Quantifying bi-variate coordination variability during longitudinal motor learning of a complex skill

Abstract

Biofeedback (BFb) can enhance the motor learning process by guiding skill exploration. Too much BFb, however, can foster dependency leading to skill retention deficits once removed. A reducing BFb schedule could negate dependency effects, however limited methodologies exist to assess the effectiveness of an intervention during application. This research proposes a new bi-variate method (CI2Area) to quantify coordination variability (CoordVar) as a measure of skill exploration during a motor learning intervention. Thirty-two participants were introduced to a novel explosivelunge task. A BFb group (n=16) were provided with visual BFb on rear hip, knee and ankle joint extension magnitudes and timing during a 26-week reducing schedule BFb intervention. CoordVar of hip-knee and knee-ankle angular velocities were quantified by calculating the area encompassed by the 95% confidence intervals of joint coupling angular-velocity bi-variate plots (CI2Area). Linear regressions were fitted to group and individual CoordVar longitudinal data. The BFb was effective in successfully altering whole limb technique within just two sessions, and these changes were retained. The BFb group demonstrated a continual increase of CoordVar throughout the intervention, showing continual skill exploration strategies, while the Control group remained unchanged. Gradually increasing time between sessions, using a longitudinally reducing BFb schedule, successfully negates dependency effects on BFb while also encouraging motor learning. Manipulating time between sessions allows for the provision of a high frequency of 100% BFb without fostering dependency. The CI2Area method was able to detect individual exploration strategies and could be used in the future to direct individual intervention modifications.

Sensor-based augmented visual feedback for coordination training in healthy adults: a scoping review

“…Most studies (18 out of 26) had a relatively small group size with less than 15 participants per intervention arm ( Table 1 columns “Groups” and “N”). The exceptions were Benjaminse et al ( 20 ) with 30, Chan et al ( 21 ) with 160, Mulloy et al ( 25 ) with 16, Post et al ( 28 ) with 22, Eriksson et al ( 36 ) with 20, Hamacher et al ( 37 ) with 15, and Teran-Yengle et al ( 44 ) with 17.…”

“…Positive and no benefits are approximately equally common in the feedback and no-feedback conditions of the training effect studies. Even when looking only at the studies with the biggest group-sizes, the outcomes are mixed: Chan et al ( 21 ) (160/group with fading) shows a clear benefit, Benjaminse et al ( 20 ) (30/group with 100% feedback) and Mulloy et al ( 25 ) (16/group with 70% feedback) show no benefit compared to no-feedback control groups, and Post et al ( 28 ) (22/group) only shows a clear benefit in a transfer test. This pattern does not continue in the immediate effect studies, where feedback groups always outperformed no-feedback groups in at least one outcome measure.…”

Hieb‐ und stichfest

“…Bei 25 Teilnehmern eines Fechtteams der amerikanischen Luftwaffe wurde im Ausfallschritt eine Spitzengeschwindigkeit von 1,21 m/s gemessen. Die durchschnittliche Leistung, berechnet mit den beschleunigten Massen der Athleten, betrug 430 W, die Spitzenleistung 850 W. Die Geschwindigkeit der Waffe ist im Ausfallschritt wegen einer zusätzlichen Armstreckung höher: So ergaben Messungen eine Geschwindigkeit von 3,2 m/s bei geübten Fechtern und 2,6 m/s bei Anfängern .…”

A Wearable-Sensor System with AI Technology for Real-Time Biomechanical Feedback Training in Hammer Throw

“…In most sports, limb coordination is an essential factor influencing the performance of a motor skill, but it is very difficult to be quantified [ 1 , 2 , 3 ]. Obtaining reliable kinematic and kinetic parameters, such as joint angles, applied forces, etc., and further performing 3D motion analysis can help to reveal the related hidden information.…”