Detection of knee wobbling as a screen to identify athletes who may be at high risk for ACL injury

Abstract

This study developed a method to detect knee wobbling (KW) at low knee flexion. KW consists of quick uncontrollable medio-lateral knee movements without knee flexion, which may indicate a risk of ACL injury. Ten female athletes were recorded while performing slow, single-leg squats. Using motion capture data, the ratio of the frontal angular velocity to sagittal angular velocity (F/S) was calculated. An ‘F/S spike’ was defined when the F/S ratio exceeded 100%. The number of F/S spikes was counted before and after low-pass filtering at different cut-off frequencies. Intraclass correlation coefficients for KW and filtered F/S spike were analysed. KWs per squat cycle showed a median (range) of 3 (2–8) times. F/S spikes before and after low-pass filtering at 3-, 6-, 10-, and 15-Hz were 51 (12–108), 2 (0–6), 3 (1–12), 5 (2–21), and 9 (3–33) times, respectively. KWs and F/S spikes on motion capture with 6-Hz, low-pass filtering were well correlated ( r = 0 .76). Median percentages of valgus and varus F/S spikes were 71% and 29%, respectively. After 6Hz, low-pass filtering, the number of F/S spikes was strongly correlated with observed KWs. An F/S spike assessment may be used to objectively detect KW, including flexion and varus/valgus angular velocity.

Remote assessment of pelvic kinematics during single leg squat using smartphone sensors: Between-day reliability and identification of acute changes in motor performance

“…Differently from measures of pelvic orientation, clinical data on pelvic stability obtained from acceleration signals analysed in the time-or frequency domains are less available and less standardized, which makes comparisons across studies difficult. A main difference between this and most of the other studies is that measures of stability during SLS often focused on the knee (described as knee wobbling) rather than the pelvic region [30,31]. Despite the gap in the literature which precludes direct comparisons across studies, the reduction of frequency-domain features reported on the second day is in accordance with other studies showing balance improvement after a single session [26], and indirectly supports the ability of smartphones to detect changes over time.…”

Biomechanical Risk Factors for Anterior Cruciate Ligament Injury in Young Female Basketball Players: A pilot Study

“…On the other hand, those with only positive or negative RFM's were excluded (Figure 2b). The method we developed during a previous study for detecting knee valgus/varus movement with RFM was further validated in the present study 23 . Subjects were divided into two groups: ACL-injured and uninjured groups.…”

Diagnostics Using the Change-of-Direction and Acceleration Test (CODAT) of the Biomechanical Patterns Associated with Knee Injury in Female Futsal Players: A Cross-Sectional Analytical Study

“…The data from the clinical history were used to allocate the subjects into the KI or control group. All players who had suffered a knee injury involving the valgus collapse non-contact mechanism, without surgical intervention, were included in the KI group [16,17,30]. The recorded information included age, height, weight, knee injury history, lower limb dominance, injury mechanism, medical diagnosis, pain region, time to recovery, treatment received, possible relapse, and futsal level league at the time the injury occurred.…”