Rehabilitation and Return to Sport Assessment after Anterior Cruciate Ligament Injury: Quantifying Joint Kinematics during Complex High-Speed Tasks through Wearable Sensors.

Stefano Di Paolo,Francesco Della Villa,Laura Bragonzoni,Stefano Zaffagnini,Giulio Figari,Gabriele Paolini,Alberto Grassi,Nicola Francesco Lopomo

doi:10.3390/s21072331

Abstract

The aim of the present study was to quantify joint kinematics through a wearable sensor system in multidirectional high-speed complex movements used in a protocol for rehabilitation and return to sport assessment after Anterior Cruciate Ligament (ACL) injury, and to validate it against a gold standard optoelectronic marker-based system. Thirty-four healthy athletes were evaluated through a full-body wearable sensor (MTw Awinda, Xsens) and a marker-based optoelectronic (Vicon Nexus, Vicon) system during the execution of three tasks: drop jump, forward sprint, and 90° change of direction. Clinically relevant joint angles of lower limbs and trunk were compared through Pearson’s correlation coefficient (r), and the Coefficient of Multiple Correlation (CMC). An excellent agreement (r > 0.94, CMC > 0.96) was found for knee and hip sagittal plane kinematics in all the movements. A fair-to-excellent agreement was found for frontal (r 0.55–0.96, CMC 0.63–0.96) and transverse (r 0.45–0.84, CMC 0.59–0.90) plane kinematics. Movement complexity slightly affected the agreement between the systems. The system based on wearable sensors showed fair-to-excellent concurrent validity in the evaluation of the specific joint parameters commonly used in rehabilitation and return to sport assessment after ACL injury for complex movements. The ACL professionals could benefit from full-body wearable technology in the on-field rehabilitation of athletes.

Highlights

Biomechanical assessment of human movement represents a key tool to discriminate normal and pathological patterns in a wide variety of applications
In the sport-related context, the risky patterns lead to an increased risk for severe injuries such as the noncontact Anterior Cruciate Ligament (ACL) injury [1,2,3,4,5]
The main finding of the present study was that the wearable inertial sensors (WIS) motion capture system showed overall fair-to-excellent correlation with respect to the optoelectronic marker-based (OMB) system, and acceptable measurement errors in all the movements assessed

Summary

Introduction

Biomechanical assessment of human movement represents a key tool to discriminate normal and pathological patterns in a wide variety of applications. In the sport-related context, the risky patterns lead to an increased risk for severe injuries such as the noncontact Anterior Cruciate Ligament (ACL) injury [1,2,3,4,5]. All the main joints have a role in the ACL injury mechanism [1,9,10], and targeted neuromuscular training has been proposed to modify the specific risky patterns in the rehabilitation phase after injury [11,12,13,14]. The interest in tools for assessing multi-joint biomechanics in this context has increased more and more [15,16].

Objectives

Methods

Conclusion