Abstract
Background
Traditional examinations of anterior cruciate ligament (ACL) injuries focus primarily on static assessments and lack the ability to evaluate dynamic knee stability. Hence, a dynamic scoring system for knee function is needed in clinical settings. This study aimed to propose a dynamic scoring system based on a large sample of normative six-degree-of-freedom (6-DOF) knee kinematics during gait, and validate its correlation with conventional outcome measurements in assessing ACL-injured knees.
Methods
A total of 500 healthy Chinese participants were enrolled to establish a large dataset. The 6-DOF kinematics of both knees during gait were recorded using an infrared navigation three-dimensional portable knee motion analysis system. Based on the large sample dataset, a novel 6-DOF scoring system was developed using the dynamic time warping algorithm. To further validate the scoring system, an additional 83 patients with ACL injuries were included, and their preoperative dynamic knee kinematics assessment and patient-reported outcome measurements (PROMs) were recorded. Spearman’s correlation coefficient (ρ) was used to determine the correlations between the 6-DOF score and the Lysholm score, International Knee Documentation Committee (IKDC) subjective score, and Tegner activity scale.
Results
The mean values of adduction/abduction, internal/external rotation, flexion/extension, anterior/posterior translation, proximal/distal translation, and medial/lateral translation in the 500 healthy participants were 10.07 ± 4.04°, 15.13 ± 4.85°, 60.56 ± 6.07°, 1.79 ± 0.75 cm, 1.58 ± 0.54 cm, and 1.10 ± 0.42 cm, respectively. The mean preoperative 6-DOF score, Lysholm score, IKDC subjective score, and Tegner activity scale of the 83 ACL-injured patients were 74.29 ± 7.23, 70.26 ± 17.55, 66.78 ± 15.79, and 2.28 ± 1.56, respectively. The 6-DOF score was significantly correlated with the Lysholm score (ρ = 0.375, P < 0.001) and Tegner activity scale (ρ = 0.273, P = 0.016) for the ACL-injured patients. No significant correlation was found between the 6-DOF score and the IKDC subjective score (ρ = 0.145, P = 0.208).
Conclusion
This study proposed a normative 6-DOF knee kinematic reference range for the Chinese population based on a large sample dataset. The 6-DOF dynamic score was developed accordingly and proven to be significantly correlated with the Lysholm score and the Tegner activity scale, showing the potential to provide comprehensive and meaningful information on dynamic knee function and stability for patients with ACL injuries in the future.
Keywords: Anterior cruciate ligament, Gait analysis, Kinematics, Knee, Scoring system
Background
Anterior cruciate ligament (ACL) injuries are among the most common sports injuries and have been extensively studied in the orthopaedic literature [1]. The incidence of ACL injuries is estimated to be between 30 and 78 per 100,000 people worldwide [2–6]. As one of the most populous countries, China has a significant population of individuals with ACL injuries. In particular, the incidence of ACL injuries in Chinese athletes is much higher than that in some other countries, ranging from 0.29 to 0.71% [7].
The stability of the knee is provided mainly by a combination of static ligaments and dynamic muscle forces, and these two systems work in coordination to prevent excessive movement of the knee in all planes [8]. Since the ACL is a key component of static stabilizers, ACL injuries can cause anterior and rotational knee instability [9]. This instability deteriorates knee function and consequently results in degenerative changes in cartilage [10]. The current assessment of knee stability for ACL injuries relies on physical examinations such as the Lachman test, anterior drawer test, and pivot shift test. However, these tests are subjective and prone to bias [11]. Furthermore, there are also no validated correlations between their results and functional outcomes or activity levels [12]. On the other hand, arthrometers can quantify side-to-side differences but only assess knee stability in the sagittal plane under static conditions. Consequently, these traditional examinations are not capable of assessing dynamic knee stability for ACL injuries during motion and cannot provide a comprehensive understanding of overall knee function.
