Abstract: A garment system comprises a garment substrate formed from one or more textile-based sheets, a distributed array of a plurality of resistive pressure sensors coupled to the garment substrate at a set of first specified locations. Each of the plurality of resistive sensors comprises a pair of first textile-based outer layers each having an electrical resistance of no more than 100 ohms and a textile-based inner layer sandwiched between the pair of first textile-based outer layers having an electrical resistance of at least 1 mega-ohm. The system also includes electronics configured to process signals from the distributed array of resistive pressure sensors to determine one or more physiological properties of a wearer of the garment substrate.

Abstract: Use of high frequency waves, such a millimeter waves, in many circumstances is prevented due to their inability to diffract around common obstacles. Disclosed herein is a system and method for transforming an incident high frequency wave. The system includes meta-atom pairs that define a surface. The meta-atom pairs generate an electro-magnetic response by interacting with an incident wave. This electro-magnetic response can be modulated by applying voltage to the meta-atom pairs. The electro-magnetic response transforms the incident wave into an emitted wave based on its controlled properties. The system and method are able to, by changing the voltage applied, steer the emitted wave a full 360 degrees as wells as transmit it through the surface without significant power loss. Embodiments enable the transmission through or around many obstacles that would normally interfere with high frequency waves.

Abstract: A garment system comprises a garment substrate formed from one or more textile-based sheets, a distributed array of a plurality of resistive pressure sensors coupled to the garment substrate at a set of first specified locations. Each of the plurality of resistive sensors comprises a pair of first textile-based outer layers each having an electrical resistance of no more than 100 ohms and a textile-based inner layer sandwiched between the pair of first textile-based outer layers having an electrical resistance of at least 1 mega-ohm. The system also includes electronics configured to process signals from the distributed array of resistive pressure sensors to determine one or more physiological properties of a wearer of the garment substrate.

Abstract: A garment system comprises a garment substrate formed from one or more textile-based sheets, a distributed array of a plurality of resistive pressure sensors coupled to the garment substrate at a set of first specified locations. Each of the plurality of resistive sensors comprises a pair of first textile-based outer layers each having an electrical resistance of no more than 100 ohms and a textile-based inner layer sandwiched between the pair of first textile-based outer layers having an electrical resistance of at least 1 mega-ohm. The system also includes electronics configured to process signals from the distributed array of resistive pressure sensors to determine one or more physiological properties of a wearer of the garment substrate.

Abstract: Systems and techniques for a low power wrist-worn RFID reader capable of reading RFID tags within the area of a localized personal body network. The wrist-worn reader provides a means for tracking how a user interacts with their environment. The wrist-worn reader may distinguish between tagged objects within the range of the reader and objects held by the user. The reader may also distinguish when a tagged object has been picked up and when it has been released.

Abstract: Examples herein disclose capturing a wifi signal from a computing device corresponding to a computing accessory and harvesting energy from the captured wifi signal. The examples power the computing accessory based on the harvested energy.

Abstract: Examples included herein involve analyzing first movement data measured by a first accelerometer of the first device, analyzing second movement data measured by a second accelerometer of a second device, determining whether the first device and the second device are collocated on a same user based on the first movement data and the second movement data, and controlling a function of the first device or the second device based on whether the first device and the second device are collocated on the same user.

Abstract: Examples relate to determining finger movements. In one example, a computing device may: receive input from at least one of: a first proximity sensor coupled to the frame at a first position and facing a first direction; or a second proximity sensor coupled to the frame at a second position and facing a second direction; determine, based on the input, that a finger action occurred, the finger action being one of: a first movement of a first finger, the first movement being detected by the first proximity sensor; a second movement of a second finger, the second movement being detected by the second proximity sensor; generate, based on the finger action, output that includes data defining an event that corresponds to the finger action; and provide the output to another computing device.

Abstract: Systems and techniques for a low power wrist-worn RFID reader capable of reading RFID tags within the area of a localized personal body network. The wrist-worn reader provides a means for tracking how a user interacts with their environment. The wrist-worn reader may distinguish between tagged objects within the range of the reader and objects held by the user. The reader may also distinguish when a tagged object has been picked up and when it has been released.

