Abstract: The present disclosure provides methods for identifying non-penetrating brain injury in a subject, as well as methods for classifying a subject that received a hit to the body that transmitted an impulsive force to the brain as either having a non-penetrating brain injury or not, by analyzing one or more components of frequency-following response (FFR) following administration of an acoustic stimulus to the subject. In addition, the present disclosure provides methods for assessing a subject's recovery from a non-penetrating brain injury. Also disclosed herein are processes and systems for automatically generating acoustic stimuli and processing brain response data to identify non-penetrating brain injuries in subjects.

Abstract: The present disclosure relates to methods for evaluating the sound quality of a digital engineering process by, in part, measuring the frequency following response (FFR) of the human auditory system elicited by identical auditory stimuli (e.g., a musical interval) encoded with variations of a digital signal processing technique (e.g., various sampling rates). Once measured, the FFR may be analyzed to determine the comparative effect of each digital signal processing technique on a human subject's ability to process complex stimuli presented by the digital engineering process.

Abstract: Central nervous (“CNS”) health in subjects who have human immunodeficiency virus (“HIV”) or non-human-species analogs thereof is 102 evaluated or otherwise monitored by analyzing frequency following response (“FFR”). In general, one or more components of an FFR are analyzed, The FFR is measured in response to the administration of an acoustic stimulus to the subject. The acoustic stimulus includes a complex sound, which may include a consonant and a consonant-to-vowel transition. An indication of CNS health can be generated by measuring changes in the FFR components (e.g., over time or relative to normative data).

Abstract: The present disclosure provides methods for identifying non-penetrating brain injury in a subject, as well as methods for classifying a subject that received a hit to the body that transmitted an impulsive force to the brain as either having a non-penetrating brain injury or not, by analyzing one or more components of frequency-following response (FFR) following administration of an acoustic stimulus to the subject. In addition, the present disclosure provides methods for assessing a subject's recovery from a non-penetrating brain injury. Also disclosed herein are processes and systems for automatically generating acoustic stimuli and processing brain response data to identify non-penetrating brain injuries in subjects.

Abstract: The present disclosure relates to methods for evaluating the sound quality of a digital engineering process by, in part, measuring the frequency following response (FFR) of the human auditory system elicited by identical auditory stimuli (e.g., a musical interval) encoded with variations of a digital signal processing technique (e.g., various sampling rates). Once measured, the FFR may be analyzed to determine the comparative effect of each digital signal processing technique on a human subject's ability to process complex stimuli presented by the digital engineering process.

Abstract: Disclosed systems and methods analyze a complex auditory response to generate a particular model for a behavioral outcome. An example method includes analyzing one or more response to a complex stimulus to identify regions in each response and peaks in each region. The example method includes constructing a behavioral outcome model based on region and peak information by evaluating a plurality of parameters based on the information associated with the regions and peaks and applying a best fit analysis to include and/or exclude parameters from the plurality of parameters to determine parameters and relationship between the parameters to form the model. The example method includes facilitating application of the model to generate a score by obtaining values for the parameters forming the model and combining the values according to the relationship between the parameters specified in the model, the score indicative of the behavior outcome with respect to at least one first subject.

Abstract: The present disclosure provides methods for identifying non-penetrating brain injury in a subject, as well as methods for classifying a subject that received a hit to the body that transmitted an impulsive force to the brain as either having a non-penetrating brain injury or not, by analyzing one or more components of frequency-following response (FFR) following administration of an acoustic stimulus to the subject. In addition, the present disclosure provides methods for assessing a subject's recovery from a non-penetrating brain injury. Also disclosed herein are processes and systems for automatically generating acoustic stimuli and processing brain response data to identify non-penetrating brain injuries in subjects.

Abstract: The present disclosure provides methods for identifying non-penetrating brain injury in a subject, as well as methods for classifying a subject that received a hit to the body that transmitted an impulsive force to the brain as either having a non-penetrating brain injury or not, by analyzing one or more components of frequency-following response (FFR) following administration of an acoustic stimulus to the subject. In addition, the present disclosure provides methods for assessing a subject's recovery from a non-penetrating brain injury. Also disclosed herein are processes and systems for automatically generating acoustic stimuli and processing brain response data to identify non-penetrating brain injuries in subjects.

