Recovery of cognitive and dynamic motor function following concussion
TL;DR: In order to fully examine the effects of concussion and determine the optimal time for a safe return to activity, a multi-factorial approach, including both cognitive and motor tasks, should be employed.
Abstract: Objective: Neuropsychological testing has been advocated as an important tool of proper post-concussion management. Although these measures provide information that can be used in the decision of when to return an individual to previous levels of physical activity, they provide little data on motor performance following injury. The purpose of this investigation was to examine the relationship between measures of dynamic motor performance and neuropsychological function following concussion over the course of 28 days. Methods: Participants completed two experimental protocols: gait stability and neuropsychological testing. The gait stability protocol measured whole-body centre of mass motion as subjects walked under conditions of divided and undivided attention. Neuropsychological testing consisted of a computerised battery of tests designed to assess memory, reaction time, processing speed and concussion symptoms. Correlation coefficients were computed between all neuropsychological and gait variables and comparisons of neuropsychological and gait stability post-concussion recovery curves were assessed. Results: Dynamic motor tasks, such as walking under varying conditions of attention, are complex and demanding undertakings, which require a longer recovery time following a concussion than cognitive measures. Little statistical relationship was found between the neuropsychological and gait variables, and the recovery curves of neuropsychological and gait domains were observed to be independent. Conclusions: In order to fully examine the effects of concussion and determine the optimal time for a safe return to activity, a multi-factorial approach, including both cognitive and motor tasks, should be employed.
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01 Jan 2015
TL;DR: Eighty-one percent athletes demonstrated a deficit from their baseline scores on one or more of the assessments, thus failing the concussion battery and giving objective evidence of a possible concussion.
Abstract: Context: Athletic participation accounts for 1.6-3.8 million concussions, or mild traumatic brain injuries (mTBI) every year in the United States. Accurate assessment and diagnosis of concussions is critical to protect athletes from further injury. The Fourth International Conference on Concussion in Sport Consensus Statement recommends a multifaceted concussion assessment which includes symptom inventories, postural stability assessment, and neurocognitive testing. The accuracy of each test is vital in correctly diagnosing concussions. The Balance Error Scoring System (BESS), Standardized Assessment of Concussion (SAC), and Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) are among the most commonly used assessment tools by NCAA athletic trainers. Objectives: (1) evaluate the false positive rate of a clinical concussion assessment battery (BESS, SAC, ImPACT) in a healthy Division I collegiate athlete population and (2) identify trends in pass/fail rates based on months elapsed from baseline testing. Design: Prospective longitudinal study. Setting: A large university in southeast Georgia. Participants: Fifty Division I collegiate athletes were recruited as participants. Forty-eight participants fulfilled the study requirements. Main Outcome Measure(s): Descriptive statistics were run for all demographic variables, along with scores on the various dependent variables. Failure rates for each test were then determined. Any increase in BESS score, decrease in SAC score, or change in an ImPACT composite score exceeding the reliable change index was classified as a false positive for the concussion battery. A one-way repeated measures ANOVA was run to determine changes in scores by testing time (baseline vs. current) and time elapsed from baseline. Tukey post-hoc testing and planned simple contrasts were evaluated as needed. Results: The concussion battery produced an 81% false positive rate. BESS produced the most false positives (62.5%), followed by ImPACT (33.3%), and SAC (27.1%). No significant interactions were found between the time from baseline testing and differences in scores from baseline to current testing. There was a significant main effect across time between BESS baseline scores and testing scores. Conclusions: Eighty-one percent athletes demonstrated a deficit from their baseline scores on one or more of the assessments, thus failing the concussion battery and giving objective evidence of a possible concussion. When a patient fails an objective assessment used to identify and diagnose a concussion, they are at risk of being removed from all participation. To return to participation, the current recommendation is a symptom free graduated return to play protocol taking about seven days to complete. This may result in significant playing time lost for the athlete.
1 citations
Cites background from "Recovery of cognitive and dynamic m..."
