A Multifaceted Approach to Interpreting Reaction Time Deficits After Adolescent Concussion.

CONTEXT: Reaction time (RT) is a critical element of return to participation (RTP), and impairments have been linked to subsequent injury after a concussion. Current RT assessments have limitations in clinical feasibility and in the identification of subtle deficits after concussion symptom resolution. OBJECTIVES: To examine the utility of RT measurements (clinical drop stick, simple stimulus-response, single-task Stroop, and dual-task Stroop) to differentiate between adolescents with concussion and uninjured control individuals at initial assessment and RTP. DESIGN: Prospective cohort study. SETTING: A pediatric sports medicine center associated with a regional tertiary care hospital. PATIENTS OR OTHER PARTICIPANTS: Twenty-seven adolescents with a concussion (mean age = 14.8 ± 2.1 years; 52% female; tested 7.0 ± 3.3 days postconcussion) and 21 uninjured control individuals (mean age = 15.5 ± 1.6 years; 48% female). MAIN OUTCOME MEASURE(S): Participants completed the Post-Concussion Symptoms Inventory (PCSI) and a battery of RT tests: clinical drop stick, simple stimulus-response, single-task Stroop, and dual-task Stroop. RESULTS: The concussion group demonstrated slower clinical drop stick (ß = 58.8; 95% CI = 29.2, 88.3; P < .001) and dual-task Stroop (ß = 464.2; 95% CI = 318.4, 610.0; P < .001) RT measures at the initial assessment than the uninjured control group. At 1-month follow up, the concussion group displayed slower clinical drop stick (238.9 ± 25.9 versus 188.1 ± 21.7 milliseconds; P < .001; d = 2.10), single-task Stroop (1527.8 ± 204.5 versus 1319.8 ± 133.5 milliseconds; P = .001; d = 1.20), and dual-task Stroop (1549.9 ± 264.7 versus 1341.5 ± 114.7 milliseconds; P = .002; d = 1.04) RT than the control group, respectively, while symptom severity was similar between groups (7.4 ± 11.2 versus 5.3 ± 6.5; P = .44; d = 0.24). Classification accuracy and area under the curve (AUC) values were highest for the clinical drop stick (85.1% accuracy, AUC = 0.86, P < .001) and dual-task Stroop (87.2% accuracy, AUC = 0.92, P < .002) RT variables at initial evaluation. CONCLUSIONS: Adolescents recovering from concussion may have initial RT deficits that persist despite symptom recovery. The clinical drop stick and dual-task Stroop RT measures demonstrated high clinical utility given high classification accuracy, sensitivity, and specificity to detect postconcussion RT deficits and may be considered for initial and RTP assessment.

Ankle Sprain History Does Not Significantly Alter Single- and Dual-Task Spatiotemporal Gait Mechanics.

CONTEXT: Single- and dual-task walking gait assessments have been used to identify persistent movement and cognitive dysfunction among athletes with concussions. However, it is unclear whether previous ankle sprain injuries confound these outcomes during baseline testing. The purpose of this study was to determine the effects of (1) ankle sprain history and (2) time since prior ankle sprain injury on single- and dual-task spatiotemporal gait outcomes and cognitive measures. DESIGN: Cross-sectional study. METHODS: We assessed 60 college Division-I athletes (31 with ankle sprain history; 13 females and 18 males, 19.3 [0.8] y; 29 with no ankle sprain history, 14 females and 15 males, 19.7 [0.9] y) who completed injury history forms and underwent concussion baseline testing. Athletes completed single- and dual-task gait assessments by walking back and forth along an 8-m walkway for 40 seconds. Athletes wore a smartphone with an associated mobile application on their lumbar spine to record spatiotemporal gait parameters and dual-task cognitive performance. Separate multivariate analyses of variance were used to assess the effects of ankle sprain injury history on spatiotemporal measures, gait variability, and cognitive performance. We performed a multivariate regression subanalysis on athletes who reported time since injury (n = 23) to assess temporal effects on gait and cognitive performance. RESULTS: Athletes with and without a history of ankle sprains had comparable spatiotemporal and gait variability outcomes during single- (P = .42; P = .13) and dual-task (P = .75; P = .55) conditions. Additionally, ankle sprain injury history did not significantly influence cognitive performance (P = .35). Finally, time since ankle sprain did not significantly affect single- (P = .75) and dual-task gait (P = .69), nor cognitive performance (P = .19). CONCLUSIONS: Ankle sprain injury history did not significantly alter spatiotemporal gait outcomes nor cognitive performance during this common clinical assessment. Future studies may consider including athletes with ankle sprain injury history during concussion assessments.