Abstract: Disclosed systems and methods analyze a complex auditory response to generate a particular model for a behavioral outcome. An example method includes analyzing one or more response to a complex stimulus to identify regions in each response and peaks in each region. The example method includes constructing a behavioral outcome model based on region and peak information by evaluating a plurality of parameters based on the information associated with the regions and peaks and applying a best fit analysis to include and/or exclude parameters from the plurality of parameters to determine parameters and relationship between the parameters to form the model. The example method includes facilitating application of the model to generate a score by obtaining values for the parameters forming the model and combining the values according to the relationship between the parameters specified in the model, the score indicative of the behavior outcome with respect to at least one first subject.

Abstract: Certain examples provide a method of collecting and analyzing complex auditory brainstem response. The example method includes presenting at least one complex auditory stimulus to a subject and acquiring the subject's complex auditory brainstem response. The example method includes averaging complex auditory brainstem responses from the subject in at least one of a time domain and a frequency domain to form a collected response. The example method includes analyzing the collected response using a signal processor to process the collected response to provide a processed output and to adapt the response for comparison to the at least one complex auditory stimulus. The example method includes performing statistical computations on the processed output to generate visual and data feedback for a user.

Abstract: Certain examples provide a method of collecting and analyzing complex auditory brainstem response. The example method includes presenting at least one complex auditory stimulus to a subject and acquiring the subject's complex auditory brainstem response. The example method includes averaging complex auditory brainstem responses from the subject in at least one of a time domain and a frequency domain to form a collected response. The example method includes analyzing the collected response using a signal processor to process the collected response to provide a processed output and to adapt the response for comparison to the at least one complex auditory stimulus. The example method includes performing statistical computations on the processed output to generate visual and data feedback for a user.

Abstract: A system and method of central auditory processing testing and evaluation provides for identifying clinically relevant neural synchrony in the auditory brainstem pathway. The system or method finds use as a tool to evaluate auditory processing disorders, and hence, potential auditory system and/or learning disabilities. The system or method may further find use in the selection and fitting of hearing corrective appliances such as hearing aid or cochlear implant devices and/or in the selection and implementation of auditory training regimens.

Abstract: Certain examples provide a method of collecting and analyzing complex auditory brainstem response. The example method includes presenting at least one complex auditory stimulus to a subject and acquiring the subject's complex auditory brainstem response. The example method includes averaging complex auditory brainstem responses from the subject in at least one of a time domain and a frequency domain to form a collected response. The example method includes analyzing the collected response using a signal processor to process the collected response to provide a processed output and to adapt the response for comparison to the at least one complex auditory stimulus. The example method includes performing statistical computations on the processed output to generate visual and data feedback for a user.

Abstract: A system and method of central auditory processing testing and evaluation provides for identifying clinically relevant neural synchrony in the auditory brainstem pathway. The system or method finds use as a tool to evaluate auditory processing disorders, and hence, potential auditory system and/or learning disabilities. The system or method may further find use in the selection and fitting of hearing corrective appliances such as hearing aid or cochlear implant devices and/or in the selection and implementation of auditory training regimens.

Abstract: A system and method of central auditory processing testing and evaluation provides for identifying clinically relevant neural synchrony in the auditory brainstem pathway. The system or method finds use as a tool to evaluate auditory processing disorders, and hence, potential auditory system and/or learning disabilities. The system or method may further find use in the selection and fitting of hearing corrective appliances such as hearing aid or cochlear implant devices and/or in the selection and implementation of auditory training regimens.

Abstract: A system and method of central auditory processing testing and evaluation provides for identifying clinically relevant neural synchrony in the auditory brainstem pathway. The system or method finds use as a tool to evaluate auditory processing disorders, and hence, potential auditory system and/or learning disabilities. The system or method may further find use in the selection and fitting of hearing corrective appliances such as hearing aid or cochlear implant devices and/or in the selection and implementation of auditory training regimens.