An obstacle clearance test for evaluating sensorimotor control after anterior cruciate ligament injury: A kinematic analysis

Sensorimotor deficits, particularly proprioceptive, are often reported following rupture of the anterior cruciate ligament (ACL). High secondary injury rates and long‐term negative consequences suggest that these deficits are not properly identified using current assessment methods. We explored a novel obstacle clearance test to evaluate sensorimotor control in individuals following ACL reconstruction (ACLR) and rehabilitation. Thirty‐seven post‐ACLR individuals, 23 nonathletic asymptomatic controls (CTRL), and 18 elite athletes stepped over a hurdle‐shaped obstacle, downward vision occluded, aiming for minimal clearance. Kinematic outcomes (3D motion capture) for the leading and trailing legs, for two unpredictably presented obstacle heights, were categorized into Accuracy: vertical foot clearance and minimal distance from the obstacle; Variability: end‐point and hip/knee trajectory; and Symmetry: trunk/hip/knee crossing angles, hip–knee–ankle movement, and velocity curves. Accuracy was worse for CTRL compared with both other groups. ACLR had less leading and trailing vertical foot clearance with their injured compared with their noninjured leg. ACLR and athletes had less crossing knee flexion in their injured/nondominant legs compared with their contralateral leg, both leading and trailing. ACLR showed greater trunk flexion when crossing with their injured leg, both leading and trailing. For the leading leg, ACLR showed greater asymmetry for the hip–knee–ankle velocity curve compared with elite athletes. Trailing leg trajectory variability was lower for ACLR compared with CTRL and athletes for higher obstacles. Clinical significance: Sensorimotor deficits in individuals post‐ACLR were reflected by greater asymmetry and less variable (more stereotypical) trajectories rather than limb positioning ability. This consideration should be addressed in clinical evaluations.


| BACKGROUND
Anterior cruciate ligament (ACL) tear is a prevalent sport-related injury and often results in long-term consequences, such as reduced knee function, 1 weakened knee muscle strength, 2 and deficient postural control. 3,4 Furthermore, ACL-reconstructed individuals have been reported to have a high rate of graft rupture as well as contralateral ACL injury. 5,6 Postinjury sensorimotor deficits may underlie this tendency, originating in damage to proprioceptors within the ligament, 7,8 and assumed to persist despite extensive rehabilitation. 9 Human motor activity involves the integration of multiple sensory afferents within an elaborate neural network for the planning and optimal execution of voluntary motor commands. 10 Such integration occurs mostly within the central nervous system (CNS) and is generally referred to as sensorimotor control. 11,12 Due to the abundance of neural components and the complex nature of the body-environment interaction in constantly changing conditions, the study of sensorimotor control is a complex endeavor. Clinically, defining the sensorimotor control of an individual as deficient often refers to symptoms of insufficiency, attributed to one or more of the different sensory or neuromuscular components. 12 Proprioception, defined broadly as the ability to sense the position and movement of one's own body, 13 is considered a key element in sensorimotor control. 11,12,14 Two metaanalyses demonstrated proprioceptive deficits following an ACL injury, compared with either the contralateral side 15 or to noninjured individuals. 16 In contrast, an additional systematic review, 17 which included studies with an average time after surgery of 20 months, concluded that there was no evidence of proprioceptive deficits after ACL reconstruction, suggesting that either assessment methods are not sensitive enough or that proprioception, in fact, improves over time.
Regardless, initially altered sensory input from the knee, along with injury-associated inflammation, joint instability, and movement compensations are suggested to lead to postinjury sensorimotor compensations that may not be sufficient for adequate motor control. 9 Proprioception cannot be directly assessed, though various methods have been implemented to target different components encompassed within the term "proprioceptive ability." This is mainly done through movement detection and angle/force reproduction tasks. 12 These tasks often require custom-built devices and/or expensive equipment and are thus impractical in the clinics where such assessment tools are virtually lacking. 18 Furthermore, the use of functional assessments is more frequent in clinical settings.
Generally, performances in different functional tests (e.g., squat, vertical hop, and hop for distance) are deemed central to the decision of whether or not an individual is eligible to return to preinjury activity level/sports. 19 However, the high rate of secondary injury 5,6 suggests that such tests may not be sufficient to identify those with sensorimotor deficiencies, possibly due to coarse outcome variables that should otherwise be broken down into detailed movement characteristics rather than summated to overall functional scores. 20,21 Another approach for addressing sensorimotor control involves context-conditioned variability in the execution of voluntary movements. The sensorimotor system is rarely constrained to a single solution of a motor task but rather utilizes a variety of contextspecific movement patterns. 22,23 In other words, multijoint taskspecific coordination solutions are part of a healthy repertoire available to move an end-point of a limb to the same location despite environmental or sensory constraints, various body configurations, and different task requirements. 22 Such repertoire, referred to as motor abundance, 23,24 is considered necessary for optimal control of movements performed in various contexts and under changing environmental demands. In addition, less movement variability (i.e., more stereotypical movements) has been previously reported in ACL-injured individuals during postural control tasks, 25,26 in particular in those who suffered more than one injury. 25 The obstacle clearance (OC) paradigm has been previously implemented as a means of investigating the involvement of vision and proprioception within a common locomotion task. [27][28][29][30] It features a participant stepping over an obstacle while maintaining only a minimal margin during crossing. This task requires both identifications of the obstacle's position in space and well-coordinated limb movements to step over the obstacle without hitting it with either leg. This article presents a novel attempt to implement an OC paradigm among individuals who had suffered an ACL-injury, targeting their reliance on proprioception by means of standard OC outcomes (i.e., distance from the obstacle), while evaluating the sensorimotor control throughout the task by also addressing movement variability and between leg symmetry. We compared the performance of individuals following ACL-injury, who had undergone reconstruction (ACLR) and rehabilitation, to that of asymptomatic controls (CTRL) and elite athletes (ATH), the latter assumed to have superior sensorimotor control and body awareness than the less-active CTRL group. The use of elite athletes also provided a certain proxy to the preinjury state of ACLR as most of them were highly sports active before their injury. We hypothesized that ACLR would perform the OC test with larger margins (i.e., longer distances from the obstacle) and show greater leg asymmetry.
Variability of performance was expected to be greater for ACLR in terms of endpoint consistency, yet more stereotypical movement patterns were also hypothesized, reflected as less trajectory variability.