Abstract: Examples included herein involve analyzing first movement data measured by a first accelerometer of the first device, analyzing second movement data measured by a second accelerometer of a second device, determining whether the first device and the second device are collocated on a same user based an the first movement date and the second movement data, and controlling a function of the first device or the second device based on whether the first device and the second devices are collocated on the same user.

Abstract: Examples relate to determining finger movements. In one example, a computing device may: receive input from at least one of: a first proximity sensor coupled to the frame at a first position and facing a first direction; or a second proximity sensor coupled to the frame at a second position and facing a second direction; determine, based on the input, that a finger action occurred, the finger action being one of: a first movement of a first finger, the first movement being detected by the first proximity sensor; a second movement of a second finger, the second movement being detected by the second proximity sensor; generate, based on the finger action, output that includes data defining an event that corresponds to the finger action; and provide the output to another computing device.

Abstract: Examples disclosed herein involve a user authenticator that harvests energy from signals. An example involves an authentication manager to provide authentication information to an authorization device to enable access to a secure device in response to receiving a request signal from the authorization device for the authentication Information a power manager to harvest energy from the request signal to power the apparatus.

Abstract: Examples herein disclose capturing a wifi signal from a computing device corresponding to a computing accessory and harvesting energy from the captured wifi signal. The examples power the computing accessory based on the harvested energy.

Abstract: Embodiments that relate to energy efficient gesture input on a surface are disclosed. One disclosed embodiment provides a hand-worn device that may include a microphone configured to capture an audio input and generate an audio signal, an accelerometer configured to capture a motion input and generate an accelerometer signal, and a controller comprising a processor and memory. The controller may be configured to detect a wake-up motion input based on the accelerometer signal. The controller may wake from a low-power sleep mode in which the accelerometer is turned on and the microphone is turned off and enter a user interaction interpretation mode in which the microphone is turned on. Then, the controller may contemporaneously receive the audio signal and the accelerometer signal and decode strokes. Finally, the controller may detect a period of inactivity based on the audio signal and return to the low-power sleep mode.

Abstract: Embodiments that relate to energy efficient gesture input on a surface are disclosed. One disclosed embodiment provides a hand-worn device that may include a microphone configured to capture an audio input and generate an audio signal, an accelerometer configured to capture a motion input and generate an accelerometer signal, and a controller comprising a processor and memory. The controller may be configured to detect a wake-up motion input based on the accelerometer signal. The controller may wake from a low-power sleep mode in which the accelerometer is turned on and the microphone is turned off and enter a user interaction interpretation mode in which the microphone is turned on. Then, the controller may contemporaneously receive the audio signal and the accelerometer signal and decode strokes. Finally, the controller may detect a period of inactivity based on the audio signal and return to the low-power sleep mode.

Abstract: Embodiments that relate to energy efficient gesture input on a surface are disclosed. One disclosed embodiment provides a hand-worn device that may include a microphone configured to capture an audio input and generate an audio signal, an accelerometer configured to capture a motion input and generate an accelerometer signal, and a controller comprising a processor and memory. The controller may be configured to detect a wake-up motion input based on the accelerometer signal. The controller may wake from a low-power sleep mode in which the accelerometer is turned on and the microphone is turned off and enter a user interaction interpretation mode in which the microphone is turned on. Then, the controller may contemporaneously receive the audio signal and the accelerometer signal and decode strokes. Finally, the controller may detect a period of inactivity based on the audio signal and return to the low-power sleep mode.

Abstract: Embodiments that relate to energy efficient gesture input on a surface are disclosed. One disclosed embodiment provides a hand-worn device that may include a microphone configured to capture an audio input and generate an audio signal, an accelerometer configured to capture a motion input and generate an accelerometer signal, and a controller comprising a processor and memory. The controller may be configured to detect a wake-up motion input based on the accelerometer signal. The controller may wake from a low-power sleep mode in which the accelerometer is turned on and the microphone is turned off and enter a user interaction interpretation mode in which the microphone is turned on. Then, the controller may contemporaneously receive the audio signal and the accelerometer signal and decode strokes. Finally, the controller may detect a period of inactivity based on the audio signal and return to the low-power sleep mode.