...Evaluation of concussion should include assessments of complex motor tasks which test the demands required of an athlete returning to play.(45) In one study, concussion participants performed worse for gait velocity, propulsion and braking....
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01 May 2017
1 citations
Cites result from "Recovery of cognitive and dynamic m..."
...3 DT research done on the young, athletic population has looked at athletes who have suffered a concussion.(38,39) These studies are in line with other gait and DT research, which show that concussed individuals have more conservative gait patterns than healthy control subjects....
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Dissertation•
01 Jan 2015
TL;DR: Age-Related Declines in Motor Performance 32 2.4.4d Dual Task 31 2.2.5 Return to Play 33 2.3.xiv CHAPTER 1: INTRODUCTION 1 1.1 Statement of Problem 1.2 Statement of Purpose and Hypotheses 7
Abstract: xiv CHAPTER 1: INTRODUCTION 1 1.1 Statement of Problem 1 1.2 Statement of Purpose and Hypotheses 7 Hypothesis 1: 7 Hypothesis 2: 7 Hypothesis 3: 8 CHAPTER 2: LITERATURE REVIEW 9 2.1 Epidemiology 9 2.2 Physiology 11 2.2.1 Acute Phase 11 2.2.2 Sub-Clinical Impacts 15 2.2.3 Sub-Acute Phase 16 2.3 Concussion Assessment and Management 18 2.4 Acute Sequelae 19 2.4.1 Symptoms 19 2.4.2 Neurostatus 21 2.4.3 Neurocognition 21 2.4.4 Motor Control 22 2.4.4a Reaction Time 26 2.4.4b Balance 26 2.4.4c Gait 29 2.4.4d Dual Task 31 2.4.4e Age-Related Declines in Motor Performance 32 2.5 Return to Play 33
1 citations
Cites background or methods from "Recovery of cognitive and dynamic m..."
...2.4.4d Dual Task Current concussion research has separately focused on cognitive and motor testing as a means to assess recovery following concussion (Parker et al., 2007)....
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...The recently concussed presented slower gait velocities, shorter stride lengths, greater stride times, and reduced COM and COP separation (Catena et al., 2007a, 2007b; Parker et al., 2005; Parker et al., 2006, 2007)....
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...…in gait velocity, step width, stride length, stride time, obstacle clearance, and center of mass (COM) motion in the coronal and sagittal planes, compared to matched controls (Catena et al., 2007a, 2007b; Fait et al., 2009; P. Fait et al., 2013; Parker et al., 2005; Parker et al., 2006, 2007)....
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...Parker and colleagues noted that the concussed subjects showed a slower gait on day two than they did on the final testing day (day 28) (Parker et al., 2005; Parker et al., 2006, 2007)....
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...4d Dual Task Current concussion research has separately focused on cognitive and motor testing as a means to assess recovery following concussion (Parker et al., 2007)....
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Dissertation•
12 Feb 2016
TL;DR: There is evidence that the SCAT3 Score and RTClin may be good sideline diagnostic or screening tools within the first 72 hours after concussion.
