Is symmetry of loading improved for injured runners during novice barefoot running?

Tenforde, Adam S.; Ruder, Matthew C.; Jamison, Steve T.; Singh, Pratham; Davis, Irene S.

doi:10.1016/j.gaitpost.2018.03.043

Cited by 15 publications

(10 citation statements)

References 19 publications

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“…The kinematic data were processed using Visual 3D software (C-Motion Inc., Rockville, MD). Cadence, step length, vertical displacement of the center of gravity, step width, and stance/swing times were calculated as we previously described [ 41 ] from data that were averaged from 10 consecutive strides [ 42 ].…”

Section: Methodsmentioning

confidence: 99%

“…VALR was calculated from ΔF/Δt from the initial linear portion of the force curve using the techniques described by Samaan et al [ 44 ]. In cases where GRF curves had an initial impact peak, the ΔF in vertical GRF from 20%–80% of the initial peak was calculated [ 42 ]. Vertical stiffness was estimated using the following calculation: where F max is the peak vertical force and Δy is the maximum displacement of the COG [ 45 ].…”

Section: Methodsmentioning

confidence: 99%

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Anxiety state impact on recovery of runners with lower extremity injuries

et al. 2022

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This prospective cohort study examined the impact of high anxiety levels on psychological state and gait performance during recovery in runners with lower body injuries. Recreational runners diagnosed with lower body injuries who had reduced running volume (N = 41) were stratified into groups using State Trait Anxiety Inventory (STAI) scores: high anxiety (H-Anx; STAI ≥40 points) and low anxiety (L-Anx; STAI <40 points). Runners were followed through rehabilitation to return-to-run using monthly surveys. Main outcome measures included kinesiophobia (Tampa Scale of Kinesiophobia, TSK-11), Positive and Negative Affect Schedule (PANAS; Positive and negative scores), Lower Extremity Function Scale (LEFS), running recovery (University of Wisconsin Running Injury and Recovery Index [UWRI]) and CDC Healthy Days modules for general health, days of anxiety/tension, disrupted sleep and work/usual activities. Running biomechanics were assessed at baseline and the final visit using 3D motion capture and a force-plated treadmill. The time to return-to-running for was 5.0±3.1 and 7.9±4.1 months for L-Anx and H-Anx, respectively and participants who withdrew (n = 15) did so at 7.7±6.2 months. L-Anx maintained low anxiety and H-Anx reduced anxiety from baseline to final visit (STAI = 31.5 to 28.4 points, 50.4 to 37.8 points, respectively), whereas the withdrawn runners remained clinically anxious at their final survey (41.5 to 40.3 points; p < .05). Group by time interactions were found for PANAS positive, LEFS UWRI, general health scores, and days feeling worry, tension and anxiety (all p < .05). Final running performance in L-Anx compared to H-Anx was most improved with cadence (8.6% vs 3.5%; p = .044), impact loading rate [-1.9% vs +8.9%] and lower body stiffness [+14.1% vs +3.2%; all p < .05). High anxiety may identify runners who will experience a longer recovery process, health-related functional disruptions, and less optimization of gait biomechanics during rehabilitation after a lower extremity injury.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Anxiety state impact on recovery of runners with lower extremity injuries

et al. 2022

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“…GRF were normalized by body weight. VALR was calculated from the slope of the ΔF/Δt of the most linear portion of the force curve, where ΔF is the change of vertical force and Δt is the change of time (between 20% and 80% of the first rise to peak of the vertical GRF 16 or vertical GRF at 13% of stance in case the initial peak is the missing 17…”

Section: Methodsmentioning

confidence: 99%

Impact of Body Mass Index on Biomechanics of Recreational Runners

Vincent

Kilgore

Chen

et al. 2020

PM&R

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Background Some recreational runners with obesity successfully train or compete without musculoskeletal injury. Insight into the key kinetic strategies of injury‐free heavier runners is necessary to appropriately guide development of safe training programs for this population. Objective To determine key biomechanical strategies of running in individuals with body mass index (BMI) values above and equal to and higher than 30 kg/m2. Design This was a case‐control study. Participants Runners with obesity (n =18; 42.7 years, 38.9% women) who were matched by sex, age, footstrike type, footwear characteristics, and running speed with healthy runners (n = 36; 41.7 years, 32.5% women). Setting Research laboratory affiliated with an academic medical center. Methods A seven‐camera optical motion analysis system was used to capture running kinematics and an instrumented treadmill captured kinetic data. Main Outcomes Main outcomes were temporal spatial parameters, joint excursions, peak ground reaction forces (GRFs), joint moments, vertical average loading rate (VALR), impulses, and vertical stiffness (Kvert). Results Runners with obesity demonstrated 15% less vertical excursion of the center of mass, 18% wider strides, and 3% longer stance times than nonobese runners (P < .05). Normalized peak GRFs and VALRs were higher in the nonobese group. GRF impulse was higher in the group with obesity compared to the nonobese group (means ± SD; 339.6 ± 55.2 Ns vs. 255.0 ± 45.8 Ns; P = .0001). Kvert was higher in the obese group compared to the nonobese group (238.6 ± 50.3 N/cm vs. 183.1 ± 29.4 N/cm; P = .0001). Peak hip moments were higher in runners with obesity in the sagittal and frontal planes (P < .05). Conclusion Runners with obesity dampened impact forces and controlled loading rate more than nonobese runners by increasing lower body stiffness and constraining vertical displacement.

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“…Average and instantaneous vertical loading rates (AVLR/IVLR) were calculated as described in Tenforde et al [27] to allow calculation in mid/forefoot strikers (no impact peak). Briefly, the point of interest was determined as the first point, above 75% of the participant's body weight (bw) for which the instantaneous slope of the vertical ground reaction force was below 15 bw/s.…”

Section: B Wearable Sensorsmentioning

confidence: 99%

Validating Commercial Wearable Sensors for Running Gait Parameters Estimation

et al. 2020

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A growing number of people all over the world are running. Gathering in-field data with wearable sensors is attractive for runners, clinicians and coaches to improve running performance, avoid injury or return to running after an injury. However, it is yet to be proven that commercially available wearable sensors provide valid data. The objective of this study was to assess the validity of five wearable sensors (Moov Now TM , MilestonePod, RunScribe TM , TgForce and Zoi) to measure ground reaction force related metrics, step rate, foot strike pattern, and vertical displacement of the center of mass during running. Concurrent/criterion validity was assessed against a laboratory-based system using Pearson's correlation coefficients and ANOVAs. Step rate measurement provided by all wearable sensors was valid (all r > 0.96 and p < 0.001). Only Zoi provided valid vertical displacement of the center of mass (r = 0.81, p < 0.001); only TgForce provided meaningful estimates of instantaneous vertical loading rate (r = 0.76, p < 0.001); only MilestonePod could discriminate between a rear-, mid-and fore-foot strike pattern during running (p < 0.001). None of the wearable sensors was valid for estimating peak braking force. In conclusion, only a few metrics provided by these commercially available wearable sensors are valid. Potential buyers should therefore be aware of such limitations when monitoring running gait variables.

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Is symmetry of loading improved for injured runners during novice barefoot running?

Cited by 15 publications

References 19 publications

Anxiety state impact on recovery of runners with lower extremity injuries

Anxiety state impact on recovery of runners with lower extremity injuries

Impact of Body Mass Index on Biomechanics of Recreational Runners

Validating Commercial Wearable Sensors for Running Gait Parameters Estimation

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