Immersive Real-Time Biofeedback Optimized With Enhanced Expectancies Improves Motor Learning: A Feasibility Study

Abstract

Context: An Optimizing Performance through Intrinsic Motivation and Attention for Learning theory-based motor learning intervention delivering autonomy support and enhanced expectancies (EE) shows promise for reducing cognitive-motor dual-task costs, or the relative difference in primary task performance when completed with and without a secondary cognitive task, that facilitate adaptive injury-resistant movement response. The current pilot study sought to determine the effectiveness of an autonomy support versus an EE-enhanced virtual reality motor learning intervention to reduce dual-task costs during single-leg balance. Design: Within-subjects 3 × 3 trial. Methods: Twenty-one male and 24 female participants, between the ages of 18 and 30 years, with no history of concussion, vertigo, lower-extremity surgery, or lower-extremity injuries the previous 6 months, were recruited for training sessions on consecutive days. Training consisted of 5 × 8 single-leg squats on each leg, during which all participants mimicked an avatar through virtual reality goggles. The autonomy support group chose an avatar color, and the EE group received positive kinematic biofeedback. Baseline, immediate, and delayed retention testing consisted of single-leg balancing under single- and dual-task conditions. Mixed-model analysis of variances compared dual-task costs for center of pressure velocity and SD between groups on each limb. Results: On the right side, dual-task costs for anterior–posterior center of pressure mean and SD were reduced in the EE group (mean Δ = −51.40, Cohen d = 0.80 and SD Δ = −66.00%, Cohen d = 0.88) compared with the control group (mean Δ = −22.09, Cohen d = 0.33 and SD Δ = −36.10%, Cohen d = 0.68) from baseline to immediate retention. Conclusions: These findings indicate that EE strategies that can be easily implemented in a clinic or sport setting may be superior to task-irrelevant AS approaches for influencing injury-resistant movement adaptations.

The effects of sports‐related concussion history on female adolescent brain activity and connectivity for bilateral lower extremity knee motor control

“…Specifically, athletes with a history of SRC motor behavior and associated neural functioning may be uniquely supported when adopting an external focus of attention, are provided autonomy support, and/ or are provided enhanced expectancies for future performance (Avedesian et al, 2021). For instance, recent work demonstrated that a single session of visual biofeedback double-leg squat training with real-time positive feedback (i.e., enhanced expectancies) reduced dual-task cost for single-leg postural control in healthy controls (Williams et al, 2022). However, we emphasize that sensorimotor-based interventions such as OPTIMAL PREP, remain largely theoretical and necessitate future research before clinical implementation.…”

Either Autonomy Support or Enhanced Expectancies Delivered Via Virtual-Reality Benefits Frontal-Plane Single-Leg Squatting Kinematics

“…Our primary analysis consisted of three 3x2 repeated measures ANOVAs (between factor: Group [control, AS, EE]; within factor: Time [baseline, post-test]), for measures of peak knee abduction, peak hip adduction, and peak trunk ipsilateral lean. Given the preliminary pilot and proof of concept nature of this study and consistent with similar prior work (Hogg et al, 2022;Williams et al, 2022), we used effect sizes (η p 2 and Cohen's d) to interpret the magnitude of main effects and interactions. We interpreted η p 2 effect sizes as small (.01), moderate (.06), and large (.14) and Cohen's d effect sizes as small (0.2), moderate (0.5) and large (0.8) as according to Cohen (Cohen, 1988).…”

“…We engaged 45 participants (21 male and 24 female) in a single 90-minute research session (Table 1) (Hogg et al, 2022; Williams et al, 2022). Of these, 41 reported prior engagement in moderate-to-vigorous exercise for 30 minutes, three times a week.…”

“…The instrumentation we used for kinematic biofeedback delivery has been reported in detail elsewhere (Hogg et al, 2022;Williams et al, 2022). Briefly, kinematic data for biofeedback delivery were collected using the Microsoft Azure Kinect DK (https:// azure.microsoft.com/en-us/services/kinect-dk/).…”

“…The highlights remained on as long as the participant did not exceed predetermined knee valgus, pelvic drop, or trunk lean thresholds. Participants in the EE group were instructed to move in such a way as to retain the green lights on the avatar but were given no explicit feedback on how to accomplish this (Figure 2) (Williams et al, 2022).…”