Detection of Traumatic Brain Injury Using Single Channel Electroencephalogram in Mice

Author(s):  
A. Sutandi ◽  
N. Dhillon ◽  
M. Lim ◽  
H. Cao ◽  
D. Si
Biofeedback ◽  
2013 ◽  
Vol 41 (4) ◽  
pp. 158-173 ◽  
Author(s):  
Michael Thompson ◽  
Lynda Thompson ◽  
Andrea Reid-Chung ◽  
James Thompson

Impairments that may result from a mild traumatic brain injury (TBI) or concussion can be both severe and long-lasting. This article will list some of the common persisting symptoms that may occur and give a brief description of the neuropathological processes that can be triggered by TBI, including diffuse axonal injury and its effects on the mitochondrial Kreb's cycle and the production of adenosine triphosphate, the brain's source of energy. This is followed by a summary of a comprehensive assessment process that includes quantitative electroencephalography, evoked potentials, heart rate variability (HRV) measures, neuropsychological testing, and blood and urine analysis. Details concerning a neurophysiological approach to effective treatment are given. These include conventional single-channel neurofeedback (NFB), also called brain-computer interface training, low-resolution electromagnetic tomography z-score neurofeedback, HRV training, and counseling on diet, sleep, and exercise. The authors expand the discussion on their treatment approach to include a neuroanatomical explanation of why the practitioner should consider combining the NFB training with HRV training.


Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2779
Author(s):  
Navjodh Singh Dhillon ◽  
Agustinus Sutandi ◽  
Manoj Vishwanath ◽  
Miranda M. Lim ◽  
Hung Cao ◽  
...  

Traumatic Brain Injury (TBI) is a common cause of death and disability. However, existing tools for TBI diagnosis are either subjective or require extensive clinical setup and expertise. The increasing affordability and reduction in the size of relatively high-performance computing systems combined with promising results from TBI related machine learning research make it possible to create compact and portable systems for early detection of TBI. This work describes a Raspberry Pi based portable, real-time data acquisition, and automated processing system that uses machine learning to efficiently identify TBI and automatically score sleep stages from a single-channel Electroencephalogram (EEG) signal. We discuss the design, implementation, and verification of the system that can digitize the EEG signal using an Analog to Digital Converter (ADC) and perform real-time signal classification to detect the presence of mild TBI (mTBI). We utilize Convolutional Neural Networks (CNN) and XGBoost based predictive models to evaluate the performance and demonstrate the versatility of the system to operate with multiple types of predictive models. We achieve a peak classification accuracy of more than 90% with a classification time of less than 1 s across 16–64 s epochs for TBI vs. control conditions. This work can enable the development of systems suitable for field use without requiring specialized medical equipment for early TBI detection applications and TBI research. Further, this work opens avenues to implement connected, real-time TBI related health and wellness monitoring systems.


Biosensors ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 320
Author(s):  
Alyse D. Krausz ◽  
Frederick K. Korley ◽  
Mark A. Burns

Traumatic brain injury (TBI) is a leading cause of global morbidity and mortality, partially due to the lack of sensitive diagnostic methods and efficacious therapies. Panels of protein biomarkers have been proposed as a way of diagnosing and monitoring TBI. To measure multiple TBI biomarkers simultaneously, we present a variable height microfluidic device consisting of a single channel that varies in height between the inlet and outlet and can passively multiplex bead-based immunoassays by trapping assay beads at the point where their diameter matches the channel height. We developed bead-based quantum dot-linked immunosorbent assays (QLISAs) for interleukin-6 (IL-6), glial fibrillary acidic protein (GFAP), and interleukin-8 (IL-8) using DynabeadsTM M-450, M-270, and MyOneTM, respectively. The IL-6 and GFAP QLISAs were successfully multiplexed using a variable height channel that ranged in height from ~7.6 µm at the inlet to ~2.1 µm at the outlet. The IL-6, GFAP, and IL-8 QLISAs were also multiplexed using a channel that ranged in height from ~6.3 µm at the inlet to ~0.9 µm at the outlet. Our system can keep pace with TBI biomarker discovery and validation, as additional protein biomarkers can be multiplexed simply by adding in antibody-conjugated beads of different diameters.