Smartphone- and Paper-Based Delivery of Balance Intervention for Older Adults Are Equally Effective, Enjoyable, and of High Fidelity: A Randomized Controlled Trial.

Home-based rehabilitation programs for older adults have demonstrated effectiveness, desirability, and reduced burden. However, the feasibility and effectiveness of balance-intervention training delivered through traditional paper-versus novel smartphone-based methods is unknown. Therefore, the purpose of this study was to evaluate if a home-based balance-intervention program could equally improve balance performance when delivered via smartphone or paper among adults over the age of 65. A total of 31 older adults were randomized into either a paper or phone group and completed a 4-week asynchronous self-guided balance intervention across 12 sessions for approximately 30 min per session. Baseline, 4-week, and 8-week walking and standing balance evaluations were performed, with exercise duration and adherence recorded. Additional self-reported measures were collected regarding the enjoyment, usability, difficulty, and length of the exercise program. Twenty-nine participants completed the balance program and three assessments, with no group differences found for any outcome measure. Older adults demonstrated an approximately 0.06 m/s faster gait velocity and modified balance strategies during walking and standing conditions following the intervention protocol. Participants further self-reported similar enjoyment, difficulty, and exercise effectiveness. Results of this study demonstrated the potential to safely deliver home-based interventions as well as the feasibility and effectiveness of delivering balance intervention through a smartphone-based application.

A novel smartphone application is reliable for repeat administration and comparable to the Tekscan Strideway for spatiotemporal gait.

Smartphone applications are increasingly being used to measure gait due to their portability and cost-effectiveness. Important reliability metrics are not available for most of these devices. The purpose of this article was to evaluate the test-retest reliability and concurrent validity of spatiotemporal gait using the novel Gait Analyzer smartphone application compared to the Tekscan Strideway. Healthy participants (n=23) completed 12 trials of 10-meter walking, at two separate time points, using Gait Analyzer and while walking across the Tekscan Strideway. The results suggest excellent test-retest reliability for the Gait Analyzer and good test-retest reliability for the Tekscan Strideway for both velocity and cadence. At both time points, these devices were moderately to strongly correlated to one another for both velocity and cadence. These data suggest that the Gait Analyzer and Tekscan Strideway are reliable over time and can comparably calculate velocity and cadence.

Three-Day Remote Monitoring of Gait Among Young and Older Adults Using Participants' Personal Smartphones.

Conventional one-time gait analyses do not evaluate walking across more than a few steps, cannot monitor changes longitudinally, and do not reflect performance in real-life environments. To successfully quantify age-related gait decrement, technology that can continuously monitor gait is vital. This study examined the feasibility and validity for participant smartphones to remotely assess gait. In addition, the authors investigated whether smartphone-derived measures could differentiate between young and older adults (fallers and nonfallers). A total of 63 adults completed clinical and gait assessment in the laboratory and donned their smartphones for 3 days in the real-life environment. A custom-built Android application collected triaxial accelerations with spatiotemporal gait measures computed and compared between groups. Across 11 brands and 10 Android versions, smartphone-derived gait parameters were valid. Furthermore, results indicated age-related differences in walking during the 3-day assessment. However, no disparities were found between older adult groups. Smartphone-based evaluations may improve real-life screening of adults with gait deficits.