Abstract: Background: Concussion is a worldwide challenge and diagnosing, evaluating and monitoring injured athletes places a huge burden on even experienced clinicians. Each concussed athlete presents differently and each one should be treated individually. In an ideal world, enough resources should be available for neuropsychologists and neuropsychology tests to evaluate each athlete. In resource-limited areas, neuropsychologists are replaced by experienced clinicians for treating concussions; these clinicians use as many objective cognitive tests as are available. If computerised neuropsychology tests are unavailable, then low-cost, objective and fast sideline tests, like the clinical reaction time test, may be incorporated in the assessment battery protocol. No one test can be the sole cognitive assessment for recovery after a concussion. It is imperative that all these clinical tests practical limitations and benefits are known. Aims: This study’s primary aim was to compare the Sport Concussion Assessment Tool 3 (SCAT3) total score with the clinical reaction time test (RTClin). The secondary aim was to compare the two tests as recovery tracking evaluations in the days following a concussion. Methods: In one season (2014) a prospective cohort study of amateur collegiate rugby union players who suffered concussion (n = 46, mean age 21, range 18 to 33 years) out of 1 166 registered players were evaluated within 72 hours (Evaluation-1), then weekly (Evaluations 2 to 4) until they became asymptomatic (Evaluation-Asymptomatic) using the SCAT3 total score and RTClin tests. Results: Within the first 72 hours after a concussion the SCAT3 Score and the RTClin showed a moderately positive correlation of 0.47 (Spearman test) and p = 0.04. The Spearman correlation between asymptomatic athletes was poor (0.21 and p = 0.46). A comparison of the SCAT3 Score of the first evaluation (E-1, n = 19, mean 24, range 10 to 74) with the asymptomatic evaluation (EAsym, n = 14, mean 3.5, range 0 to 9) shows statistical significance (p < 0.01). The RTClin during E-1 (n = 19, mean 190 ms, range 168 to 258 ms) and, compared to E-Asym (n = 14, mean 179 ms, range 147 to 223 ms), came close to showing significance (p = 0.07). The recovery tracking showed the mean time for recovery as 6 days (n = 5, range 4 to 18 days). The SCAT3 Score for E-1 showed a mean of 24, E-Asym mean of 3 and mean iii iv difference of 18. The RTClin for E-1 showed a mean of 199 ms, E-Asym mean of 178 ms and a mean difference of 20 ms. There is a strong correlation of SCAT3 Score and RTClin over time, of 0.80, but p > 0.05. The recovery time correlation for SCAT3 Score was moderate (-0.56), but p > 0.05, and for RTClin recovery showed a strong correlation over time (-0.82), but also p > 0.05. Conclusions: In a low-resource environment with only clinical examinations, SCAT3 and RTClin as tools there is evidence that the SCAT3 Score and RTClin may be good sideline diagnostic or screening tools within the first 72 hours after concussion. When athletes become asymptomatic, the RTClin becomes more important for monitoring persistent cognitive impairment than the SCAT3 Score. Further research is needed with larger study populations to confirm the utility of the RTClin as part of a post-concussion assessment battery.
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References
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01 May 1990TL;DR: The Fourth Edition of Biomechanics as an Interdiscipline: A Review of the Fourth Edition focuses on biomechanical Electromyography, with a focus on the relationship between Electromyogram and Biomechinical Variables.