Biofeedback ◽  
2015 ◽  
Vol 43 (1) ◽  
pp. 31-37 ◽  
Author(s):  
J. Lawrence Thomas ◽  
Mark L. Smith

Traumatic brain injuries constitute significant health and societal problems which can be ameliorated with some recent developments in neurofeedback. The field of neurofeedback has evolved from single channel to multiple-site training, and with LORETA Z-score training, deeper levels of the brain can reached. Neurofeedback for traumatic brain injury patients may provide improvements never before possible.


2019 ◽  
Vol 42 ◽  
Author(s):  
Colleen M. Kelley ◽  
Larry L. Jacoby

Abstract Cognitive control constrains retrieval processing and so restricts what comes to mind as input to the attribution system. We review evidence that older adults, patients with Alzheimer's disease, and people with traumatic brain injury exert less cognitive control during retrieval, and so are susceptible to memory misattributions in the form of dramatic levels of false remembering.


2020 ◽  
Vol 5 (1) ◽  
pp. 88-96
Author(s):  
Mary R. T. Kennedy

Purpose The purpose of this clinical focus article is to provide speech-language pathologists with a brief update of the evidence that provides possible explanations for our experiences while coaching college students with traumatic brain injury (TBI). Method The narrative text provides readers with lessons we learned as speech-language pathologists functioning as cognitive coaches to college students with TBI. This is not meant to be an exhaustive list, but rather to consider the recent scientific evidence that will help our understanding of how best to coach these college students. Conclusion Four lessons are described. Lesson 1 focuses on the value of self-reported responses to surveys, questionnaires, and interviews. Lesson 2 addresses the use of immediate/proximal goals as leverage for students to update their sense of self and how their abilities and disabilities may alter their more distal goals. Lesson 3 reminds us that teamwork is necessary to address the complex issues facing these students, which include their developmental stage, the sudden onset of trauma to the brain, and having to navigate going to college with a TBI. Lesson 4 focuses on the need for college students with TBI to learn how to self-advocate with instructors, family, and peers.


2019 ◽  
Vol 28 (3) ◽  
pp. 1363-1370 ◽  
Author(s):  
Jessica Brown ◽  
Katy O'Brien ◽  
Kelly Knollman-Porter ◽  
Tracey Wallace

Purpose The Centers for Disease Control and Prevention (CDC) recently released guidelines for rehabilitation professionals regarding the care of children with mild traumatic brain injury (mTBI). Given that mTBI impacts millions of children each year and can be particularly detrimental to children in middle and high school age groups, access to universal recommendations for management of postinjury symptoms is ideal. Method This viewpoint article examines the CDC guidelines and applies these recommendations directly to speech-language pathology practices. In particular, education, assessment, treatment, team management, and ongoing monitoring are discussed. In addition, suggested timelines regarding implementation of services by speech-language pathologists (SLPs) are provided. Specific focus is placed on adolescents (i.e., middle and high school–age children). Results SLPs are critical members of the rehabilitation team working with children with mTBI and should be involved in education, symptom monitoring, and assessment early in the recovery process. SLPs can also provide unique insight into the cognitive and linguistic challenges of these students and can serve to bridge the gap among rehabilitation and school-based professionals, the adolescent with brain injury, and their parents. Conclusion The guidelines provided by the CDC, along with evidence from the field of speech pathology, can guide SLPs to advocate for involvement in the care of adolescents with mTBI. More research is needed to enhance the evidence base for direct assessment and treatment with this population; however, SLPs can use their extensive knowledge and experience working with individuals with traumatic brain injury as a starting point for post-mTBI care.


ASHA Leader ◽  
2010 ◽  
Vol 15 (13) ◽  
pp. 38-38
Author(s):  
G. Gayle Kelley

Sign in / Sign up

Export Citation Format

Share Document