Abstract:
Embodiments relate generally to electrical and electronic hardware, computer software, wired and wireless network communications, and wearable computing devices in capturing and deriving physiological characteristic data. More specifically, disclosed are one or more electrodes and methods to determine physiological characteristics using a wearable device (or carried device) and one or more sensors that can be subject to motion. In one embodiment, a method includes receiving a sensor signal during one or more portions of a time interval in which the wearable device is in motion, and receiving a motion sensor signal. The method includes decomposing at a processor the sensor signal to determine physiological signal components. An analysis of the physiological signal components can yield a physiological characteristic, whereby a physiological characteristic signal that includes data representing the physiological characteristic can be generated during at least one of the one or more portions of the time interval.
Abstract:
Embodiments of the present application relate generally to personal electronics, portable electronics, wearable electronics, and more specifically to wirelessly enabled devices that include a haptic interface and are configured to wirelessly communicate with one another to synchronize body motion or other user actions based on haptic prompts generated by a sensor system in one or more of the wirelessly enabled devices. Each wirelessly enabled device may include at least one radio configured to transmit, receive or both, RF signals encoded with motion data operative to generate sensory outputs from the haptic interface of one or more of the wirelessly enabled devices. At least one of the wirelessly enabled devices may be configured as a leader device and one or more other wirelessly enabled devices may be configured as a follower device. One or more wirelessly enabled devices may be wirelessly linked to a wireless media device that generates motion data.
Abstract:
Various embodiments relate generally to electrical and electronic hardware, computer software, wired and wireless network communications, and wearable computing and audio devices for monitoring health and wellness. More specifically, disclosed are an apparatus and a method for processing signals representing physiological characteristics sensed from tissue at or adjacent an ear of an organism. In one or more embodiments, a wearable device includes a sensor terminal and a physiological sensor coupled to the sensor terminal to sense one or more signals originating at the sensor terminal. The wearable device may also include a radio frequency (“RF”) communications interface. Also, the wearable device can include a processor configured to cause generation of data representing a physiological characteristic of the organism.
Abstract:
Techniques associated with a combination speaker and light source powered using a light socket are described, including a housing comprising a plate coupled to a substantially hemispherical enclosure, a platform configured to couple a light source to a terminal configured to receive a light control signal, the light control signal configured to modify a light characteristic, a speaker coupled to the housing and configured to project audio in a direction, a light socket connector coupled to the housing and configured to provide power to the speaker and the light source when the light socket connector is coupled with a light socket, an acoustic sensor disposed on a surface of the housing, and a light sensor located within the housing, the light sensor facing away from the light source.
Abstract:
Techniques associated with a combination speaker and light source (“speaker-light device”) responsive to states of an organism based on sensor data are described, including generating motion sensor data in response to a movement captured using a motion sensor, deriving movement data using a motion analysis module configured to determine the movement to be associated with one or more of a gesture, an identity, and an activity, using the motion sensor data, generating acoustic sensor data in response to sound captured using an acoustic sensor, deriving audio data using a noise removal module configured to subtract a noise signal from the acoustic sensor data, detecting a radio frequency signal using a communication facility, the radio frequency being associated with a personal device, obtaining state data from the personal device, and determining a desired light characteristic using the state data and one or both of the movement data and the audio data.
Abstract:
Embodiments relate generally to electrical and electronic hardware, computer software, wired and wireless network communications, and wearable computing devices, audio devices, and communication devices for facilitating the presentation of personal audio. More specifically, disclosed are an apparatus and method to form directional audio personal to a user in a non-occluded manner. In one embodiment, a personal audio and communication devices can include a first directional speaker disposed at a first mounting region of a first support member. The first support member is configured to position the first directional speaker adjacent a first ear in substantial alignment with the first ear. Also included is a second directional speaker disposed at a second mounting region of a second support member. The second support member is configured to position the second directional speaker adjacent a second ear in substantial alignment with the second ear.
Abstract:
Techniques for motion profiles in wearable devices are described, including receiving motion-related data, user-related data, and environmental-related data from one or more sensors coupled to one or more wearable devices, forming a motion profile using the motion-related data, determining an activity using the motion profile, the user-related data, and the environmental-related data, the activity comprising sleep, and setting a mode of operation of one of the one or more wearable devices to a sleep mode, the mode of operation being configured to be set to one of the sleep mode and another mode. A sampling rate of one of the one or more sensors in the sleep mode may be set to be lower than the sampling rate of the one of the one or more sensors in the another mode.
Abstract:
Embodiments of the invention relates generally to electrical and electronic hardware, computer software, wired and wireless network communications, and computing devices, and more specifically to structures and techniques for managing power generation, power consumption, and other power-related functions in a data-capable strapband. Embodiments relate to a band including sensors, a controller coupled to the sensors, an energy storage device, a connector configured to receive power and control signals, and a power manager. The power manager includes at least a transitory power manager configured to manage power consumption of the band during a first power mode and a second mode. The band can be configured as a wearable communications device and sensor platform.
Abstract:
Techniques for device control using sensory input are described, including receiving input from one or more sensors coupled to a wearable computing device, processing the input to determine a pattern, the pattern associated with a social network, and generating a control signal based on the input, the control signal configured to initiate execution of a social-related activity on the social network.
Abstract:
Embodiments of the invention relates generally to electrical and electronic hardware, computer software, wired and wireless network communications, and computing devices, and more specifically to structures and techniques for managing power generation, power consumption, and other power-related functions in a data-capable strapband, including receiving input from one or more sensors coupled to a wearable computing device, processing the input to determine a pattern, the pattern indicating a threshold clock frequency, and operating a processor coupled to the wearable computing device at a clock frequency above the threshold clock frequency.