Abstract: Preface to the Fourth Edition. 1 Biomechanics as an Interdiscipline. 1.0 Introduction. 1.1 Measurement, Description, Analysis, and Assessment. 1.2 Biomechanics and its Relationship with Physiology and Anatomy. 1.3 Scope of the Textbook. 1.4 References. 2 Signal Processing. 2.0 Introduction. 2.1 Auto- and Cross-Correlation Analyses. 2.2 Frequency Analysis. 2.3 Ensemble Averaging of Repetitive Waveforms. 2.4 References. 3 Kinematics. 3.0 Historical Development and Complexity of Problem. 3.1 Kinematic Conventions. 3.2 Direct Measurement Techniques. 3.3 Imaging Measurement Techniques. 3.4 Processing of Raw Kinematic Data. 3.5 Calculation of Other Kinematic Variables. 3.6 Problems Based on Kinematic Data. 3.7 References. 4 Anthropometry. 4.0 Scope of Anthropometry in Movement Biomechanics. 4.1 Density, Mass, and Inertial Properties. 4.2 Direct Experimental Measures. 4.3 Muscle Anthropometry. 4.4 Problems Based on Anthropometric Data. 4.5 References. 5 Kinetics: Forces and Moments of Force. 5.0 Biomechanical Models. 5.1 Basic Link-Segment Equations-the Free-Body Diagram. 5.2 Force Transducers and Force Plates. 5.3 Bone-on-Bone Forces During Dynamic Conditions. 5.4 Problems Based on Kinetic and Kinematic Data. 5.5 References. 6 Mechanical Work, Energy, and Power. 6.0 Introduction. 6.1 Efficiency. 6.2 Forms of Energy Storage. 6.3 Calculation of Internal and External Work. 6.4 Power Balances at Joints and Within Segments. 6.5 Problems Based on Kinetic and Kinematic Data. 6.6 References. 7 Three-Dimensional Kinematics and Kinetics. 7.0 Introduction. 7.1 Axes Systems. 7.2 Marker and Anatomical Axes Systems. 7.3 Determination of Segment Angular Velocities and Accelerations. 7.4 Kinetic Analysis of Reaction Forces and Moments. 7.5 Suggested Further Reading. 7.6 References. 8 Synthesis of Human Movement-Forward Solutions. 8.0 Introduction. 8.1 Review of Forward Solution Models. 8.2 Mathematical Formulation. 8.3 System Energy. 8.4 External Forces and Torques. 8.5 Designation of Joints. 8.6 Illustrative Example. 8.7 Conclusions. 8.8 References. 9 Muscle Mechanics. 9.0 Introduction. 9.1 Force-Length Characteristics of Muscles. 9.2 Force-Velocity Characteristics. 9.3 Muscle Modeling. 9.4 References. 10 Kinesiological Electromyography. 10.0 Introduction. 10.1 Electrophysiology of Muscle Contraction. 10.2 Recording of the Electromyogram. 10.3 Processing of the Electromyogram,. 10.4 Relationship between Electromyogram and Biomechanical Variables. 10.5 References. 11 Biomechanical Movement Synergies. 11.0 Introduction. 11.1 The Support Moment Synergy. 11.2 Medial/Lateral and Anterior/Posterior Balance in Standing. 11.3 Dynamic Balance during Walking. 11.4 References. APPENDICES. A. Kinematic, Kinetic, and Energy Data. Figure A.1 Walking Trial-Marker Locations and Mass and Frame Rate Information. Table A.1 Raw Coordinate Data (cm). Table A.2( a ) Filtered Marker Kinematics-Rib Cage and Greater Trochanter (Hip). Table A.2( b ) Filtered Marker Kinematics-Femoral Lateral Epicondyle (Knee) and Head of Fibula. Table A.2( c ) Filtered Marker Kinematics-Lateral Malleolus (Ankle) and Heel. Table A.2( d ) Filtered Marker Kinematics-Fifth Metatarsal and Toe. Table A.3( a ) Linear and Angular Kinematics-Foot. Table A.3( b ) Linear and Angular Kinematics-Leg. Table A.3( c ) Linear and Angular Kinematics-Thigh. Table A.3( d ) Linear and Angular Kinematics-1/2 HAT. Table A.4 Relative Joint Angular Kinematics-Ankle, Knee, and Hip. Table A.5( a ) Reaction Forces and Moments of Force-Ankle and Knee. Table A.5( b ) Reaction Forces and Moments of Force-Hip. Table A.6 Segment Potential, Kinetic, and Total Energies-Foot, Leg, Thigh, and1/2 HAT. Table A.7 Power Generation/Absorption and Transfer-Ankle, Knee, and Hip. B. Units and Definitions Related to Biomechanical and Electromyographical Measurements. Table B.1 Base SI Units. Table B.2 Derived SI Units. Index.
9,092 citations
TL;DR: A study with 40 normal adult subjects indicates that the ANT produces reliable single subject estimates of alerting, orienting, and executive function, and further suggests that the efficiencies of these three networks are uncorrelated.