To overcome the limitations of traditional assessments, motion capture systems such as optical motion capture (OMC) and biplanar fluoroscopy have been developed and validated to accurately measure and analyze knee dynamic stability and gait posture. Specifically, they can assess knee kinematics during activities such as running, single-leg hopping, and stair negotiation, providing valuable insights for tailored treatment strategies and postoperative rehabilitation [13–17]. However, these systems are only available in specialized laboratories with large setups and numerous cameras, making them impractical for regular clinical use. Additionally, the OMC technique is characterized by noise and intensive labor, while biplanar fluoroscopy can expose patients to harmful radiation. To address the above issues, a simplified motion capture system (Opti_Knee, Innomotion Inc., Shanghai, China) was developed for use in clinical settings. This system uses two stereo infrared cameras to assess knee kinematics of six degrees of freedom (6-DOF) during gait and takes only 5–10 min to complete. At present, it has been validated to have acceptable accuracy for both angular and translational degrees of freedom when compared to biplanar fluoroscopy [18]. Furthermore, the system is noninvasive, user-friendly, and efficient in distinguishing normal and pathological knee motions [19, 20].
A preliminary study involving 56 knees has reported the use of the Opti_Knee system to analyze the gait patterns of healthy individuals in a Chinese population [21]. However, the time- and labor-saving advantages of this novel device make it feasible to conduct a clinical trial with a much larger sample size. This would allow for the exploration of the relationship between dynamic knee kinematics and functional outcomes. The main purpose of this study was to establish a dataset of dynamic knee kinematics in a large sample of 1,000 knees from 500 healthy Chinese individuals. We subsequently attempted to propose a dynamic knee function scoring system and validated its correlation with conventional knee function outcome measurements in patients with ACL injuries.
Materials and methods
Participants
This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee on Biomedical Research, West China Hospital of Sichuan University (No. 2016-99). All participants were provided with the study information and they signed an informed consent before the study began.
Healthy participants
A total of 500 healthy Chinese participants were enrolled through an electronic survey from January 2016 to December 2020 to establish a large sample dataset. The electronic surveys were distributed to gyms and running clubs of Shanghai University of Sport and to some commercial gyms and sports clubs in the Yangpu region and Xuhui region of Shanghai. The electronic survey requested participants’ sex, age, height, weight, history of knee-related symptoms, musculoskeletal problems of the lower extremities, and history of chronic systemic disease. After data collection of the survey results was complete, participants were assessed to ensure that they met the inclusion criteria. To avoid selection bias, participants were unaware of the following inclusion criteria: (1) aged between 18 and 60 years; (2) no history of lower extremity trauma, disease, pain, or operations; (3) no history of musculoskeletal disorders, cardiovascular disease, or other systematic diseases; (4) walked normally with morphologically normal lower extremities and joints; and (5) voluntarily agreed to participate with informed consent.
ACL-injured patients
All patients with ACL injuries were prospectively enrolled from the outpatient department of the Sports Medicine Center, West China Hospital, Sichuan University, from January 2016 to December 2018. The inclusion criteria were as follows: (1) aged between 18 and 45 years; (2) unilateral ACL injury; (3) no significant knee pain (visual analogue scale score ≤ 2) or swelling; (4) no symptomatic articular cartilage defects requiring treatment; (5) no history of meniscal repair; and (6) able and willing to complete the tests with informed consent. Patients with second ACL injuries after primary ACL reconstruction were excluded. Finally, a total of 83 patients underwent preoperative dynamic knee kinematics assessment and functional outcome measurements.
For the included patients, the assessments were scheduled three months before ACL reconstruction. Demographic characteristics and clinical data, including injury side, time from injury to assessment, and concomitant meniscal injuries, were collected. The International Knee Documentation Committee (IKDC) subjective knee evaluation form, Lysholm score, and Tegner activity scale were assessed preoperatively for all patients with ACL injuries.
Conventional patient-reported outcome measurements (PROMs)
The Lysholm score, Tegner activity scale, and IKDC subjective score are all validated and reliable PROMs for assessing knee function in patients with ACL injuries. The Lysholm score is an 8-item questionnaire designed to evaluate knee symptoms, stability, and daily activities. The Tegner activity scale grades activity level based on work and sports activities from level 0 to level 10. Moreover, the IKDC subjective score is an 18-item, region-specific and patient-reported questionnaire containing the domains of knee symptoms, stability, daily activity, and sports activity, which has also proven to be a powerful and validated tool for assessing ACL-injured knee function. Consequently, this study selected the above three widely accepted conventional knee functional measurements as the standard criteria, and the correlations of the 6-DOF score with these measurements were calculated.