Trunk and pelvis biomechanical responses in children with cerebral palsy and with typical development during horseback riding.

BACKGROUND: Children with cerebral palsy (CP) have poor postural control. Horseback riding (HR) is an alternative treatment shown to improve postural control among children with CP. However, there is a paucity of research investigating the underlying mechanisms responsible for improving postural control during HR. RESEARCH QUESTION: What are the three-dimensional biomechanical responses of the trunk and pelvis during HR among children with CP and with typical development (TD)? METHODS: The participants, aged 4-12 years old, were inexperienced horseback riders, consisting of 10 children with TD and 10 children with spastic diplegia CP (SDCP) with GMFCS level III. Participants donned inertial measurement units (IMU) on their trunk and pelvis in order to measure angular displacement and velocity. An additional IMU was placed on the horse's lumbosacral joint. The mean absolute relative phase (MARP) and deviation phase (DP) were calculated from each plane of movement for the angular displacement and velocity across the gait cycle of the horse. Differences between groups were analyzed using independent t-tests. RESULTS: The MARP in the frontal plane was lower in the SDCP group, when compared to the TD group (p = 0.01). Additionally, no differences were found between groups for the DP along all three axes. However, the TD group demonstrated greater pelvic movement variability in relation to the horse's pelvis movement, when compared to the SDCP group. SIGNIFICANCE: Children with SDCP demonstrated an in-phase coupling pattern with decreased variability of pelvic movement in relation to the horse's pelvis.

Reliability and Minimal Detectable Change for a Smartphone-Based Motor-Cognitive Assessment: Implications for Concussion Management.

Our purpose was to investigate the reliability and minimal detectable change characteristics of a smartphone-based assessment of single- and dual-task gait and cognitive performance. Uninjured adolescent athletes (n = 17; mean age = 16.6, SD = 1.3 y; 47% female) completed assessments initially and again 4 weeks later. The authors collected data via an automated smartphone-based application while participants completed a series of tasks under (1) single-task cognitive, (2) single-task gait, and (3) dual-task cognitive-gait conditions. The cognitive task was a series of continuous auditory Stroop cues. Average gait speed was consistent between testing sessions in single-task (0.98, SD = 0.21 vs 0.96, SD = 0.19 m/s; P = .60; r = .89) and dual-task (0.92, SD = 0.22 vs 0.89, SD = 0.22 m/s; P = .37; r = .88) conditions. Response accuracy was moderately consistent between assessments in single-task standing (82.3% accurate, SD = 17.9% vs 84.6% accurate, SD = 20.1%; P = .64; r = .52) and dual-task gait (89.4% accurate, SD = 15.9% vs 85.8% accurate, SD = 20.2%; P = .23; r = .81) conditions. Our results indicate automated motor-cognitive dual-task outcomes obtained within a smartphone-based assessment are consistent across a 1-month period. Further research is required to understand how this assessment performs in the setting of sport-related concussion. Given the relative reliability of values obtained, a smartphone-based evaluation may be considered for use to evaluate changes across time among adolescents, postconcussion.

Smartphone Monitoring of Gait and Balance During Irregular Surface Walking and Obstacle Crossing.