Abstract: In recent years, three attentional networks have been defined in anatomical and functional terms. These functions involve alerting, orienting, and executive attention. Reaction time measures can be used to quantify the processing efficiency within each of these three networks. The Attention Network Test (ANT) is designed to evaluate alerting, orienting, and executive attention within a single 30-min testing session that can be easily performed by children, patients, and monkeys. A study with 40 normal adult subjects indicates that the ANT produces reliable single subject estimates of alerting, orienting, and executive function, and further suggests that the efficiencies of these three networks are uncorrelated. There are, however, some interactions in which alerting and orienting can modulate the degree of interference from flankers. This procedure may prove to be convenient and useful in evaluating attentional abnormalities associated with cases of brain injury, stroke, schizophrenia, and attention-deficit disorder. The ANT may also serve as an activation task for neuroimaging studies and as a phenotype for the study of the influence of genes on attentional networks.
3,166 citations
TL;DR: In this paper, a study of 1631 football players from 15 US colleges found that players with concussions exhibited more severe symptoms (mean GSC score 20.93 [95% confidence interval {CI, 15.65-26.21] points higher than that of controls), cognitive impairments (mean SAC score 2.94 [ 95% CI, 1.41 to 2.06], cognitive functioning improved to baseline levels within 5 to 7 days (day 7 SAC mean difference, −0.33;
Abstract: ContextLack of empirical data on recovery time following sport-related concussion
hampers clinical decision making about return to play after injury.ObjectiveTo prospectively measure immediate effects and natural recovery course
relating to symptoms, cognitive functioning, and postural stability following
sport-related concussion.Design, Setting, and ParticipantsProspective cohort study of 1631 football players from 15 US colleges.
All players underwent preseason baseline testing on concussion assessment
measures in 1999, 2000, and 2001. Ninety-four players with concussion (based
on American Academy of Neurology criteria) and 56 noninjured controls underwent
assessment of symptoms, cognitive functioning, and postural stability immediately,
3 hours, and 1, 2, 3, 5, 7, and 90 days after injury.Main Outcome MeasuresScores on the Graded Symptom Checklist (GSC), Standardized Assessment
of Concussion (SAC), Balance Error Scoring System (BESS), and a neuropsychological
test battery.ResultsNo player with concussion was excluded from participation; 79 players
with concussion (84%) completed the protocol through day 90. Players with
concussion exhibited more severe symptoms (mean GSC score 20.93 [95% confidence
interval {CI}, 15.65-26.21] points higher than that of controls), cognitive
impairment (mean SAC score 2.94 [95% CI, 1.50-4.38] points lower than that
of controls), and balance problems (mean BESS score 5.81 [95% CI, –0.67
to 12.30] points higher than that of controls) immediately after concussion.
On average, symptoms gradually resolved by day 7 (GSC mean difference, 0.33;
95% CI, −1.41 to 2.06), cognitive functioning improved to baseline levels
within 5 to 7 days (day 7 SAC mean difference, −0.03; 95% CI, −1.33
to 1.26), and balance deficits dissipated within 3 to 5 days after injury
(day 5 BESS mean difference, −0.31; 95% CI, −3.02 to 2.40). Mild
impairments in cognitive processing and verbal memory evident on neuropsychological
testing 2 days after concussion resolved by day 7. There were no significant
differences in symptoms or functional impairments in the concussion and control
groups 90 days after concussion.ConclusionsCollegiate football players may require several days for recovery of
symptoms, cognitive dysfunction, and postural instability after concussion.
Further research is required to determine factors that predict variability
in recovery time after concussion. Standardized measurement of postconcussive
symptoms, cognitive functioning, and postural stability may enhance clinical
management of athletes recovering from concussion.
1,484 citations
TL;DR: The recommendations for concussion management provided here are based on the most current research and divided into sections on education and prevention, documentation and legal aspects, evaluation and return to play, and other considerations.
Abstract: Objective: To provide athletic trainers, physicians, and other health care professionals with best-practice guidelines for the management of sport-related concussions. Background: An estimated 3.8 ...
1,026 citations
TL;DR: A subroutine package is presented in which the amount of smoothing on a set of n noisy datapoints is determined from the data by means of the Generalized Cross-Validation or predicted Mean-Squared Error criteria of Wahba and her collaborators.
987 citations