includes receiving an amplified signal including a portion of the physiological-related signal component including data representing a physiological characteristic, the amplified signal being derived from bioimpedance signal based on an impedance value of a tissue, and identifying a magnitude of a portion of the physiological-related signal component. Also, the method can compare the magnitude of the portion against another magnitude of a data model (e.g., in a time-domain) to form a matched value.

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: Techniques for presenting and recommending media content based on media content responses are described. Disclosed are techniques for receiving data associated with a portion of media content, receiving a set of sensor data from one or more sensors coupled to a wearable device, comparing the set of sensor data to one or more templates to determine a response to the portion of media content, and causing presentation of information associated with the response at a display. The portion of media content may be configured to be presented at the display. The set of sensor data may include galvanic skin response (GSR) data.

Abstract: Techniques for selecting and presenting media programs and user states are described. Disclosed are techniques for receiving data representing a distance between a display and a wearable device is below a threshold, receiving data representing a user state, and determining that a condition is satisfied based on the user state, the condition being associated with a type of media program. Data representing a media program may be selected based on the type of media program. Presentation of the data representing the media program and information associated with the user state at the display may be caused.

Abstract: Embodiments relate generally to electrical/electronic hardware, computer software, wired and wireless network communications, portable, wearable, and stationary media devices. RF transceivers and/or audio system in each media device may be used to wirelessly communicate between media devices and allow configuration and other data to be wirelessly transmitted from one media device to another media device. The proximity detection system may be configured to detect a presence of a user or multiple users and upon detecting presence, access content on a user device, and record the content while also playing back the content on the media device. One or more user devices in proximity of the media device post detection may wirelessly communicate with the media device and the media device may orchestrate handling of content from those devices or from a wirelessly accessible location such as the Cloud or Internet.