As gait adaptation is vital for successful locomotion, the development of field-based tools to quantify gait in challenging real-world environments are crucial. The aims of this study were to assess the reliability and validity of a smartphone-based gait and balance assessment while walking on unobstructed and obstructed terrains using two phone placements. Furthermore, age-related differences in smartphone-derived gait strategies when navigating different walking conditions and environments were evaluated. By providing a method for evaluating gait in the simulated free-living environment, results of this study can elucidate the strategies young and older adults utilize to navigate obstructed and unobstructed walking paths. A total of 24 young and older adults ambulated indoors and outdoors under three conditions: level walking, irregular surface walking, and obstacle crossing. Android smartphones placed on the body and in a bag computed spatiotemporal gait (i.e., velocity, step time, step length, and cadence) and balance (i.e., center of mass (COM) displacement), with motion capture and video used to validate parameters in the laboratory and free-living environments, respectively. Reliability was evaluated using the intraclass correlation coefficient and validity was evaluated using Pearson's correlation and Bland-Altman analysis. A three-way ANOVA was used to assess outcome measures across group, condition, and environment. Results showed that smartphones were reliable and valid for measuring gait across all conditions, phone placements, and environments (ICC2,1: 0.606-0.965; Pearson's r: 0.72-1.00). Although body and bag placement demonstrated similar results for spatiotemporal parameters, accurate vertical COM displacement could only be obtained from the body placement. Older adults demonstrated a longer step time and lower cadence only during obstacle crossing, when compared to young adults. Furthermore, environmental differences in walking strategy were observed only during irregular surface walking. In particular, participants utilized a faster gait speed and a longer step length in the free-living environment, compared to the laboratory environment. In conclusion, smartphones demonstrate the potential for remote patient monitoring and home health care. Along with being easy-to-use, inexpensive, and portable, smartphones can accurately evaluate gait during both unobstructed and obstructed walking, indoors and outdoors.

THE EFFECT OF BLOOD GLUCOSE ON QUIET STANDING BALANCE IN YOUNG HEALTHY INDIVIDUALS.

Falling is one of the leading causes of accidental injury and death among elderly adults and construction workers, with costs exceeding US$31 billion each year. Having good balance reduces the likelihood of falling - therefore it is important to determine which possible factors might influence balance. The purpose of this study was to determine if consuming three different types of breakfast altered blood glucose levels in such a way that young healthy individual's balance control was compromised. Balance was then measured while the subjects completed single- and dual-task standing trials with eyes open and closed. Although changing blood glucose did alter quiet standing balance - as measured by the separation distance between the COG and COP, the velocity of the COM, and the total distance traveled by the COG and COP along the anterior-posterior (AP) and medial-lateral (ML) axes - the results were contradictory to what was hypothesized. Subjects with lower blood glucose swayed less than those with higher blood glucose. This could potentially be due to the habitual skipping of breakfast in young adults. Though the changing of blood glucose did influence quiet standing balance of young healthy adults, it was not in a way which increased the risk of falling.

Determining the utility of a smartphone-based gait evaluation for possible use in concussion management.

Objectives: Our was objectives were to (1) assess the validity of a smartphone-based application to obtain spatiotemporal gait variables relative to an established movement monitoring system used previously to evaluate post-concussion gait, and (2) determine the test-retest reliability of gait variables obtained with a smartphone.Methods: Twenty healthy participants (n = 14 females, mean age = 22.2, SD = 2.1 years) were assessed at two time points, approximately two weeks apart. Two measurement systems (inertial sensor system, smartphone application) acquired and analyzed single-task and dual-task spatio-temporal gait variables simultaneously. Our primary outcome measures were average walking speed (m/s), cadence (steps/min), and stride length (m) measured by the inertial sensor system and smartphone application.Results: Correlations between the systems were high to very high (Pearson r = 0.77-0.98) at both time points, with the exception of dual-task stride length at time 2 (Pearson r = 0.55). Bland-Altman analysis for average gait speed and cadence indicated the average disagreement between systems was close to zero, suggesting little evidence for systematic bias between acquisition systems. Test-retest consistency measures using the smartphone revealed high to very high reliability for all measurements (ICC = 0.81-0.95).Conclusions: Our results indicate that sensors within a smartphone are capable of measuring spatio-temporal gait variables similar to a validated three-sensor inertial sensor system in single-task and dual-task conditions, and that data are reliable across a two-week time interval. A smartphone-based application might allow clinicians to objectively evaluate gait in the management of concussion with high ease-of-use and a relatively low financial burden.

