Abstract: The present disclosure features systems and methods for analyzing student learning and calibrating the difficulty of questions on a test or examination. In one embodiment, a method for analyzing the learning of a student includes administering, by an assessment agent, a task to a student, the task comprising a question having an associated difficulty. The assessment agent receives a response to the question from the student and evaluates the response to generate an observable, the observable comprising information related to the response. A posterior determination of the student's ability is then calculated by incorporating the observable into an ability model associated with the student, and the posterior determination of ability may be compared with the difficulty of the question, a skill acquisition probability, or other measure. The student's response, or a plurality of responses from students within a cohort, may be used to determine the difficulty of each question.

Abstract: Systems and methods for analyzing electrophysiological signals acquired from a subject are provided. In some aspects, a method includes receiving electrophysiological signals acquired from a subject using one or more sensors, and assembling a set of time-series data using the acquired electrophysiological signals. The method also includes analyzing the set of time-series data using a state-space multi-taper framework to generate spectral information describing the electrophysiological signals, and determining a brain state of the subject using the spectral information. The method further includes generating a report indicative of the determined brain state.

Abstract: Systems and apparatuses for determining locations of wireless nodes in a network architecture are disclosed herein. In one example, an asynchronous system includes first and second wireless nodes each having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in the wireless network architecture. The system also includes a third wireless node having an unknown location and a wireless device with a transmitter and a receiver to enable communications with the first and second wireless nodes in the wireless network architecture.

Abstract: Systems and apparatuses for determining locations of wireless nodes in a network architecture are disclosed herein. In one example, an asynchronous system includes first and second wireless nodes each having a wireless device with one or more processing units and RF circuitry for transmitting and receiving communications in the wireless network architecture. The system also includes a third wireless node having an unknown location and a wireless device with a transmitter and a receiver to enable communications with the first and second wireless nodes in the wireless network architecture.

Abstract: Systems and methods for analyzing electrophysiological signals acquired from a subject are provided. In some aspects, a method includes receiving electrophysiological signals acquired from a subject using one or more sensors, and assembling a set of time-series data using the acquired electrophysiological signals. The method also includes analyzing the set of time-series data using a state-space multi-taper framework to generate spectral information describing the electrophysiological signals, and determining a brain state of the subject using the spectral information. The method further includes generating a report indicative of the determined brain state.

Abstract: The present disclosure features systems and methods for analyzing student learning and calibrating the difficulty of questions on a test or examination. In one embodiment, a method for analyzing the learning of a student includes administering, by an assessment agent, a task to a student, the task comprising a question having an associated difficulty. The assessment agent receives a response to the question from the student and evaluates the response to generate an observable, the observable comprising information related to the response. A posterior determination of the student's ability is then calculated by incorporating the observable into an ability model associated with the student, and the posterior determination of ability may be compared with the difficulty of the question, a skill acquisition probability, or other measure. The student's response, or a plurality of responses from students within a cohort, may be used to determine the difficulty of each question.

Abstract: A system and method for monitoring a patient includes a sensor configured to acquire physiological data from a patient and a processor configured to receive the physiological data from the at least one sensor. The processor is also configured to apply a spectral estimation framework that utilizes structured time-frequency representations defined by imposing, to the physiological data, a prior distributions on a time-frequency plane that enforces spectral estimates that are smooth in time and sparse in a frequency domain. The processor is further configured to perform an iteratively re-weighted least squares algorithm to perform yield a denoised time-varying spectral decomposition of the physiological data and generate a report indicating a physiological state of the patient.

Abstract: A novel enhanced beamforming technique that improves beamforming operations by incorporating a model for the directional gains of the sensors, such as microphones, and provides means of estimating these gains. The technique forms estimates of the relative magnitude responses of the sensors (e.g., microphones) based on the data received at the array and includes those in the beamforming computations.