Kinematic assessment & motion analysis
Dynamic knee stability was assessed by the Opti_Knee system, which consists of two stereo infrared cameras placed 50 cm apart for trajectory tracking and attached together with another high-speed camera to a portable workstation (Fig. 1A). The participant was required to wear two bandages with four infrared light reflective markers on each bandage during the measurement. Specifically, the shorter bandage was attached to the middle half of the participant’s lower leg, and the longer bandage was attached to the thigh at 5–10 cm above the tibiofemoral joint line [21]. After the markers were secured, the participant stood in an upright position on a treadmill 3–5 m away from the cameras and kept the markers facing the cameras. The osseous landmarks, including the greater trochanter, medial and lateral femoral condyles, medial and lateral tibial plateaus, and medial and lateral malleolus, were subsequently calibrated by using a hand-held probe composed of four infrared light reflective markers (Fig. 1B). Three arbitrary points on the same datum plane were also captured [20].
Fig. 1.
Presentation of the Opti_Knee system. (A) The instrumental setup. (B) The establishment of the baseline anatomic relationship of the femur and tibia, and the illustrated probe is digitizing the lateral plateau
The treadmill was set to a speed of 3 km/h, with the infrared signals collected at 60 Hz. Knee kinematics, including adduction/abduction, internal/external rotation, flexion/extension, anterior/posterior translation, proximal/distal translation, and medial/lateral translation, were calculated for each frame using the geometric relationships between the reflective markers under the lower limb coordinate systems that were established during calibration [21]. During the measurement process, all eight reflective markers were ensured to be clearly detectable by the system. The participants were required to walk steadily on the treadmill for 15–20 s to obtain a continuous and complete gait curve. Five repetitive trials were acquired for every participant on each limb.
Data analysis of the 6-DOF score
The dynamic time warping (DTW) algorithm was used to calculate the similarity between the 6-DOF knee kinematics data of the participants and the corresponding data in the database of healthy people [22]. Specifically, the database of similar healthy people was used to recognize and match features based on basic information such as the age, sex, height, and weight of the participants. This process resulted in a dataset of normal individuals with similar characteristics, which was used to calculate the statistical average of the data in the database of similar healthy people.
The time series of the subject’s degrees of freedom curve was represented as 
, and the corresponding time series of the average degrees of freedom for normal individuals was represented as 
. Using these, we constructed a dynamic programming matrix of size 
, where the matrix element (i, j) represents the Euclidean distance between the points 
and 
, denoted as 
. Smaller distances indicated greater similarity between the two time series curves. To calculate the similarity of the curves after dynamic time warping, we defined W, where the k-th element of W is defined as 
. This effectively defines a mapping between sequence X and sequence Y:
 |
We then searched for a continuous path from the matrix starting point 
to the endpoint 
. We started from 
, requiring the next matrix element to be 
, 
, or 
. Finally, we calculated the minimum cost path for achieving time warping using the following formula:
 |
To calculate the minimum cost path, we defined the cumulative distance D as:
 |
To calculate the normal value of the subject’s joint motion function, we mapped the cumulative distance values. The sigmoid function is commonly used in the output layer of neural networks due to its monotonicity, continuity, limited output range, and stable optimization. Compared with linear functions, the sigmoid function can better reflect the correlation between the degrees of freedom distance and the quality of the joint function. Therefore, this method uses the sigmoid function for mapping calculations. The modified definition of the sigmoid function used in this method is as follows: 
,
in which F represents the similarity parameter value for the degrees of freedom motion data and N represents the number of 6-DOF motion data selected. In this project, N is set to 100, and e is the mathematical constant, also known as Euler’s number.
A 6-DOF score of 0 represented the worst dynamic knee function, and a 6-DOF score of 100 represented normal healthy knee function.
