Learning effects in over-ground running gait retraining: A six-month follow-up of a quasi-randomized controlled trial.

This study evaluated learning and recall effects following a feedback-based retraining program. A 6-month follow-up of a quasi-randomized controlled trial was performed with and without recall. Twenty runners were assigned to experimental or control groups and completed a 3-week running program.

Biomechanical adaptations following a music-based biofeedback gait retraining program to reduce peak tibial accelerations.

Purpose: The present study aimed to determine whether runners can reduce impact measures after a six-session in-the-field gait retraining program with real-time musical biofeedback on axial peak tibial acceleration (PTA ) and identify the associated biomechanical adaptations.

Methods: Twenty trained high-impact runners were assigned to either the biofeedback or the music-only condition. The biofeedback group received real-time feedback on the PTA during the gait retraining program, whereas the music-only condition received a sham treatment.

Reducing the peak tibial acceleration of running by music-based biofeedback: A quasi-randomized controlled trial.

Background: Running retraining with the use of biofeedback on an impact measure has been executed or evaluated in the biomechanics laboratory. Here, the execution and evaluation of feedback-driven retraining are taken out of the laboratory.

Purpose: To determine whether biofeedback can reduce the peak tibial acceleration with or without affecting the running cadence in a 3-week retraining protocol.

Music-based biofeedback to reduce tibial shock in over-ground running: a proof-of-concept study.

Methods to reduce impact in distance runners have been proposed based on real-time auditory feedback of tibial acceleration. These methods were developed using treadmill running. In this study, we extend these methods to a more natural environment with a proof-of-concept.

Predicting gait events from tibial acceleration in rearfoot running: A structured machine learning approach.

Background: Gait event detection of the initial contact and toe off is essential for running gait analysis, allowing the derivation of parameters such as stance time. Heuristic-based methods exist to estimate these key gait events from tibial accelerometry. However, these methods are tailored to very specific acceleration profiles, which may offer complications when dealing with larger data sets and inherent biological variability.

Change-Point Detection of Peak Tibial Acceleration in Overground Running Retraining.

A method is presented for detecting changes in the axial peak tibial acceleration while adapting to self-discovered lower-impact running. Ten runners with high peak tibial acceleration were equipped with a wearable auditory biofeedback system. They ran on an athletic track without and with real-time auditory biofeedback at the instructed speed of 3.

Tibial Acceleration-Based Prediction of Maximal Vertical Loading Rate During Overground Running: A Machine Learning Approach.

Ground reaction forces are often used by sport scientists and clinicians to analyze the mechanical risk-factors of running related injuries or athletic performance during a running analysis. An interesting ground reaction force-derived variable to track is the maximal vertical instantaneous loading rate (VILR). This impact characteristic is traditionally derived from a fixed force platform, but wearable inertial sensors nowadays might approximate its magnitude while running outside the lab.

Validity and reliability of peak tibial accelerations as real-time measure of impact loading during over-ground rearfoot running at different speeds.

Studies seeking to determine the effects of gait retraining through biofeedback on peak tibial acceleration (PTA) assume that this biometric trait is a valid measure of impact loading that is reliable both within and between sessions. However, reliability and validity data were lacking for axial and resultant PTAs along the speed range of over-ground endurance running. A wearable system was developed to continuously measure 3D tibial acceleration and to detect PTAs in real-time.

Experimental Evaluation of UWB Indoor Positioning for Sport Postures.

Radio frequency (RF)-based indoor positioning systems (IPSs) use wireless technologies (including Wi-Fi, Zigbee, Bluetooth, and ultra-wide band (UWB)) to estimate the location of persons in areas where no Global Positioning System (GPS) reception is available, for example in indoor stadiums or sports halls. Of the above-mentioned forms of radio frequency (RF) technology, UWB is considered one of the most accurate approaches because it can provide positioning estimates with centimeter-level accuracy. However, it is not yet known whether UWB can also offer such accurate position estimates during strenuous dynamic activities in which moves are characterized by fast changes in direction and velocity.

Magnitude and Spatial Distribution of Impact Intensity Under the Foot Relates to Initial Foot Contact Pattern.

In running, foot contact patterns (rear-, mid-, or forefoot contact) influence impact intensity and initial ankle and foot kinematics. The aim of the study was to compare impact intensity and its spatial distribution under the foot between different foot contact patterns. Forty-nine subjects ran at 3.