Smartphone-Based Assessment of Gait During Straight Walking, Turning, and Walking Speed Modulation in Laboratory and Free-Living Environments.

As turns and walking speed modulation are crucial for functional mobility, development of a field-based tool to objectively evaluate non-steady-state gait is essential. This study aimed to quantify spatiotemporal gait using three Android smartphones during steady-state walking, turns, and gait speed modulation in laboratory and free-living environments. In total, 24 adults ambulated along a 10-m walkway in both environments under seven conditions: straight walking, 90° left or right turn, and modulating gait speed from usual-slow, usual-fast, slow-fast, and fast-slow. Two smartphones were attached to the body, with another phone placed in a shoulder bag. Gait velocity, step time, step length, cadence, and symmetry were computed from smartphone-based tri-axial accelerometers and validated with motion capture and video, in laboratory and free-living environments, respectively. Validity was assessed using Pearson's correlation and Bland-Altman analysis. Gait velocity results revealed moderate to very high validity across all walking conditions, smartphone models, smartphone locations, and environments. Correlations for gait velocity ranged between 0.87-0.91 and 0.79-0.83 for straight walking, 0.86-0.95 and 0.86-0.89 for turning, and 0.51-0.90 and 0.67-0.89 for speed modulation trials, in laboratory and free-living environments, respectively. Step time, step length, and cadence demonstrated high to very high correlations for straight walking and turns. However, symmetry results revealed high correlations only during straight walking in the laboratory. Conditions that included slow walking showed negligible to moderate validity with a high bias. In conclusion, smartphones can be employed as field-based devices to assess steady-state walking, turning, and speed modulation across environment, model, and placement when walking faster than 0.5 m/s.

A multifaceted and clinically viable paradigm to quantify postural control impairments among adolescents with concussion.

OBJECTIVE: To identify clinically significant postural control measures capable of distinguishing the performance of adolescents with concussion from uninjured controls. APPROACH: Fifteen adolescents with concussion (67% female; median age = 16.3 years; tested 8 ± 4 d post-injury) and 31 controls (45% female; median age = 15.2 years) completed a single/dual-task gait evaluation with a smartphone affixed to their lumbar spine, modified balance error scoring system (mBESS), and single/dual-task tandem gait test. Outcome measures were obtained via smartphone (single/dual-task gait speed, cadence, step length), mBESS (double/single/tandem errors), and tandem gait (single/dual-task time). We calculated area under the curve (AUC) values for each measure that demonstrated a significant difference between groups independently, and calculated a comprehensive AUC value for all measures combined. MAIN RESULTS: The concussion group walked significantly slower (mean = 0.89 ± 0.15 versus 1.05 ± 0.15 m s-1; p  = 0.002) and with significantly fewer steps per minute (median = 103 [interquartile range = 94-108] versus 116 [104-118] steps/minute; p  = 0.002) than the control group under single-task conditions. They also completed single-task (median = 22.0 [16.6-24.2] versus 14.5 [12.4-15.5] s; p  < 0.001) and dual-task (median = 30.0 [24.0-35.2] versus 18.6 [16.1-21.7] s; p  < 0.001) tandem gait tests significantly slower than controls. The AUC value for single-task gait velocity, single-task cadence, single-task tandem gait time, and dual-task tandem gait time indicated an excellent ability to distinguish between concussion and control groups (AUC = 0.91, 95% CI = 0.80-0.99). SIGNIFICANCE: Smartphone-obtained gait measures and tandem gait times allowed for an excellent differentiation between adolescents with concussion versus control participants. This reinforces the need for multimodal approaches to postural control impairment recognition among adolescents with concussion.

Cognitive and visual demands, but not gross motor demand, of concurrent smartphone use affect laboratory and free-living gait among young and older adults.

