Battery Cell Health Self-Test

This disclosure describes techniques for self-testing of battery health of electronic devices. Per techniques of this disclosure, a battery cell health state is determined by performing a self-test that emulates high power-draw and/or critical usage scenarios. The self-test is conducted at a likely inactive time for the device use based on user-permitted contextual factors. During the test, device charging is disabled so that the battery cell is isolated from its power source. The battery voltage is lowered to a predetermined voltage that is representative of a low state of charge by utilizing a power virus. Battery health parameters such as power consumption, state of charge, current being drawn from battery, battery voltage during the test, etc., are recorded. Based on the battery health parameters measured during the self-test, usage parameters are adjusted to mitigate brownout risk

Motion activated wireless reconnection

The time taken from the removal of a laptop or other device from a bag by a user to the establishment of connection to a wireless network can be significant, e.g., ten seconds or more. This disclosure describes techniques to reduce this delay to nearly zero. Per the techniques, upon detection of motion by on-board motion sensors of a device, the device wakes from a sleep state and automatically scans for and connects to a WiFi network

Determination of User Home Location for Emergency Services

This disclosure describes techniques to accurately determine a user’s home location for use in voice over WiFi (VoWiFi) emergency calls. Per techniques of this disclosure, with user permission, a user’s home location is determined on a user device based on location information and corresponding time signatures associated with the locations. Based on user location data, location clusters and sub-clusters are created. Based on the identified sub-clusters, a home cluster is identified and labeled as the user home location based on the location sub-cluster with time signatures representing the end of day and/or the location sub-cluster where the user has spent the longest stationary time. If the determined home location address is different from the current emergency address associated with the user, the user is prompted to update their emergency address to the newly determined home location address. The process is performed entirely on the user device

Cell Age Balancing For Wireless Earbuds

True wireless earbuds that include on-board batteries are popular. This disclosure describes techniques to balance cell aging of wireless earbuds and enable utilization of the full capacity of the battery cells of wireless earbuds. A fuel gauge value (available cell capacity) for each earbud is recorded. When the earbuds are charging, e.g., in a charging case, the fuel gauge value for each earbud is read. A cell age equalization mode is invoked if the difference between the available cell capacities meets a predetermined threshold. When the earbuds are placed in cell equalization mode, a code path may be configured to enable more frequent master-slave role switches between the earbuds, configure the earbud with the healthier cell automatically as the master earbud, and/or deactivate some compute functionality on the earbud with the weaker cell

Dynamic Audio Level Adjustment in Wearable Audio Devices

Ambient sound levels in environments where wearable audio devices are utilized can vary substantially. Such variation can cause responses provided via such devices to be inaudible or too loud in certain situations. This disclosure describes techniques for dynamic adjustment of wearable device audio output levels based on measured ambient sounds levels. Per techniques of this disclosure, with user permission, sound pressure levels (dB SPL) of a user’s ambient environment are measured and stored in a buffer. The audio output level for the user device is set such that audio output from the wearable device exceeds an average measured dB SPL level by a predetermined threshold. When an on-board speaker on the wearable device is to be utilized, a moving average of dB SPL levels is computed that is representative of an ambient noise level of an immediately preceding time period. Based on the computed average dB SPL level, the output speaker volume is selected, e.g., set to about 6 dB above the computed average dB SPL level

INTELLIGENTLY LOCKING A DEVICE BASED ON CONTEXTUAL SIGNALS

A system is described that enables a computing device (e.g., a mobile phone, smartwatch, tablet computer, etc.) to detect or couple with a companion computing device to detect various contextual signals and automatically lock the computing device based on the various contextual signals. The computing device may use one or more sensors (e.g., infrared cameras, near-field microwave sensors, cameras, microphones, etc.) to detect user inputs, measure wireless signal characteristics, capture images, determine a location of the computing device, etc. as contextual signals. The computing device may analyze these contextual signals to lock the computing device automatically (i.e., change the computing device from operating in a first access state to operating in a second access state that restricts usage of one or more features, applications, or other functionalities of the computing device relative to the first access state). For example, if a user walks away from the computing device, the computing device may use a radio detection and ranging (radar) system to detect that the user is no longer in front of the computing device and, in response, may automatically lock the computing device. In various instances, a companion computing device may couple with the computing device to detect or otherwise determine contextual signals which may be provided to and used by the computing device to lock the device automatically

Detecting hardware damage using a resistive grid

Dropping a mobile phone or other electronic device can damage not only the enclosure but also internal components, e.g., batteries, printed circuit boards, etc. Sometimes the damage is only internal, with no apparent damage to the casing. Continued use of damaged internal components can result in further damage, e.g., continued use of a damaged USB bridge or battery can result in short circuits or explosions. Per techniques of this disclosure, a variable resistive matrix is embedded within the casing of the electronic device. If the casing is dented or otherwise damaged, even invisibly, the resistance of corresponding rows and columns of the matrix changes enabling localization of the damage. Components near the damage can be disabled, and the user can be notified to take the device in for service

User account suggestions for access-restricted online resources

Mobile device users often have multiple account credentials, e.g., personal accounts, corporate accounts, etc., stored on their devices. A given webpage, document, or URL may be configured with permission for access via one user account but not for other user accounts. This disclosure describes techniques that automatically use or recommend credentials stored on a device to gain access to protected content

Multi-camera arrays to detect posture

This disclosure describes techniques that, with user permission, automatically detect the posture of a user of a personal computer. The user’s posture is detected using hardware typically found on a desktop or laptop PC, e.g., cameras, without requiring extra sensors or other additional hardware. If the detected posture is determined to be poor, the user is alerted. By detecting and alerting the user of poor posture, the techniques can help forestall health problems. The techniques are implemented with user permission. Users are provided with options to turn off posture detection

Looking the Part: Social Status Cues Shape Race Perception

It is commonly believed that race is perceived through another's facial features, such as skin color. In the present research, we demonstrate that cues to social status that often surround a face systematically change the perception of its race. Participants categorized the race of faces that varied along White–Black morph continua and that were presented with high-status or low-status attire. Low-status attire increased the likelihood of categorization as Black, whereas high-status attire increased the likelihood of categorization as White; and this influence grew stronger as race became more ambiguous (Experiment 1). When faces with high-status attire were categorized as Black or faces with low-status attire were categorized as White, participants' hand movements nevertheless revealed a simultaneous attraction to select the other race-category response (stereotypically tied to the status cue) before arriving at a final categorization. Further, this attraction effect grew as race became more ambiguous (Experiment 2). Computational simulations then demonstrated that these effects may be accounted for by a neurally plausible person categorization system, in which contextual cues come to trigger stereotypes that in turn influence race perception. Together, the findings show how stereotypes interact with physical cues to shape person categorization, and suggest that social and contextual factors guide the perception of race