Statistical analysis
The data were analyzed using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). For normally distributed data in the 6-DOF knee kinematics, the 95% confidence interval was calculated as mean ± 1.96 standard error (SE). Spearman’s correlation coefficient (ρ) was used to determine the correlations between the 6-DOF score and the Lysholm score, IKDC subjective score, and Tegner activity scale. A correlation coefficient ρ < 0.3 was considered low, 0.3 ≤ ρ ≤ 0.6 was considered moderate, and ρ > 0.6 was considered high [23]. A value of P < 0.05 was considered statistically significant.
Results
Characteristics of the healthy participants
The demographic characteristics of the 500 healthy participants are shown in Table 1. There were 274 male and 226 female healthy participants performing the gait testing, with a mean age of 29.49 ± 8.27 years and a mean body mass index (BMI) of 22.40 ± 2.94 kg/m2.
Table 1.
Demographic characteristics of the healthy participants
| Variables | Values |
|---|---|
| Sex (male/female) | 274/226 |
| Age (years) | 29.49 ± 8.27 |
| Height (cm) | 168.62 ± 8.01 |
| Body weight (kg) | 64.06 ± 11.60 |
| BMI (kg/m2) | 22.40 ± 2.94 |
BMI, body mass index
6-DOF knee kinematics of the healthy participants
Table 2 shows the 6-DOF knee kinematics data of the 500 healthy participants. The 6-DOF knee kinematic curves of the healthy participants during gait cycles are illustrated in Fig. 2A. Two flexion peaks were detected. The first flexion peak occurred in the early stance phase, and was at approximately 45% of the gait cycle where the knee extended fully. Thereafter, flexion of the knee occurred again at toe-off. In the swing phase, flexion continued until it reached another peak of 60.56 ± 6.07° at approximately 77% of the gait cycle. The knee motion then returned to heel strike with extension and started another cycle. The tibiofemoral motion patterns of internal/external rotation and adduction/abduction showed tendencies similar to those of flexion/extension.
Table 2.
6-DOF knee kinematics of the healthy participants
| 95% Confidence Interval | |||
|---|---|---|---|
| Mean ± SD | Lower limit | Upper limit | |
| Adduction/abduction (°) | 10.07 ± 4.04 | 4.34 | 19.93 |
| Internal/external rotation (°) | 15.13 ± 4.85 | 7.66 | 26.54 |
| Flexion/extension (°) | 60.56 ± 6.07 | 49.17 | 72.92 |
| Anterior/posterior translation (cm) | 1.79 ± 0.75 | 0.66 | 3.55 |
| Proximal/distal translation (cm) | 1.58 ± 0.54 | 0.77 | 2.91 |
| Medial/lateral translation (cm) | 1.10 ± 0.42 | 0.48 | 2.19 |
6-DOF, six degrees of freedom; SD, standard deviation
Fig. 2.
6-DOF knee kinematic curves of the healthy participants (A) and patients with ACL injuries (B) in this study
The first peak of anterior/posterior translation occurred slightly before toe-off. From toe-off to approximately 69% at the gait cycle, the femur translated backward. Thereafter, it reversed to move forward until reaching the second peak. The knee was then drawn backward during the remaining swing phase. After heel strike, the femur began to translate proximally and then reached a peak value of 1.79 ± 0.75 cm as the knee reached the maximal flexion in the swing phase. Thereafter, the femur moved close to the tibia again.
In the medial/lateral direction, the femur shifted inward during the heel strike and remained nearly constant until toe-off, where it moved further inward. After toe-off, the femur began shifting outward with a greater magnitude and reached the maximum of 1.10 ± 0.42 cm at approximately 65% of the gait cycle.
Characteristics of the patients with ACL injuries
Table 3 shows the demographic characteristics and clinical data of the 83 patients with ACL injuries. The mean time from injury to assessment was 2.85 ± 0.91 weeks. Among them, there were 37 patients with concomitant meniscal injuries. The mean preoperative 6-DOF score, Lysholm score, IKDC subjective score and Tegner activity scale of the 83 patients was 74.29 ± 7.23, 70.26 ± 17.55, 66.78 ± 15.79, and 2.28 ± 1.56, respectively (Table 3).
