Abstract:
Embodiments are disclosed for a wireless wearable computer with fitness machine connectivity for improved activity monitoring using caloric expenditure models. In an embodiment, a method comprises: establishing, by a processor of a wireless wearable computer worn by a user, a wireless communication connection with a fitness machine; obtaining, by the processor using the communication connection, machine data from the fitness machine while the user is engaged in a workout session on the fitness machine; obtaining, from a heart rate sensor of the wireless device, heart rate data of the user; determining, by the processor, a work rate caloric expenditure by applying a work rate calorie model to the machine data; determining, by the processor, a calibrated maximal oxygen consumption of the user based on the heart rate data and the work rate caloric expenditure; determining, by the processor, a heart rate caloric expenditure by applying a heart rate calorie model to the heart rate data and the calibrated maximal oxygen consumption of the user; and sending, by the processor to the fitness machine via the communication connection, at least one of the work rate caloric expenditure or the heart rate caloric expenditure.
Abstract:
This disclosure relates to caching SIM files at a baseband processor to reduce cellular bootup time. According to one embodiment, a wireless device may read SIM files from a SIM and store a local copy of each file in a cache of the baseband processor of the wireless device. SIM identification information for the SIM from which the cached files were read may be associated with the cache. Indicator information usable for comparing file versions may also be generated and stored in the cache for each file. Upon a subsequent SIM initialization, the wireless device may read SIM files from the cache instead of from the initialized SIM if the cached version is identical to the SIM version, which may be determined based at least in part on the SIM identification information and the indicator information for such files.
Abstract:
Methods and apparatus for dynamic search management in a multi-mode device. In one embodiment, a mobile device performs network search and acquisition by dynamically changing search delays and/or search frequencies. In one implementation, the mobile device adjusts the amount of time allocated for each network search based on e.g., previous network connection history (e.g., previously connected to a home network, previously connected to a roaming network), device conditions, user preferences, geographical information, etc. By focusing search effort on cellular technologies which have a high likelihood of success, the mobile device can greatly improve search time and reduce unnecessary power consumption.
Abstract:
The present disclosure relates to methods and systems of determining swimming metrics of a user during a swimming session. The method can include receiving, by a processor circuit of a user device, motion information from one or more motion sensors of the user device; determining, by the processor circuit using the motion information, a first set of rotational data of the user device, wherein the first set of rotational data is expressed in a first frame of reference; converting, by the processor circuit, the first set of rotational data into a second set of rotational data, wherein the second set of rotational data is expressed in a second frame of reference; determining, by the processor circuit, one or more swimming metrics of the user; and outputting the one or more swimming metrics.
Abstract:
An electronic device may use motion and/or activity sensors to estimate a user's maximum volumetric flow of oxygen (VO2 max). In particular, the electronic device may use the user's heart rate, speed, and grade to determine the VO2 max. However, in indoor environments, it may be difficult to accurately measure the user's speed and grade. Therefore, the device may receive the speed and grade from external equipment, such as exercise equipment. To ensure that the user is moving at the reported speed, a discordance detector may compare the user's cadence to an expected cadence based on the speed and grade reported by the external equipment. If the user's cadence is within an acceptable range of the expected cadence, the user's VO2 max may be estimated based on the speed and grade. If the user's cadence is not within the acceptable range, the speed and grade may be discarded or corrected.
Abstract:
In an embodiment, a method comprises: establishing, by a wireless wearable computer worn by a user, a wireless communication connection with a fitness machine; obtaining machine data from the fitness machine while the user is engaged in a workout session on the fitness machine; obtaining, from a heart rate sensor of the wireless device, heart rate data of the user; determining a work rate caloric expenditure by applying a work rate calorie model to the machine data; determining a calibrated maximal oxygen consumption of the user based on the heart rate data and the work rate caloric expenditure; determining a heart rate caloric expenditure by applying a heart rate calorie model to the heart rate data and the calibrated maximal oxygen consumption of the user; and sending to the fitness machine via the communication connection, at least one of the work rate caloric expenditure or the heart rate caloric expenditure.
Abstract:
A digitally stored map can indicate the signal quality for each of the map's regions. A device can determine its location, speed, and direction using global positioning system (GPS) and other sensors. Based on this information, the mobile device can predict a field of locations within which the device will probably be located within a specified future time frame. Based on both the information indicating signal quality and the probable future field of locations, the device can estimate a moment at which the device will probably begin to suffer from low-quality or absent signal. Using this prediction, the device can proactively perform a variety of anticipatory remedial actions. For example, the device can begin allocating a greater portion of currently available wireless network communication bandwidth to the reception of data packets that represent content that is being streamed to the device, so that the device can proactively buffer those packets.
Abstract:
A digitally stored map can indicate the signal quality for each of the map's regions. A device can determine its location, speed, and direction using global positioning system (GPS) and other sensors. Based on this information, the mobile device can predict a field of locations within which the device will probably be located within a specified future time frame. Based on both the information indicating signal quality and the probable future field of locations, the device can estimate a moment at which the device will probably begin to suffer from low-quality or absent signal. Using this prediction, the device can proactively perform a variety of anticipatory remedial actions. For example, the device can begin allocating a greater portion of currently available wireless network communication bandwidth to the reception of data packets that represent content that is being streamed to the device, so that the device can proactively buffer those packets.
Abstract:
In one aspect, the present disclosure relates to a method, including obtaining, by the fitness tracking device, motion data of the user over a period of time, wherein the motion data can include a first plurality motion measurements from a first motion sensor of the fitness tracking device; determining, by the fitness tracking device, using the motion data an angle of the fitness tracking device relative to a plane during the period of time; estimating by the fitness tracking device, using the motion data, a range of linear motion of the fitness tracking device through space during the period of time; and comparing, by the fitness tracking device, the angle of the fitness tracking device to a threshold angle and comparing the range of linear motion of the fitness tracking device to a threshold range of linear motion to determine whether the user is sitting or standing.
Abstract:
A digitally stored map can indicate the signal quality for each of the map's regions. A device can determine its location, speed, and direction using global positioning system (GPS) and other sensors. Based on this information, the mobile device can predict a field of locations within which the device will probably be located within a specified future time frame. Based on both the information indicating signal quality and the probable future field of locations, the device can estimate a moment at which the device will probably begin to suffer from low-quality or absent signal. Using this prediction, the device can proactively perform a variety of anticipatory remedial actions. For example, the device can begin allocating a greater portion of currently available wireless network communication bandwidth to the reception of data packets that represent content that is being streamed to the device, so that the device can proactively buffer those packets.