Sports Concussion And Mild Traumatic Brain Injury Assessment Is Enhanced With Portable, Non-invasive Biosensor Arrays

2015 ◽  
Vol 47 ◽  
pp. 11 ◽  
Author(s):  
Adam J. Simon ◽  
David M. Devilbiss
2014 ◽  
Vol 29 (6) ◽  
pp. 595-596 ◽  
Author(s):  
A. Simon ◽  
K. Tatsuakawa ◽  
J. Van Gelder ◽  
H. Ashrafiuon ◽  
D. Devilbiss

Brain Injury ◽  
2019 ◽  
Vol 33 (8) ◽  
pp. 1021-1031 ◽  
Author(s):  
Jennyfer Ansado ◽  
Aaron Blunt ◽  
Jen-Kai Chen ◽  
Lisa Koski ◽  
Alain Ptito

Author(s):  
Natalie Le Sage ◽  
Pier-Alexandre Tardif ◽  
Jérôme Frenette ◽  
Marcel Émond ◽  
Jean-Marc Chauny ◽  
...  

ABSTRACT:This study assessed whether S-100β protein could be measured in urine when detectable in plasma after a mild traumatic brain injury (mTBI). Clinical data, plasma and urine samples were collected for the 46 adult patients prospectively enrolled in the emergency department (ED) of a Level 1 trauma center. S-100β protein concentrations were analysed using ELISA. S-100β protein was detectable in 91% and 71% of plasma and urine samples, but values were not correlated (r = 0.002). Urine sampling would have been a non-invasive procedure, but it does not appear to be useful in the ED during the acute phase after an mTBI.


1997 ◽  
Vol 12 (4) ◽  
pp. 380-381
Author(s):  
C. Paniak ◽  
G. Toller-Lobe ◽  
J. Nagy ◽  
A. Stock ◽  
M. I. Goltz

Over the past several years, there has been a search for an objective biomarker to detect the presence of mild traumatic brain injury (mTBI)/concussion, especially one of a non-invasive nature. Recent advances and laboratory experimentation involving the abnormal oculomotor system in these individuals has suggested one very strong candidate: convergence peak velocity, which was found to be significantly reduced in all subjects tested. This vergence parameter can be rapidly and easily assessed using automated eye movement recording and analysis systems in a full range of environments, including the sports arena and the military theater, as well as one’s optometric practice, with a very low false positive rate, thus improving the early clinical diagnosis.


PM&R ◽  
2011 ◽  
Vol 3 ◽  
pp. S413-S424 ◽  
Author(s):  
Peter G. Gonzalez ◽  
Matthew T. Walker

2021 ◽  
Vol 11 (11) ◽  
pp. 1369
Author(s):  
Hon-Ping Ma ◽  
Ju-Chi Ou ◽  
Kai-Yun Chen ◽  
Kuo-Hsing Liao ◽  
Shuo-Jhen Kang ◽  
...  

To identify a screening tool for poor self-reported sleep quality at 12 weeks according to non-invasive measurements and patients’ characteristics in the first week after mild traumatic brain injury (mTBI), data from 473 mTBI participants were collected and follow-ups were performed at 12 weeks. Patients with previous poor self-reported sleep quality prior to the injury were excluded. Patients were then divided into two groups at 12 weeks according to the Pittsburgh Sleep Quality Index based on whether or not they experienced poor sleep quality. The analysis was performed on personal profiles and heart rate variability (HRV) for 1 week. After analyzing the non-invasive measurements and characteristics of mTBI patients who did not complain of poor sleep quality, several factors were found to be relevant to the delayed onset of poor sleep quality, including age, gender, and HRV measurements. The HRV–age–gender (HAG) index was proposed and found to have 100% sensitivity (cut-off, 7; specificity, 0.537) to predicting whether the patient will experience poor sleep quality after mTBI at the 12-week follow-up. The HAG index helps us to identify patients with mTBI who have no sleep quality complaints but are prone to developing poor self-reported sleep quality. Additional interventions to improve sleep quality would be important for these particular patients in the future.


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