BACKGROUND: As smartphones are an integral part of daily activities, understanding the underlying mechanism associated with concurrent cell phone use while walking may help reduce the risks of injury. RESEARCH QUESTION: This study examined the effect of cognitive, visual, and gross motor demands while using a phone during gait among young and older adults in the laboratory and free-living environments. METHODS: Twelve young and twelve older adults walked along a 10-m walkway under five conditions: single-task walking (Walk), walking and bi-manually holding a phone (Walk-Hold), walking while looking at a phone held in front of the participants (Walk-Look), walking while answering questions (Walk-Answer), and walking while texting (Walk-Text). All conditions were performed in laboratory and free-living environments. Gait velocity, step time, step length, and cadence were obtained using a smartphone with a built-in accelerometer attached to the body. The dual-task cost (DTC) was also assessed. A three-way ANOVA was utilized for all parameters. RESULTS: While no three-way interactions were found for any parameter, group × condition interactions were significant for gait velocity, step time, step length, cadence and their corresponding DTC. Decreased gait velocity, step length and cadence, with increased step time was demonstrated during Walk-Look, Walk-Answer, and Walk-Text, compared to Walk and Walk-Hold. While older adults markedly changed their gait during Walk-Answer and Walk-Text, these changes were less pronounced among young adults. SIGNIFICANCE: Visual and cognitive demand while concurrently using a phone influenced gait, especially among the elderly. Environment did not accentuate gait alterations during concurrent phone use. Therefore, smartphone technology should be developed to detect dual-task walking and temporarily modify functionality to reduce risk of injury from divided attention.

Reliability and validity of a smartphone-based assessment of gait parameters across walking speed and smartphone locations: Body, bag, belt, hand, and pocket.

The assessment of spatiotemporal gait parameters is a useful clinical indicator of health status. Unfortunately, most assessment tools require controlled laboratory environments which can be expensive and time consuming. As smartphones with embedded sensors are becoming ubiquitous, this technology can provide a cost-effective, easily deployable method for assessing gait. Therefore, the purpose of this study was to assess the reliability and validity of a smartphone-based accelerometer in quantifying spatiotemporal gait parameters when attached to the body or in a bag, belt, hand, and pocket. Thirty-four healthy adults were asked to walk at self-selected comfortable, slow, and fast speeds over a 10-m walkway while carrying a smartphone. Step length, step time, gait velocity, and cadence were computed from smartphone-based accelerometers and validated with GAITRite. Across all walking speeds, smartphone data had excellent reliability (ICC2,1≥0.90) for the body and belt locations, with bag, hand, and pocket locations having good to excellent reliability (ICC2,1≥0.69). Correlations between the smartphone-based and GAITRite-based systems were very high for the body (r=0.89, 0.98, 0.96, and 0.87 for step length, step time, gait velocity, and cadence, respectively). Similarly, Bland-Altman analysis demonstrated that the bias approached zero, particularly in the body, bag, and belt conditions under comfortable and fast speeds. Thus, smartphone-based assessments of gait are most valid when placed on the body, in a bag, or on a belt. The use of a smartphone to assess gait can provide relevant data to clinicians without encumbering the user and allow for data collection in the free-living environment.

Assessment of stability during gait in patients with spinal deformity-A preliminary analysis using the dynamic stability margin.

Daily living activities are dynamic, requiring spinal motion through space. Current assessment of spinal deformities is based on static measurements from full-spine standing radiographs. Tools to assess dynamic stability during gait might be useful to enhance the standard evaluation. The aim of this study was to evaluate gait dynamic imbalance in patients with spinal deformity using the dynamic stability margin (DSM). Twelve normal subjects and 17 patients with spinal deformity were prospectively recruited. A kinematic 3D gait analysis was performed for the control group (CG) and the spinal deformity group (SDG). The DSM (distance between the extrapolated center of mass and the base of support) and time-distance parameters were calculated for the right and left side during gait. The relationship between DSM and step length was assessed using three variables: gait stability, symmetry, and consistency. Variables' accuracy was validated by a discriminant analysis. Patients with spinal deformity exhibited gait instability according to the DSM (0.25m versus 0.31m) with decreased velocity (1.1ms-1 versus 1.3ms-1) and decreased step length (0.32m versus 0.38m). According to the discriminant analysis, gait stability was the more accurate variable (area under the curve AUC=0.98) followed by gait symmetry and consistency. However, gait consistency showed 100% of specificity, sensitivity, and accuracy of precision. The DSM showed that patients with spinal malalignment exhibit decreased gait stability, symmetry, and consistency besides gait time-distance parameter changes. Additional work is required to determine how to apply the DSM for preoperative and postoperative spinal deformity management.

