Pulsar Informatics, Inc.
|Pulsar Informatics, Inc. Patent applications|
|Patent application number||Title||Published|
|20130184997||Task-Modulated Neurobehavioral Status - Systems and methods for modulating a subject's neurobehavioral status by a task-dependent arousal index are provided. Neurobehavioral status may be measured or model-predicted, and the arousal index reflects the composite effect on the subject's neurobehavioral performance of behavioral, environmental, psychological, and physiological factors of the subject's performing an assigned task. Task arousal index may be selected from a database, provided by user input, or combined in real time from sensor data.||07-18-2013|
|20130132029||SYSTEMS AND METHODS FOR APPLYING DATA MAPPING TECHNIQUES TO ASSESSMENT AND DIAGNOSTIC TEST RESULTS - Systems and methods for analyzing the results of a diagnostic-assessment test result of a subject with respect to those of a comparison population or subpopulation of interest are disclosed. A first set of testing conditions and/or demographic characteristics and their corresponding values are used optionally to identify a subpopulation of interest and select appropriate data from a general-population database. A second (and optionally a third) set of testing conditions and/or demographic characteristics (which may optionally be identical to the first) are then used to project either or both of the subject's test score or the test scores for the population or optional subpopulation of interest to a common basis of testing conditions and/or demographic characteristics using one or more projection functions specific to the testing condition and/or demographic characteristic, as applied to a particular test. A metric of comparison is then determined for the testing subject with this projected data.||05-23-2013|
|20130054215||SYSTEMS AND METHODS FOR APNEA-ADJUSTED NEUROBEHAVIORAL PERFORMANCE PREDICTION AND ASSESSMENT - Human neurobehavioral performance prediction systems and methods are disclosed in which disrupted sleep patterns, such as (without limitation) sleep fracturing due to apnea, are accounted for. Biomathematical models are used to predict neurobehavioral performance based on disrupted sleep using a sleep function modified in accordance with apnea-severity data to account for loss in sleep efficiency. Risk of diminished neurobehavioral performance can then be monitored in affected individuals. Compliance with treatment regimens, adjustments to apnea severity assessment, corrections to predicted future sleep schedules, and/or individualization of neurobehavioral performance model parameters can also be achieved based upon a comparison of actual and model-predicted performance levels.||02-28-2013|
|20130053656||PHYSIOLOGICAL AND NEUROBEHAVIORAL STATUS MONITORING - A system and methods of use are disclosed for monitoring the neurobehavioral and physiological status of one or more individuals across a distributed network, the system comprising, at least in part, and according to alternative embodiments, i) a physiological sensor capable of measuring patient movement; ii) additional physiological sensors; iii) a wireless controller for monitoring polling cycles and power consumption ratings; iv) an administrative user interface for executing various executive control functions; and v) a patient interface capable of receiving input, providing output, and, optionally, administering one or more neurobehavioral tests.||02-28-2013|
|20130018592||Systems and Methods for Inter-Population Neurobehavioral Status Assessment Using Profiles Adjustable to Testing Conditions - Systems and methods for inter-population assessment of neurobehavioral status employ neurobehavioral profiles to accommodate differing external conditions. Population profiles and external condition data are provided to a neurobehavioral performance model to determine neurobehavioral status under external conditions. Alternatively, neurobehavioral performance values may be retrieved from the profile when such values are stored in conjunction with external condition data. Comparisons of the resulting neurobehavioral status(es) are then determined, and may comprise without limitation one or more of: performance deltas, statistical parameter differences, rankings, above/below performance threshold determinations, pass/fail indicators, and countermeasure recommendations. Populations may comprise pluralities, individuals and empty (“null”) sets. Comparisons may also pertain to one or more relevant times of interest and one or more sets of testing conditions. Fields of application include (without limitation) operational and military fatigue management, medical diagnosis and treatment, fatigue countermeasure training and individualization, sleep research, academic and scientific research, and/or the like.||01-17-2013|
|20120329020||SYSTEMS AND METHODS FOR PRESONALIZED FATIGUE EDUCATION AND RISK MANAGEMENT - A method is provided for ascertaining personalized education information related to one or more fatigue-related individual traits of a subject. The method involves: receiving first input data indicative of an expression of one or more fatigue-related individual traits of the subject; estimating trait values for the one or more fatigue-related individual traits, wherein estimating the trait values comprises: using the first input data and a fatigue model, which relates a fatigue level of the subject to a set of model parameters, to estimate values for the set of model parameters; and evaluating one or more trait-estimation functions using the estimated values for the set of model parameters; and determining personalized education information about the one or more fatigue-related individual traits of the subject based on the estimated trait values.||12-27-2012|