Table 3.
Demographic characteristics and clinical data of the patients with ACL injuries
| Variables | Values |
|---|---|
| Sex (male/female) | 57/26 |
| Age (years) | 27.89 ± 5.35 |
| Height (cm) | 170.56 ± 8.47 |
| Body weight (kg) | 70.55 ± 15.33 |
| BMI (kg/m2) | 24.11 ± 4.07 |
| Injury side (left/right) | 38/45 |
| Time from injury to assessment (weeks) | 2.85 ± 0.91 |
| Concomitant meniscal injuries (yes/no) | 37/46 |
| Preoperative IKDC subjective score | 66.78 ± 15.79 |
| Preoperative Lysholm score | 70.26 ± 17.55 |
| Postinjury Tegner activity scale | 2.28 ± 1.56 |
| Preoperative 6-DOF score | 74.29 ± 7.23 |
ACL, anterior cruciate ligament; BMI, body mass index; IKDC, International Knee Documentation Committee; 6-DOF, six degrees of freedom
6-DOF knee kinematics of the patients with ACL injuries
The 6-DOF knee kinematic curves of the 83 patients with ACL injuries are shown in Fig. 2B. In this study, patients with ACL injuries had significantly greater adduction/abduction (11.94 ± 5.08° vs. 10.07 ± 4.04°, P = 0.002), internal/external rotation (16.56 ± 5.67° vs. 15.13 ± 4.85°, P = 0.021), anterior/posterior translation (2.25 ± 0.95 cm vs. 1.79 ± 0.75 cm, P < 0.001), and proximal/distal translation (2.15 ± 1.03 cm vs. 1.58 ± 0.54 cm, P < 0.001), and significantly smaller flexion/extension than healthy participants (50.48 ± 12.87° vs. 60.56 ± 6.07°, P < 0.001). No significant difference was detected in terms of medial/lateral translation (1.22 ± 0.61 cm vs. 1.10 ± 0.42 cm, P = 0.137) (Table 4).
Table 4.
Comparison of 6-DOF knee kinematics between the patients with ACL injuries and healthy participants
| ACL-injured knees (n = 83) | Healthy knees (n = 1000) | P value | |
|---|---|---|---|
| Adduction/abduction (°) | 11.94 ± 5.08 | 10.07 ± 4.04 | 0.002 |
| Internal/external rotation (°) | 16.56 ± 5.67 | 15.13 ± 4.85 | 0.021 |
| Flexion/extension (°) | 50.48 ± 12.87 | 60.56 ± 6.07 | < 0.001 |
| Anterior/posterior translation (cm) | 2.25 ± 0.95 | 1.79 ± 0.75 | < 0.001 |
| Proximal/distal translation (cm) | 2.15 ± 1.03 | 1.58 ± 0.54 | < 0.001 |
| Medial/lateral translation (cm) | 1.22 ± 0.61 | 1.10 ± 0.42 | 0.137 |
6-DOF, six degrees of freedom; ACL, anterior cruciate ligament
Validation of the correlation between the 6-DOF score and PROMs
The Spearman coefficient revealed significant correlations between the 6-DOF score and the Lysholm score (ρ = 0.375, P < 0.001) and the Tegner activity scale (ρ = 0.273, P = 0.016). There was no statistically significant correlation between the 6-DOF score and the IKDC subjective score (ρ = 0.145, P = 0.208) (Table 5).
Table 5.
Correlation between the 6-DOF score and PROMs
| IKDC subjective score | Lysholm score | Tegner activity scale | ||
|---|---|---|---|---|
| 6-DOF score | ρ | 0.145 | 0.375 | 0.273 |
| P value | 0.208 | < 0.001 | 0.016 |
6-DOF, six degrees of freedom; PROMs, patient-reported outcome measurements; IKDC, International Knee Documentation Committee
Discussion
The primary finding of this study was the identification of the 6-DOF gait pattern based on a large sample dataset of healthy Chinese people, which provided more reliable and convincing results than previous preliminary research [20]. Second, this study proposed a 6-DOF knee function score based on the gait data. Finally, upon assessing 83 patients with ACL injuries, the final results revealed that the 6-DOF score was significantly correlated with the Lysholm score and the Tegner activity scale. However, no significant correlation was found between the 6-DOF score and the IKDC subjective score.
