Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: Methods and systems are provided for using frequency spreading during communications, in particular communications in which multiple carriers (or subcarriers) are used. The frequency spreading may comprise generating a plurality of spreading data vectors based on transmit data, such as by application of a spreading matrix to portions of the transmit data. Each spreading data vector may comprise a plurality of elements, for assignment to the multiple subcarriers. The receive-side device may then apply frequency de-spreading, to obtain the original transmit data. The frequency de-spreading may comprise use of the same spreading matrix on data extracted from received signals, which (the data) may correspond to the plurality of spreading data vectors.

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: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: Ear buds may have optical proximity sensors and accelerometers. Control circuitry may analyze output from the optical proximity sensors and the accelerometers to identify a current operational state for the ear buds. The control circuitry may also analyze the accelerometer output to identify tap input such as double taps made by a user on ear bud housings. Samples in the accelerometer output may be analyzed to determine whether the samples associated with a tap have been clipped. If the samples have been clipped, a curve may be fit to the samples. Optical sensor data may be analyzed in conjunction with potential tap input data from the accelerometer. If the optical sensor data is ordered, a tap input may be confirmed. If the optical sensor data is disordered, the control circuitry can conclude that accelerometer data corresponds to false tap input associated with unintentional contact with the housing.

Abstract: Methods and systems are provided for using frequency spreading during communications, in particular communications in which multiple carriers (or subcarriers) are used. The frequency spreading may comprise generating a plurality of spreading data vectors based on transmit data, such as by application of a spreading matrix to portions of the transmit data. Each spreading data vector may comprise a plurality of elements, for assignment to the multiple subcarriers. The receive-side device may then apply frequency de-spreading, to obtain the original transmit data. The frequency de-spreading may comprise use of the same spreading matrix on data extracted from received signals, which (the data) may correspond to the plurality of spreading data vectors.

Abstract: Methods and systems are provided for using frequency spreading during communications, in particular communications in which multiple carriers (or subcarriers) are used. The frequency spreading may comprise generating a plurality of spreading data vectors based on transmit data, such as by application of a spreading matrix to portions of the transmit data. Each spreading data vector may comprise a plurality of elements, for assignment to the multiple subcarriers. The receive-side device may then apply frequency de-spreading, to obtain the original transmit data. The frequency de-spreading may comprise use of the same spreading matrix on data extracted from received signals, which (the data) may correspond to the plurality of spreading data vectors.

Abstract: In an example method, a mobile device obtains a database including a plurality of data records. Each data record includes an indication of a respective impact previously experienced by a user of the mobile device, and sensor data generated by one or more first sensors worn by the user during that impact. The mobile device obtains sensor data generated by one or more second sensors worn by the user over a period of time, and determines whether the user has fallen during the period of time based on the database and the additional sensor data. The mobile device generates one or more notifications based on the determination of whether the user has fallen during the period of time.

Abstract: In an example method, a mobile device receives motion data obtained by one or more sensors worn by a user. The mobile device determines, based on the motion data, that the user has fallen at a first time and whether the user has moved between a second time and a third time subsequent to the first time. Upon determining that the user has not moved between the second time and the third time, the mobile device initiates a communication to an emergency response service at a fourth time after the third time. The communication includes an indication that the user has fallen and a location of the user.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: In an example method, a mobile device receives motion data obtained by one or more sensors worn by a user. The mobile device determines, based on the motion data, that the user has fallen at a first time and whether the user has moved between a second time and a third time subsequent to the first time. Upon determining that the user has not moved between the second time and the third time, the mobile device initiates a communication to an emergency response service at a fourth time after the third time. The communication includes an indication that the user has fallen and a location of the user.

Abstract: In an example method, a mobile device obtains a database including a plurality of data records. Each data record includes an indication of a respective impact previously experienced by a user of the mobile device, and sensor data generated by one or more first sensors worn by the user during that impact. The mobile device obtains sensor data generated by one or more second sensors worn by the user over a period of time, and determines whether the user has fallen during the period of time based on the database and the additional sensor data. The mobile device generates one or more notifications based on the determination of whether the user has fallen during the period of time.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: A method and a system for determining an energy expenditure of a user while practicing yoga are described. A heart rate sensing module can measure the user's heart rate. A temperature sensing module can measure ambient temperature. A motion sensing module can collect user's motion data. In some embodiments, a hot yoga session can be detected based on measured ambient temperature. In some embodiments, a yoga type can be detected based on the motion data. In some embodiments, an energy expenditure model can be applied based on the determined yoga type.

Abstract: A relationship relating a load of exercise and a user's aerobic capacity may be determined as follows. A processor circuit of a device may retrieve, from a memory, a prior probability distribution of the load of exercise and a prior probability distribution of the user's aerobic capacity. The processor circuit may compute a joint prior probability of the load of exercise and the user's aerobic capacity. The processor circuit may compute a joint likelihood of the load of exercise and the user's aerobic capacity based on data indicative of a measured time-stamped work rate and a measured time-stamped heart rate. The processor circuit may combine the joint prior probability and the joint likelihood to produce a joint posterior probability. The processor circuit may use the joint posterior probability to determine a relationship relating the load of exercise and the user's aerobic capacity and output a calorie calculation.

Abstract: The present disclosure relates to a system and method of detecting activity by a wheelchair user. In one aspect, a method comprises collecting motion data of a user device located on an appendage of the user; detecting, by a processor circuit, that one or more activities by the wheelchair user occurred based on the motion data; calculating, by a processor circuit, an energy expenditure by the user based the one or more activities by the wheelchair user occurred; and outputting, by a processor circuit, the energy expenditure estimation.

Abstract: The present disclosure relates to a system and method of detecting activity by a wheelchair user. In one aspect, a method comprises collecting motion data of a user device located on an appendage of the user; detecting, by a processor circuit, that one or more activities by the wheelchair user occurred based on the motion data; calculating, by a processor circuit, an energy expenditure by the user based the one or more activities by the wheelchair user occurred; and outputting, by a processor circuit, the energy expenditure estimation.

Abstract: In an example method, a mobile device obtains a signal indicating an acceleration measured by a sensor over a time period. The mobile device determines an impact experienced by the user based on the signal. The mobile device also determines, based on the signal, one or more first motion characteristics of the user during a time prior to the impact, and one or more second motion characteristics of the user during a time after the impact. The mobile device determines that the user has fallen based on the impact, the one or more first motion characteristics of the user, and the one or more second motion characteristics of the user, and in response, generates a notification indicating that the user has fallen.

Abstract: The present disclosure relates to systems and methods of estimating energy expenditure of a user while swimming. A processor circuit of a user device can estimate a speed of the user based on a stroke rate and a stroke length. The processor circuit can estimate an efficiency of the user. The processor circuit can classify a swimming style of the user. The processor circuit can determine energy expenditure of the user based on the speed, the efficiency, and the style. The processor circuit can also detect glides of the user and adjust the energy expenditure.