|20120316845||Systems and Methods for Distributed Calculation of Fatigue-Risk Prediction and Optimization - Distributed computing methods and systems are disclosed, wherein intensive fatigue-risk calculations are partitioned according to available computing resources, parameters of the fatigue-risk calculation, time-sensitive user demands, and the like. Methods are disclosed wherein execution-cost functions are used to allocate accessible computing resources. Additional methods include partitioning calculation tasks by user-prioritized needs and by general mathematical features of the calculations themselves. Included herein are methods to calculate only prediction-maximum likelihoods instead of full probability distributions, to calculate prediction likelihoods using Bayesian prediction techniques (instead of full re-tabulation of all data), to collate interim results of fatigue-risk calculations where serial results can be appropriately collated (e.g., serial time-slice independence of the cumulative task involved), to use simplified (e.g., linear, first-order) approximations of richer models of fatigue prediction, to assign user-identified priorities to each computational task within a plurality of such requests, and the like.||12-13-2012|
|20120278022||SYSTEMS AND METHODS FOR LATENCY AND MEASUREMENT UNCERTAINTY MANAGEMENT IN STIMULUS-RESPONSE TESTS - Disclosed are systems and methods for managing testing unit latency and measurement uncertainty in computer-based stimulus-response tests. An estimated latency L||11-01-2012|
|20120232414||COMPOSITE HUMAN PHYSIOLOGICAL STRESS INDEX BASED ON HEART BEAT AND SLEEP AND/OR ACTIVITY HISTORY DATA INCLUDING ACTIGRAPHY - Systems and methods are provided for providing a composite stress index representing a quantified stress level that an individual may be experiencing or may have experienced during a time interval of interest. The composite stress index is determined based on a combination of heart beat data representative of cardiac activity of the individual during the time interval of interest and one or both of: sleep history data comprising one or more sleep onset times and one or more awakening times during the time interval of interest; and physical activity history data representative of gross motor activity of the individual during the time interval of interest.||09-13-2012|
|20120221895||SYSTEMS AND METHODS FOR COMPETITIVE STIMULUS-RESPONSE TEST SCORING - Systems and methods for competitively scoring a stimulus-response test are disclosed. Competitive scoring may be based upon: i) a combination of response time and response type (e.g., false start, coincident false start, fast, slow, lapse, timeout, etc.); ii) response time and response latency correction data (e.g., a latency correction parameter corresponding to the test-taker's test system); and iii) a composite score metric comprising any function, rule of categorization, classification system, scoring system and/or the like that can be applied to at least two stimulus-response rounds of one or more test takers to determine a score for each test-taker.||08-30-2012|
|20120203464||NORMALIZED CONTEXTUAL PERFORMANCE METRIC FOR THE ASSESSMENT OF FATIGUE-RELATED INCIDENTS - A normalized contextual performance metric quantifies the susceptibility of fatigue-related risk in a fatigue environment with activities conducted within a fatigue level range of interest. Fatigue incidents are quantified by one of a plurality of values associated with fatigue-incident measurement. Activities are quantified by one of a plurality of values associated with activity measurement. A normalized contextual performance metric is determined by identifying a fatigue level range of interest, summing all values of incidents occurring at the fatigue level range of interest, summing all values for relevant activities occurring at the fatigue level range of interest, and then dividing the first sum by the second. The normalized contextual performance metric thereby allows operational managers to assess risk of fatigue incidents by monitoring activities and fatigue levels within the fatigue environment.||08-09-2012|
|20120072121||SYSTEMS AND METHODS FOR QUALITY CONTROL OF COMPUTER-BASED TESTS - Disclosed are systems and methods for monitoring, inter alter, administration compliance, test subject identity, and results quality of computer-administered tests. A test administration unit, an audio-visual data collection unit, and an audio-visual data processing unit are configured to detect testing anomaly events within the testing environment by analyzing audiovisual data from the test subject and environment itself. Disclosed methods include modifying or amending test results because of detected testing anomaly events within the testing environment, verifying the identity of the test subject, and monitoring for compliance with test-administration protocols. Additional methods disclosed include: user facial analysis, including gaze point analysis, for indirect detection of testing anomaly events; user verification using facial recognition, voice recognition, retinal scans, and or other audiovisual biometric protocols; and the like.||03-22-2012|
Patent applications by Pulsar Informatics, Inc.