Evaluating a Novel Method of EEG Evoked Response Potential Analysis in Concussion Assessment
Status: | Completed |
---|---|
Conditions: | Hospital, Neurology, Neurology |
Therapuetic Areas: | Neurology, Other |
Healthy: | No |
Age Range: | 15 - 50 |
Updated: | 9/29/2018 |
Start Date: | January 26, 2017 |
End Date: | January 16, 2018 |
Evaluating a Novel Method of EEG Evoked Response Potential Analysis in Concussion Assessment - A GE Healthcare Companion Study: Advanced MRI Applications for Mild Traumatic Brain Injury-Phase 2 (mTBI-phase2)
mTBI is widely recognized as a major public health concern in the United States and
worldwide. mTBI diagnosis remains a clinical challenge as no single test can diagnose every
concussion. Recent advances in EEG evoked response potential analysis have led to a novel
technique for assessing brain network activation (BNA) patterns. This study purpose is to
study this BNA technology in individuals who have sustained a concussion.
worldwide. mTBI diagnosis remains a clinical challenge as no single test can diagnose every
concussion. Recent advances in EEG evoked response potential analysis have led to a novel
technique for assessing brain network activation (BNA) patterns. This study purpose is to
study this BNA technology in individuals who have sustained a concussion.
Mild traumatic brain injury (mTBI), also known as concussion, occurs commonly in sport and
Motor Vehicle accidents. The Centers for Disease Control and Prevention estimate that as many
as 3.8 million sport-related concussions occur annually in the United States. Despite ongoing
research, there is no highly sensitive clinical test for cognitive function that can be
rapidly applied in a sporting environment. This makes the clinical diagnosis of concussion
particularly difficult, as the clinical presentation of concussion is highly variable with
symptoms often evolving over time. Furthermore, with less than 10% of concussions resulting
in loss of consciousness, self-reported symptom presence may be the only initial evidence of
a concussion. These factors make concussion a challenging injury to diagnose. Given the
variability in concussion presentations, there is no single test that can diagnose a
concussion.
ElMindA, the sponsor of this study, has developed a novel method to automatically reveal
functional networks of brain activity based on analysis of EEG Event Related Potential (ERP)
data. This technological platform is capable of providing new metrics of brain function that
can assist in patient evaluation and management. The analysis is done in two separate
processes that are entirely separate and are performed independently of one another.
Reference Brain Network Models of EEG data were recorded and analyzed from several groups of
subjects to establish a set of group patterns that characterized the brain network activity
of the group. EEG data from a single subject are processed to enable subject evaluation, as
compared to the established group patterns. This individual analysis is the basis of the BNA
scores computed for an individual subject.
Therefore, this investigation is designed to evaluate the clinical utility of ElMindA's BNA
scores in detecting and managing concussive injuries.
Motor Vehicle accidents. The Centers for Disease Control and Prevention estimate that as many
as 3.8 million sport-related concussions occur annually in the United States. Despite ongoing
research, there is no highly sensitive clinical test for cognitive function that can be
rapidly applied in a sporting environment. This makes the clinical diagnosis of concussion
particularly difficult, as the clinical presentation of concussion is highly variable with
symptoms often evolving over time. Furthermore, with less than 10% of concussions resulting
in loss of consciousness, self-reported symptom presence may be the only initial evidence of
a concussion. These factors make concussion a challenging injury to diagnose. Given the
variability in concussion presentations, there is no single test that can diagnose a
concussion.
ElMindA, the sponsor of this study, has developed a novel method to automatically reveal
functional networks of brain activity based on analysis of EEG Event Related Potential (ERP)
data. This technological platform is capable of providing new metrics of brain function that
can assist in patient evaluation and management. The analysis is done in two separate
processes that are entirely separate and are performed independently of one another.
Reference Brain Network Models of EEG data were recorded and analyzed from several groups of
subjects to establish a set of group patterns that characterized the brain network activity
of the group. EEG data from a single subject are processed to enable subject evaluation, as
compared to the established group patterns. This individual analysis is the basis of the BNA
scores computed for an individual subject.
Therefore, this investigation is designed to evaluate the clinical utility of ElMindA's BNA
scores in detecting and managing concussive injuries.
Inclusion Criteria:
- Enrolled in Arm 1 -mTBI group in the GE study: Advanced MRI Applications for Mild
Traumatic Brain Injury-Phase 2 study
- Enrolled in Arm 2 -non TBI group in the GE study: Advanced MRI Applications for Mild
Traumatic Brain Injury-Phase 2 study
- Males and females Aged 15-50
- Willingness to participate in the companion study and the ability to give informed
assent (for children) and/or consent (for the parent of a minor or adults aged 18
years of age or older for themselves).
Exclusion Criteria:
- Hair types which might preclude appropriate scalp electrode cap fit. E.g: dread locks,
corn rows etc.
- Significant sensory deficit e.g.: Deafness, and/or blindness
- Open scalp wound
- Active head lice infection
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University of Pittsburgh The University of Pittsburgh is a state-related research university, founded as the...
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