In the field of motion capture systems, the OMC technique is the most widely used, and the representatives of this technique mainly include large-scale capture systems such as Vicon, Qualisys, and Opti-Track [24]. However, their use in clinical settings is limited due to the large space they require, the complicated operation, and the inability to accurately quantify the 6-DOF motion range of the knee joint. As a portable motion capture system, the Opti-Knee motion analysis system uses infrared stereoscopic tracking and digital navigation techniques to perform quantitative analysis of 6-DOF knee kinematics, with the advantages of a small footprint and simple operation. At present, relevant studies have confirmed that the Opti-Knee system has good accuracy and repeatability in knee kinematics evaluation [19, 21, 25].
Prior to this study, Zhang et al. [21] used the Opti-Knee system to measure 6-DOF knee kinematics in 28 healthy subjects during gait at a speed of 3 km/h and reported that sex differences existed in the movement patterns of axial rotation and mediolateral translation. On the other hand, compared to the literature on 6-DOF knee kinematics in subjects of other racial groups, the angular range of motion obtained in their study was smaller than that reported in the studies by Andriacchi et al. [26], Chao et al. [27], and Gao et al. [28]. This suggests that angular rotation in knee kinematics may be affected by body dimensions. However, due to the relatively small sample size and the distribution of participants to young people aged between 20 and 30 years, the preliminary study may not fully reflect the 6-DOF knee kinematics in healthy people [21]. Therefore, we enrolled healthy participants ranging in age from 18 to 60 years to collect data on 6-DOF knee kinematics under the same conditions. Based on the motion curve of 500 healthy Chinese people measured by the Opti_Knee system, this study proposed a medical reference indicatrix of motion range in 6-DOF knee kinematics. Compared with the study by Zhang et al. [21], the motion ranges of flexion/extension (60.6° vs. 57.4°), internal/external rotation (15.1° vs. 10.9°), anterior/posterior translation (17.9 mm vs. 12.8 mm), and medial/lateral translation (11.0 mm vs. 9.4 mm) in this study were greater, whereas the motion ranges of adduction/abduction (10.1° vs. 9.3°) and proximal/distal translation (15.8 mm vs. 15.0 mm) were similar.
In addition, other previous studies have also reported 6-DOF knee kinematics during gait in healthy people [25, 29, 30]. Among them, Liu et al. [25] analyzed the gait patterns of 40 healthy participants using the Opti_Knee system to investigate the kinematic differences in the 6-DOF between walking and running at different speeds. In particular, they detected motion ranges of 60.9 ± 6.2° in flexion/extension, 14.0 ± 4.2° in internal/external rotation, and 9.8 ± 3.7° in abduction/adduction when the walking speed was set to 3 km/h, which were similar to the data in this study. The consistency of the results between different studies suggested good interobserver reproducibility within motion capture systems of this type. Moreover, the results of 6-DOF knee kinematics were close to those results measured by biplane fluoroscopy, which is the gold standard in kinematic analysis [31–33]. Thus, the accuracy of portable simplified motion capture systems has been improved rapidly over recent years. Although such systems cannot yet substitute biplanar fluoroscopy, they still have broad application prospects in the field of clinical gait analysis [34–36].
The correlation between the developed 6-DOF score and conventional PROMs was further validated in this study. Generally, the knee functional outcome is determined synthetically by various domains, including pain, stability, activity level, and symptomatic manifestation. In this respect, the Lysholm score and Tegner activity scale are both validated and reliable PROMs for assessing ACL-injured knee function. Correspondingly, there was a significant correlation between the 6-DOF score and PROMs measurements in our study, suggesting that the former may have the ability to detect functional differences between ACL-injured and healthy knees through gait testing. In essence, the 6-DOF score is an effective interpretation of dynamic knee stability in the sagittal, coronal, and axial planes, which is paramount to patients’ overall knee function. In addition, the 6-DOF score is a quantifiable outcome measured by an objective process with maneuverability and repeatability. These advantages minimize performance bias and detection bias, which are inherent deficiencies of PROMs [37].