Dynamic assessment of center of pressure measurements from an instrumented AMTI treadmill with controlled precision.

With the increasing use of instrumented force treadmills in biomechanical research, it is imperative that the validity of center of pressure (COP) measurements is established. The study aims were to compare an instrumented treadmill's static-belt COP accuracy to that of a floor-embedded platform, develop a novel method to quantify dynamic-belt COP accuracy with controlled precision and perform an initial investigation of how dynamic COP accuracy changes with weight and velocity. Static COP accuracy was assessed by applying a force while moving a rigid rod in a circular clockwise motion at nine positions of interest on the two treadmill and two ground-embedded force plates. Dynamic COP accuracy was assessed for weights (68.0, 102.1, and 136.1kg), applied through a ball bearing of 2.54cm circumference, with peak treadmill belt speeds of 0.5, 0.75, and 1.0m/s. COP accuracy was assessed relative to motion capture marker trajectories. Statically, treadmill COP error was similar to that of the ground-embedded force plates and that reported for other treadmills. Dynamically, COP error appeared to vary systematically with weight and velocity and in the case of anteroposterior COP error, shear force, although testing with a larger number of weights and velocities is needed to fully define the relationship. This novel method can be used to assess any instrumented treadmill's dynamic COP accuracy with controlled precision.

Home-based interventions improve trained, but not novel, dual-task balance performance in older adults: A randomized controlled trial.

The purpose of this study was to compare the efficacy of four different home-based interventions on dual-task balance performance and to determine the generalizability of the four trainings to untrained tasks. Sixty older adults, aged 65 and older, were randomly assigned to one of four home-based interventions: single-task motor training, single-task cognitive training, dual-task motor-cognitive training, and dual-task cognitive-cognitive training. Participants received 60-min individualized training sessions, 3 times a week for 4 weeks. Prior to and following the training program, participants were asked to walk under two single-task conditions (i.e. narrow walking and obstacle crossing) and two dual-task conditions (i.e. a trained narrow walking while performing verbal fluency task and an untrained obstacle crossing while counting backward by 3s task). A nine-camera motion capture system was used to collect the trajectories of 32 reflective markers placed on bony landmarks of participants. Three-dimensional kinematics of the whole body center of mass and base of support were computed. Results from the extrapolated center of mass displacement indicated that motor-cognitive training was more effective than the single-task motor training to improve dual-task balance performance (p=0.04, ES=0.11). Interestingly, balance performance under both single-task and dual-task conditions can also be improved through a non-motor, single-task cognitive training program (p=0.01, ES=0.13, and p=0.01, ES=0.11, respectively). However, improved dual-task processing skills during training were not transferred to the novel dual task (p=0.15, ES=0.09). This is the first study demonstrating that home-based dual-task training can be effectively implemented to improve balance performance during gait in older adults.

A principal component analysis approach to correcting the knee flexion axis during gait.

