A Reliability Comparison of Different Methods for Detecting Step Rate and Foot Strike Pattern in Runners Using Two-dimensional Video

Erin, Miller; Jamie, Morris; Watson, Daniel; Goss, Donald

doi:10.13189/ujph.2018.060608

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…Overall FSP was determined by the largest percentage of foot strikes observed during video analysis. Video analysis of FSP has demonstrated excellent intra-and inter-rater reliability (Esculier et al, 2018;Miller et al, 2018) and good concurrent validity when compared to three-dimensional motion analysis (Esculier et al, 2018).…”

Section: Initial Data Collectionmentioning

confidence: 99%

Wearable Technology May Assist in Retraining Foot Strike Patterns in Previously Injured Military Service Members: A Prospective Case Series

Goss

Watson

Miller

et al. 2021

Front. Sports Act. Living

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A rearfoot strike (RFS) pattern with increased average vertical loading rates (AVLR) while running has been associated with injury. This study evaluated the ability of an instrumented sock, which provides real-time foot strike and cadence audio biofeedback, to transition previously injured military service members from a RFS to a non-rearfoot strike (NRFS) running pattern. Nineteen RFS runners (10 males, 9 females) were instructed to wear the instrumented socks to facilitate a change in foot strike while completing an independent walk-to-run progression and lower extremity exercise program. Kinetic data were collected during treadmill running while foot strike was determined using video analysis at initial (T1), post-intervention (T2), and follow-up (T3) data collections. Nearly all runners (18/19) transitioned to a NRFS pattern following intervention (8 ± 2.4 weeks after the initial visit). Most participants (16/18) maintained the transition at follow-up (5 ± 0.8 weeks after the post-intervention visit). AVLR of the involved and uninvolved limb decreased 29% from initial [54.7 ± 13.2 bodyweights per sec (BW/s) and 55.1 ± 12.7 BW/s] to post-intervention (38.7 ± 10.1 BW/s and 38.9 ± 10.0 BW/s), respectively. This effect persisted 5-weeks later at follow-up, representing an overall 30% reduction on the involved limb and 24% reduction on the uninvolved limb. Cadence increased from the initial to the post-intervention time-point (p = 0.045); however, this effect did not persist at follow-up (p = 0.08). With technology provided feedback from instrumented socks, approximately 90% of participants transitioned to a NRFS pattern, decreased AVLR, reduced stance time and maintained these running adaptations 5-weeks later.

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Section: Initial Data Collectionmentioning

confidence: 99%

Wearable Technology May Assist in Retraining Foot Strike Patterns in Previously Injured Military Service Members: A Prospective Case Series

Goss

Watson

Miller

et al. 2021

Front. Sports Act. Living

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Using real‐time biofeedback to alter running biomechanics: A randomized controlled trial

et al. 2019

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In this study, we assessed the effectiveness of a mobile feedback system on transitioning runners to a non‐rearfoot strike (NRFS) pattern and prospectively compared injury incidence rates at one year between rearfoot strike (RFS) and NRFS runners. 128 RFS runners participated in a 2‐hour training session to learn a NRFS pattern with 114 completing the 1‐year follow‐up. Participants were randomized into a control group (CON) with no additional training and a biofeedback group (BFG) where they received equipment to provide real‐time biofeedback to augment the transition to a NRFS pattern. Foot strike patterns (FSP) were assessed at baseline, post‐training, 6‐months, and 1‐year. Injury data were collected through weekly email surveys over one year. Eighty percent of runners demonstrated a NRFS pattern following the training session (91/114, P < .001). The percentage of NRFS runners remaining at the one‐year follow‐up decreased slightly in both groups, but was not significantly different between groups (CON = 69%, P = .29; BFG = 75%, P = .36). Injury rates were similar between RFS runners (37% injured) and NRFS runners (30% injured) after one year (P = .47). The relative risk for knee injury in RFS runners was 5.64 (95% CI: 1.90‐16.8; P = .02). In conclusion, both groups had a significant number of participants transition to a NRFS immediately after training and maintain NRFS at the 1‐year follow‐up. However, compliance with the sensor in the BFG group was very poor due to limitations of the sensor. Regardless of FSP, runners experienced 1‐year injury incidence rates between 30%‐37%. RFS runners had nearly a six times greater risk for developing a knee injury than NRFS runners.

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The stability of step rate throughout a 3200 meter run

et al. 2019

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A Reliability Comparison of Different Methods for Detecting Step Rate and Foot Strike Pattern in Runners Using Two-dimensional Video

Cited by 5 publications

References 25 publications

Wearable Technology May Assist in Retraining Foot Strike Patterns in Previously Injured Military Service Members: A Prospective Case Series

Wearable Technology May Assist in Retraining Foot Strike Patterns in Previously Injured Military Service Members: A Prospective Case Series

Using real‐time biofeedback to alter running biomechanics: A randomized controlled trial

The stability of step rate throughout a 3200 meter run

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