However, no significant correlation was found between the outcomes of the 6-DOF score and the IKDC subjective score in this study. There are several potential reasons that might explain the insignificance of this result. Above all, the items related to pain and symptoms, rather than those related to stability or activity, account for larger weight attributes in the IKDC subjective score than in the Lysholm score and Tegner activity scale. Furthermore, there is no necessary correlation between dynamic and static knee stability, while the former is considered more important for knee functional outcomes. Although ACL-deficient knees exhibit some degree of static knee instability, several effects, such as muscle activation and soft tissue restraints, can enhance dynamic knee stability during gait [38, 39]. Finally, under the circumstance of a preset baseline treadmill speed of 3 km/h, patients with ACL injuries might be unable to maintain this speed throughout the procedure because of pain or apprehension of instability, resulting in a lower speed that could negatively affect the final results of the 6-DOF score. As a whole, this lack of significance may not constitute a solid trend in this regard, and consequently, the correlation needs to be further validated with more refined methodologies and fewer heterogeneous participants in future studies.
The results of this study should be interpreted in the context of its potential limitations. First, the validation of the 6-DOF score for ACL injuries is at a preliminary stage with only preoperative data and relatively limited sample size. Further efforts are needed for comprehensive validation in terms of reliability, measurement error, content validity, structural validity, criterion validity, and responsiveness [40]. Second, the gait pattern was determined during treadmill walking rather than flat-ground walking. As a result, the dataset might not be able to completely interpret the gait pattern of healthy people in the most natural state. Third, patients with meniscal injuries who could have affected joint kinematics were not excluded. Fourth, the limitation of skin marker-based motion analysis is inevitable, and soft tissue artifacts may be influential in our protocol because of the impact of the walking task [41]. Moreover, kinematic differences other than knee instability could increase the score differences between groups. Careful attention should be given when this scoring system is used to make clinical decisions, as more studies are necessary to clarify its utility in clinical settings.
Conclusion
A normative 6-DOF knee kinematic reference range for the Chinese population was proposed in this study based on a large sample dataset, which provided a reference in clinical evaluation for further in-depth studies. The 6-DOF dynamic score developed accordingly showed significant correlations with conventional PROMs, such as the Lysholm score and Tegner activity scale, and may provide comprehensive and meaningful information on knee function and dynamic stability for patients with ACL injuries. However, the validation of the 6-DOF score requires further investigation.
Acknowledgements
The authors would like to thank all the participants and researchers who contributed to this study.
Abbreviations
- ACL
Anterior cruciate ligament
- OMC
Optical motion capture
- 6-DOF
Six degrees of freedom
- IKDC
International Knee Documentation Committee
- PROMs
Patient-reported outcome measurements
- DTW
Dynamic time warping
- SE
Standard error
- BMI
Body mass index
- SD
Standard deviation
Author contributions
Y.M., L.H., and J.L. (Jian Li) contributed to the study design and conception. Y.M., T.L., and L.H. contributed to the data collection. L.H. and T.L. contributed to the statistical analysis. J.L. (Junqiao Li) and Y.M. wrote the draft manuscript. Y.X. revised the manuscript. All authors read and approved the final manuscript.
Funding
This work was supported by the 1.3.5 Project for Disciplines of Excellence of West China Hospital, Sichuan University (ZYGD21005).
Data availability
The corresponding author can provide the datasets used and analyzed during the current study upon a reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the ethical principles of the Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee on Biomedical Research, West China Hospital of Sichuan University (No. 2016-99). The patients/participants provided their written informed consent to participate in this study.
Clinical trial number
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Junqiao Li and Yunhe Mao contributed equally to this work.
Contributor Information
Yan Xiong, Email: luyibingli@163.com.
Jian Li, Email: hxlijian.china@163.com.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The corresponding author can provide the datasets used and analyzed during the current study upon a reasonable request.