| Participants
In the current case-control study (level of evidence: III), we included 37 individuals following ACLR and two reference groups: 23 age-and sex-matched asymptomatic controls and 18 elite athletes ( Table 1).
The project was approved by the Regional Ethical Review Board and all participants provided written informed consent. ACLR participants were recruited from an orthopedic clinic at Norrlands University Hospital, Umeå, Sweden and from a private clinic (Sports Medicine Umeå, Sweden). Inclusion criteria for ACLR were 17-34 years of age, with unilateral ACL injury (time from injury <10 years) treated with surgical reconstruction using a hamstring autograft (standard practice nationally). Participants had to have completed their rehabilitation according to their physician/physiotherapist, implying that return to sports/physical activity was allowed. Participants were excluded if they had suffered any other musculoskeletal or neurologic pathology in the preceding 6 months. Asymptomatic participants were without any known pathological conditions of relevance. Elite athletes had to be actively involved in competition at an elite level, defined as the highest/second-highest league in their respective knee-demanding sport, and we ended up including participants playing either floorball or soccer; n = 14, 4, respectively.

| Apparatus and data processing
Kinematic data were collected using an eight-camera 3D motion

| Test protocol
Participants stood in front of a resizable hurdle-shaped obstacle, placed at a standardized distance anterior to the tip of the big toe, equal to 7% of participant height ( Figure 1A). This constituted an optimal distance, ensuring OC with comfortable hip and knee range of motion (ROM). Two standardized heights were used: 13% and 18% of participant height. All ratios were chosen based on pilot testing, targeting knee joint angles of 40°and 65°, respectively, corresponding to target angles frequently used in joint position sense assessments 16 and were compatible with the ROM required to step over the obstacle. Participants were not provided any information regarding obstacle heights or how many there were. Custom-made goggles occluded downward vision, and participants were instructed to look straight forward at a red dot displayed on a TV screen at approximately eye level. Participants stood barefoot with their leading foot on a 2 cm-high platform, while the trailing foot was placed parallel on the floor. This level discrepancy was used to increase reliance on limb position sensation by creating an initial mismatch between legs and thus further challenging the trailing leg.
First, the participants were asked to place and hold their foot on top of the obstacle for approximately 3 s and memorize its height. After returning to the starting position, they were asked to immediately step over the obstacle with as little clearance as possible. Arms were free to aid balance when needed. The obstacle was removed by the examiner (unbeknownst to the participant) immediately after the participant had returned to the starting position. This was done to avoid contact with the obstacle, which could have resulted in possible overcompensation during subsequent trials. 27

| Statistical analysis
Due to the exploratory nature of the proposed paradigm, determining an adequate sample size a priori was difficult. Based on other studies implementing an OC test, sample sizes ranged from 6 to 24 participants in healthy populations. [27][28][29][30] No previous study has implemented such a paradigm among ACLR individuals.
We, therefore, to achieve sufficient power, aimed for >30 ACLR individuals.

