Abstract: A system for performing deep brain stimulation on a brain of a patient is disclosed. The system comprises one or more recording arrays, at least one stimulation array, and a processor. The recording arrays, which may be minimally invasively inserted to a target recording site of the brain, include recording electrodes having a diameter of less than about 1 mm and having a spacing of less than about 1 mm therebetween. The stimulation array, which may be inserted to a target stimulation site within the deep brain, includes at least one stimulation electrode. The processor is configured to receive one or more recorded signals from the recording arrays at the target recording site, determine a neurological state of the brain based on the recorded signals, and deliver electrical stimulation to the target stimulation site through the stimulation array based on the neurological state in order to electrically stimulate the brain.

Abstract: A medical device system that can include a medical device configured to sense data associated with the subject or receive control input, an external device communicably coupled to the medical device, a storage medium communicably coupled to the external device, and one or more communications interfaces between the medical device, the external device, and the storage medium or components thereof, wherein the one or more communications interfaces comprise an encryption protocol.

Abstract: A system for performing spinal cord stimulation on a subject is disclosed. The system comprises one or more recording arrays, at least one stimulation array, and a processor. The recording arrays, which may be minimally invasively inserted to a target recording site of the brain, include recording electrodes having a diameter of less than about 1 mm and having a spacing of less than about 1 mm therebetween. The stimulation array, which may be minimally invasively inserted to a target stimulation site within the nervous tissue, includes stimulation electrodes. The processor is configured to receive more recorded signals from the recording arrays at the target recording site, determine an electrophysiological state of the brain based on the recorded signals, and deliver electrical stimulation to the target stimulation site through the stimulation array based on the determined electrophysiological state in order to affect the electrophysiological state.

Abstract: A systems and methods for calibrating a neural device using transfer learning techniques. The methods can include aggregating calibration data across a user population to define a global dataset, identifying similar data segments across the global dataset to define a task-independent training dataset, training a feature extraction model based on the task-independent training dataset to define a trained, task-independent feature extraction model, receiving the calibration data from a user calibrating the neural device, and calibrating a user-specific feature extraction model using the trained, task-independent feature extraction model and the calibration data.

Abstract: A neural device system that can include a neural device configured to sense data associated with the subject or receive control input, an external device communicably coupled to the neural device, a storage medium communicable coupled to the external device, and one or more communications interfaces between the neural device, the external device, and the storage medium or components thereof, wherein the one or more communications interfaces comprise an encryption protocol.

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: Systems and methods of analyzing a user's motion during a swimming session are described. One or more motions sensors can collect motion data of the user. A processor circuit can make motion analysis based on the motion data. The processor circuit can determine if the user's arm swing is a genuine swim stroke. The processor circuit can also determine whether the user is swimming or turning. The processor circuit can also classify the user's swim stroke style. The processor circuit can also determine the user's swim stroke phase. The processor circuit can also determine the user's stroke orbit consistency.

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: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

Abstract: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.

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.

Abstract: In one aspect, the present disclosure relates to a method including obtaining, by a heart rate sensor of a fitness tracking device, a heart rate measurement of a user of the fitness tracking device; obtaining, by at least one motion sensor, motion data of the user; analyzing, by the fitness tracking device, the motion data of the user to estimate a step rate of the user; estimating, by the fitness tracking device, a load associated with a physical activity of the user by comparing the heart rate measurement with the step rate of the user; and estimating, by the fitness tracking device, an energy expenditure rate of the user using the load and at least one of the heart rate measurement and the step rate.

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: Systems and methods of analyzing a user's motion during a swimming session are described. One or more motions sensors can collect motion data of the user. A processor circuit can make motion analysis based on the motion data. The processor circuit can determine if the user's arm swing is a genuine swim stroke. The processor circuit can also determine whether the user is swimming or turning. The processor circuit can also classify the user's swim stroke style. The processor circuit can also determine the user's swim stroke phase. The processor circuit can also determine the user's stroke orbit consistency.

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.

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 method and a system for determining an individual energy expenditure are described. In some embodiments, an energy expenditure can be calculated based on a combination of biometrics, heart rate and work rate. In some embodiments, a relative drag associated with the user can be calculated based on a group formation size, a group formation shape, participant velocities, weather, air density, and participant body surface areas. In some embodiments, a load adjustment factor can be determined based on the relative drag. In some embodiments, an adjusted energy expenditure can be determined based on the load adjustment factor.

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: Improved techniques and systems are disclosed for determining the components of resistance experienced by a wearer of a wearable device engaged in an activity such as bicycling or running. By monitoring data using the wearable device, improved estimates can be derived for various factors contributing to the resistance experienced by the user in the course of the activity. Using these improved estimates, data sampling rates may be reduced for some or all of the monitored data.