Abstract: Systems and methods related to recalibrating neural devices based on external sensory information are disclosed. The systems can include a neural device configured to sense data associated with the subject or receive control input, a sensor communicably coupled to the external device, the sensor configured to detect a state associated with the subject, and an external device communicably coupled to the neural device and the sensor. The external device can recalibrate a neural decoding model based on the state detected via the sensor, wherein the neural decoding model correlates the data received from the neural device with a corresponding thought or action performed by the subject.

Abstract: A device and system for real-time visualization of the electrophysiologic activity of a brain, particularly at the cortical surface. The neural device can acquire, process, and display high-spatiotemporal-resolution electrophysiologic data in real-time across entire electrode arrays spanning many thousands of electrodes over identified anatomic regions. The system is compatible with thin-film cortical surface electrodes that record from neural tissues without damaging those tissues. The system can be used to guide diagnostic and therapeutic actions with high precision, and also provides the basis for a brain-computer interface.

Abstract: A system for detecting a neurological state of a brain of a patient is disclosed. The system comprises one or more recording arrays, a database, and a processor. The recording arrays comprise a plurality of recording electrodes having a diameter of less than about 1 mm and spaced by less than about 1 mm, and are configured to be minimally invasively inserted to the brain to record electrical signals from a target recording site. The database stores electrophysiological data relating to known electrophysiological signatures associated with neurological states. The processor is configured to receive recorded signals from the recording arrays, access the electrophysiological data from the database, identify electrophysiological signatures in the recorded signals based on the electrophysiological data, and determine the neurological state of the brain based on the identified electrophysiological signatures.

Abstract: In an example method, a computing device obtains sensor data generated by one or more accelerometers and one or more gyroscopes over a time period, including an acceleration signal indicative of an acceleration measured by the one or more accelerometers over a time period, and an orientation signal indicative of an orientation measured by the one or more gyroscopes over the time period. The one or more accelerometers and the one or more gyroscopes are physically coupled to a user walking along a surface. The computing device identifies one or more portions of the sensor data based on one or more criteria, and determines characteristics regarding a gait of the user based on the one or more portions of the sensor data, including a walking speed of the user and an asymmetry of the gait of the user.

Abstract: A system for compressing neural signal data using spatiotemporal data compression techniques. The system includes an implantable neural that receives electrophysiologic signal data from the electrode array, maps the electrophysiologic signal data to locations of each of the plurality of the electrodes, and compresses the mapped electrophysiologic signal data based on the locations of the plurality of electrodes utilizing a spatiotemporal data compression algorithm to define compressed electrophysiologic signal data. The implantable neural device can be connectable to a computer system that decompressed the electrophysiologic data for various downstream applications.

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: 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 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 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: 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: In an example method, a computing device obtains sensor data generated by one or more accelerometers and one or more gyroscopes over a time period, including an acceleration signal indicative of an acceleration measured by the one or more accelerometers over a time period, and an orientation signal indicative of an orientation measured by the one or more gyroscopes over the time period. The one or more accelerometers and the one or more gyroscopes are physically coupled to a user walking along a surface. The computing device identifies one or more portions of the sensor data based on one or more criteria, and determines characteristics regarding a gait of the user based on the one or more portions of the sensor data, including a walking speed of the user and an asymmetry of the gait of the user.

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: Embodiments are disclosed for passive tracking of dyskinesia and tremor symptoms using a wearable computer. In an embodiment, a method comprises: obtaining, by one or more motion sensors of a computer attached to a user's limb, motion data; extracting, by one or more processors of the computer, one or more features from the motion data that are potentially indicative of dyskinesia or tremor; determining, by one or more processors of the computer and based on the one or more extracted features, the likelihood of dyskinesia or tremor; generating, by the one or more processors, data indicating the likelihood of dyskinesia or tremor; and outputting, by the one or more processors, the data through an output device of the computer.

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.