Coping Responses Among Athletes With Concussion, Orthopaedic Injuries, and Healthy Controls

2012 ◽  
Author(s):  
Anthony P. Kontos ◽  
R. J. Elbin ◽  
Renee N. Appaneal ◽  
Tracey Covassin
2013 ◽  
Vol 21 (4) ◽  
pp. 367-379 ◽  
Author(s):  
Anthony P. Kontos ◽  
R.J. Elbin ◽  
Renee Newcomer Appaneal ◽  
Tracey Covassin ◽  
Michael W. Collins

2020 ◽  
Vol 63 (1) ◽  
pp. 59-73 ◽  
Author(s):  
Panying Rong

Purpose The purpose of this article was to validate a novel acoustic analysis of oral diadochokinesis (DDK) in assessing bulbar motor involvement in amyotrophic lateral sclerosis (ALS). Method An automated acoustic DDK analysis was developed, which filtered out the voice features and extracted the envelope of the acoustic waveform reflecting the temporal pattern of syllable repetitions during an oral DDK task (i.e., repetitions of /tɑ/ at the maximum rate on 1 breath). Cycle-to-cycle temporal variability (cTV) of envelope fluctuations and syllable repetition rate (sylRate) were derived from the envelope and validated against 2 kinematic measures, which are tongue movement jitter (movJitter) and alternating tongue movement rate (AMR) during the DDK task, in 16 individuals with bulbar ALS and 18 healthy controls. After the validation, cTV, sylRate, movJitter, and AMR, along with an established clinical speech measure, that is, speaking rate (SR), were compared in their ability to (a) differentiate individuals with ALS from healthy controls and (b) detect early-stage bulbar declines in ALS. Results cTV and sylRate were significantly correlated with movJitter and AMR, respectively, across individuals with ALS and healthy controls, confirming the validity of the acoustic DDK analysis in extracting the temporal DDK pattern. Among all the acoustic and kinematic DDK measures, cTV showed the highest diagnostic accuracy (i.e., 0.87) with 80% sensitivity and 94% specificity in differentiating individuals with ALS from healthy controls, which outperformed the SR measure. Moreover, cTV showed a large increase during the early disease stage, which preceded the decline of SR. Conclusions This study provided preliminary validation of a novel automated acoustic DDK analysis in extracting a useful measure, namely, cTV, for early detection of bulbar ALS. This analysis overcame a major barrier in the existing acoustic DDK analysis, which is continuous voicing between syllables that interferes with syllable structures. This approach has potential clinical applications as a novel bulbar assessment.


2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.


1992 ◽  
Vol 7 (4) ◽  
pp. 653-653 ◽  
Author(s):  
Rudolf H. Moos ◽  
Penny L. Brennan ◽  
Mark R. Fondacaro ◽  
Bernice S. Moos

2013 ◽  
Author(s):  
Sheryl L. Reminger ◽  
Stefanie Ames ◽  
Laura Q. Rogers ◽  
Dian Canaday ◽  
Rita Trammell ◽  
...  

2017 ◽  
Vol 31 (7) ◽  
pp. 787-797 ◽  
Author(s):  
Jacqueline Uren ◽  
Susan M. Cotton ◽  
Eoin Killackey ◽  
Michael M. Saling ◽  
Kelly Allott

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