| Variability
There was no between-group difference in end-point variability.
However, the ACLR group showed on average less trajectory

| DISCUSSION
Our main findings were that ACLR individuals showed greater leg asymmetry and less trajectory variability compared with both controls and athletes. Conversely, contrary to our hypotheses, larger obstacle distances were not observed for ACLR, suggesting that the utilization of proprioceptive information during this functional task was not worse in our ACLR group. In brief, by utilizing an updated OC paradigm design and sensitive kinematic analysis methods, we were able to identify sensorimotor deficits that were otherwise undetected based on analyses and interpretations limited merely to limb positioning ability. The latter was assessed here functionally as opposed to standard joint position sense paradigms. 15,16

| Accuracy outcomes and proprioception
ACLR was similar to ATH in terms of both vertical clearance and minimal distance from the obstacle. Clearing the obstacle with minimal margins represented better joint positioning ability, as visual input was obscured during the task. Alternatively, participants might have placed their limbs closer than intended due to miscalculating the height of the obstacle. The first argument is however more likely as it is supported by the fact that our elite athletes, assumed to have a better limb positioning ability, were closer to the obstacle.  previously reported by Paterno and colleagues, 25 as a characteristic of individuals following ACLR, which later suffered a secondary injury. Conversely, since excessive variability might also reflect a failure to successfully implement an underlying motor program, in this context, decreased variability is expected when motor learning has occurred and the performance has stabilized. 39 Indeed, previous studies have observed increased trajectory variability in ACL-injured individuals, which was interpreted as an indication of a less stable system. 40,41 However, even supporters of the latter view acknowledge that the same goals are achievable by using a variety of kinematic patterns, known as motor equivalence. 39,42 Finally, the concept of "optimal variability" was introduced by Stergiou and colleagues 43 in an attempt to balance the two approaches. On the one end, invariability would result in a rigid system, while excessive variability could be considered as unwanted noise. Both could negatively affect the ability of the motor system to resist unexpected perturbations. 43 Bringing an end-point to a target involves moving a kinematically redundant limb, prompting trajectory variability as a necessity for synergies to emerge. The term "stability" does not necessarily apply to individual links in the kinematic chain but rather to the end-point trajectory and final outcome. 23,44 In this context, trajectory variability is required to stabilize the foot in line with the task constraints (i.e., not hitting the obstacle). In this study, there were no betweengroup differences in end-point variability, yet trajectory variability was different between groups for high obstacles, suggesting that low obstacle trials were not challenging enough to reflect variability

| Movement symmetry
Both biomechanical and functional asymmetries were previously reported in ACLR persons. 45,46 Our results likewise revealed between-leg differences in both foot clearance, and knee and trunk kinematics. As for knee flexion, ATH also showed between-leg differences, which may be expected due to uneven limb function during their years of training. 47

| Study limitations
The OC test paradigm is not yet an established and validated test for sensorimotor control after an ACL injury. We recognize this limitation and advise to treat our results accordingly.

| Clinical implications
Deciding whether or not a person is eligible to return to preinjury activity following ACLR rehabilitation is challenging. Despite adequate functional performance, 49  Motor abundance should also be encouraged by increasing variability in practice and incorporating exercise in more challenging scenarios, thus increasing the flexibility and adaptability of the sensorimotor system when performing functional tasks.
Finally, we acknowledge that while the use of an advanced 3D measuring system was required for our analysis, such equipment is rarely available for clinicians to use. However, outcomes from more simplistic equipment (i.e., a basic video camera and a physician scale) have been shown to correlate with 3D analysis of kinematic and kinetic measurements. 50 Furthermore, similar tools are also in use for calculations of symmetry indices, therefore establishing the validity of such assessments when looking at between-leg differences. 49

AUTHOR CONTRIBUTIONS
Adam Grinberg contributed to data collection, carried out data and statistical analyses, interpreted the results, and drafted the manuscript. Andrew Strong contributed to test design, data collection, and writing of the manuscript. Sebastian Buck contributed to pilot work, initial analysis, and writing of the manuscript. Jonas Selling contributed to test design, programming, biomechanical modeling, and provided ongoing technical support and feedback. Charlotte K. Häger led the conceptualization and design of the project, obtained funding, and contributed to the analysis and the writing of the manuscript. All authors read and approved the final manuscript.