Accurate and precise knee flexion axis identification is critical for prescribing and assessing tibial and femoral derotation osteotomies, but is highly prone to marker misplacement-induced error. The purpose of this study was to develop an efficient algorithm for post-hoc correction of the knee flexion axis and test its efficacy relative to other established algorithms. Gait data were collected on twelve healthy subjects using standard marker placement as well as intentionally misplaced lateral knee markers. The efficacy of the algorithm was assessed by quantifying the reduction in knee angle errors. Crosstalk error was quantified from the coefficient of determination (r(2)) between knee flexion and adduction angles. Mean rotation offset error (αo) was quantified from the knee and hip rotation kinematics across the gait cycle. The principal component analysis (PCA)-based algorithm significantly reduced r(2) (p<0.001) and caused αo,knee to converge toward 11.9±8.0° of external rotation, demonstrating improved certainty of the knee kinematics. The within-subject standard deviation of αo,hip between marker placements was reduced from 13.5±1.5° to 0.7±0.2° (p<0.001), demonstrating improved precision of the knee kinematics. The PCA-based algorithm performed at levels comparable to a knee abduction-adduction minimization algorithm (Baker et al., 1999) and better than a null space algorithm (Schwartz and Rozumalski, 2005) for this healthy subject population.

Center of pressure trajectory during gait: a comparison of four foot positions.

Knowledge of the center of pressure (COP) trajectory during stance can elucidate possible foot pathology, provide comparative effectiveness of foot orthotics, and allow for appropriate calculation of balance control and joint kinetics during gait. Therefore, the goal of this study was to investigate the COP movement when walking at self-selected speeds with plantigrade, equinus, inverted, and everted foot positions. A total of 13 healthy subjects were asked to walk barefoot across an 8-m walkway with embedded force plates. The COP was computed for each stance limb using the ground reaction forces and moments collected from three force plates. Results demonstrated that the COP excursion was 83% of the foot length and 27% of the foot width in the anterior-posterior and medial lateral directions for plantigrade walking, respectively. Regression equations explained 94% and 44% of the anterior-posterior and medial-lateral COP variability during plantigrade walking, respectively. While the range of motion and COP velocity were similar for inverted and everted walking, the COP remained on the lateral and medial aspects of the foot for these two walking conditions, respectively. A reduced anterior-posterior COP range of motion and velocity were demonstrated during equinus walking. Ankle joint motion in the frontal and sagittal planes supported this COP movement, with increased inversion and plantar flexion demonstrated during inverted and equinus conditions, respectively. Results from this study demonstrated the COP kinematics during simulated pathological gait conditions, with the COP trajectory providing an additional tool for the evaluation of patients with pathology.

An artificial neural network estimation of gait balance control in the elderly using clinical evaluations.

The use of motion analysis to assess balance is essential for determining the underlying mechanisms of falls during dynamic activities. Clinicians evaluate patients using clinical examinations of static balance control, gait performance, cognition, and neuromuscular ability. Mapping these data to measures of dynamic balance control, and the subsequent categorization and identification of community dwelling elderly fallers at risk of falls in a quick and inexpensive manner is needed. The purpose of this study was to demonstrate that given clinical measures, an artificial neural network (ANN) could determine dynamic balance control, as defined by the interaction of the center of mass (CoM) with the base of support (BoS), during gait. Fifty-six elderly adults were included in this study. Using a feed-forward neural network with back propagation, combinations of five functional domains, the number of hidden layers and error goals were evaluated to determine the best parameters to assess dynamic balance control. Functional domain input parameters included subject characteristics, clinical examinations, cognitive performance, muscle strength, and clinical balance performance. The use of these functional domains demonstrated the ability to quickly converge to a solution, with the network learning the mapping within 5 epochs, when using up to 30 hidden nodes and an error goal of 0.001. The ability to correctly identify the interaction of the CoM with BoS demonstrated correlation values up to 0.89 (P<.001). On average, using all clinical measures, the ANN was able to estimate the dynamic CoM to BoS distance to within 1 cm and BoS area to within 75 cm2. Our results demonstrated that an ANN could be trained to map clinical variables to biomechanical measures of gait balance control. A neural network could provide physicians and patients with a cost effective means to identify dynamic balance issues and possible risk of falls from routinely collected clinical examinations.