Introduction. Hip resurfacing arthroplasty has been surgical options in younger and more active patients with osteoarthritis (OA) and osteonecrosis (ON) of the femoral head. Although excellent midterm results of this procedure have been reported, there is a concern about postoperative impingement between the preserved femoral neck and the acetabular component. There were few reports about kinematics after hip resurfacing. Therefore, the purpose of this study was to investigate the postoperative motion analysis after hip resurfacing using a noble dynamic flat-panel detector (FPD) system by which clear sequential images were obtained with low dose radiation exposure. Materials and methods. 11 patients (mean age: 47.8 ± 7.4), 15 hips were included in this study. There were ten men and one woman. The preoperative diagnoses were ON of the femoral head in 10 hips, OA in 3 hips, and others in 2 hips. Mean postoperative follow-up period was 25.1 ± 21.6 months. Femoral anteversion, cup inclination and cup anteversion were measured on computed tomography and plain radiograph. Impingement signs such as the reactive osteophyte formation and divot around the femoral neck were also investigated on the anteroposterior (AP) and lateral radiographs. Sequential images of active and passive flexion motion in 45-degrees semilateral position, and active abduction motion in a supine position were obtained using a noble dynamic FPD system. Results. Mean femoral anteversion was 13.2° ± 9.1° and mean cup inclination and anteversion were 35.4° ± 2.3° and 6.8° ± 3.9°, respectively. The reactive osteophyte formation apeared in 1 hip (6.7%) on AP radiograph and 4 hips (26.7%) on lateral radiograph, and divot sign was observed in 1 hip (6.7%) on each radiographs. The location of the impingement signs were mostly observed at the anteroinferior portion of the femoral neck. In motion analysis, impingement between the femoral neck and the acetabular component was detected in 12 hips (80.0%) in flexion motion and 2 hips (13.3%) in abduction motion (Figure). There were no findings of the subluxation between the acetabular and femoral component after the impingement, but cooperative motion of lumber and pelvic flexion was occurred. None of the patients who had a impingement signs on plain radiographs and motion analysis had any symptoms and pain during hip motion. Discussion and conclusion. Postoperative motion analysis is a noble and useful technique and that can detect various findings which could not be detected by the routine static radiographs. Also, postoperative kinematics after hip resurfacing remains unknown and we investigated it in detail using a noble dynamic FPD system. The present study indicated that impingement between the preserved femoral neck and the acetabular component and consequent cooperative motion of lumber and pelvic flexion were similar to the physiological motion of the nomal hip joint. No sign of the subluxation between the component proved the good stability of the resurfacing articulation. Proprioception of the preserved femoral neck can be related to this unique kinematics

INTRODUCTION. In patients with neural disorders such as cerebral palsy, three-dimensional marker-based motion analysis has evolved to become a well standardized procedure with a large impact on the clinical decision-making process. On the other hand, in knee arthroplasty research, motion analysis has been little used as a standard tool for objective evaluation of knee joint function. Furthermore, in the available literature, applied methodologies are diverse, resulting in inconsistent findings [1]. Therefore we developed and evaluated a new motion analysis framework to enable standardized quantitative assessment of knee joint function. MATERIALS AND METHODS. The proposed framework integrates a custom-defined motion analysis protocol with associated reference database and a standardized post-processing step including statistical analysis. Kinematics are collected using a custom-made marker set defined by merging two existing protocols and combine them with a knee alignment device. Following a standing trial, a star-arc hip motion pattern and a set of knee flexion/extension cycles allowing functional, subject-specific calibration of the underlying kinematic model, marker trajectories are acquired for three trials of a set of twelve motor tasks: walking, walking with crossover turn, walking with sidestep turn, stair ascent, stair descent, stair descent with crossover turn, stair descent with sidestep turn, trunk rotations, chair rise, mild squat, deep squat and lunge. This specific set of motor tasks was selected to cover as much as possible common daily life activities. Furthermore, some of these induce greater motion at the knee joint, thus improving the measurement-to-error ratio. Kinetics are acquired by integrating two forceplates in the walkway. Bilateral muscle activity of 8 major muscles is monitored with a 16 channel wireless electromyography (EMG) system. Finally, custom-built software with an associated graphical user interface was created for automated and flexible analysis of gait lab data, including repeatability analysis, analysis of specific kinematic, kinetic and spatiotemporal parameters and statistical comparisons. RESULTS. Following ethical approval and informed consent, the proposed framework was successfully applied in a control group of 80 normal subjects within a wide age-range (age: 54.5Y±19.1; BMI: 25.5±4.0; 40M/40F; 60 Caucasian, 20 Asian) thus constructing the reference database for control. Moreover, the same framework was applied successfully in a randomly selected group of 10 patients with a bi-compartmental knee replacement (BKR) (age: 67.3Y±5.3; BMI: 29.7±3.1; time post-op: 1.65Y±0.4; 2M/8F Caucasian). Comparison between these patients and age-matched controls demonstrates that, for a large range of motor tasks, knee joint kinematics after BKR are as much consistent with the healthy controls (coefficient of multiple correlation (CMC) =0.49) as the consistency within a group of controls or BKR-subjects individually (CMC=0.52). Nevertheless, also significant differences (p<0.0167) were identified which are indicative for retention of pre-operative motion patterns and/or remaining compensations. CONCLUSION. The proposed framework allows in-vivo evaluation of knee joint performance in a standardized, objective and non-invasive way. It is applicable in both healthy subjects and knee replacement patients and is shown to be sufficiently sensitive to detect even relatively small differences between the two populations

The literature indicates that femoroacetabular impingement (FAI) patients do not return to the level of controls (CTRL) following surgery. The purpose of this study was to compare hip biomechanics during stair climbing tasks in FAI patients before and two years after undergoing corrective surgery against healthy controls (CTRL). A total of 27 participants were included in this study. All participants underwent CT imaging at the local hospital, followed by three-dimensional motion analysis done at the human motion biomechanics laboratory at the local university. Participants who presented a cam deformity >50.5° in the oblique-axial or >60° in the radial planes, respectively, and who had a positive impingement test were placed in the FAI group (n=11, age=34.1±7.4 years, BMI=25.4±2.7 kg/m2). The remaining participants had no cam deformity and negative impingement test and were placed in the CTRL group (n=16, age=33.2±6.4 years, BMI=26.3±3.2 kg/m2). The CTRL group completed the biomechanics protocol once, whereas the FAI group completed the protocol twice, once prior to undergoing corrective surgery for the cam FAI, and the second time at approximately two years following surgery. At the human motion biomechanics laboratory, participants were outfitted with 45 retroreflective markers placed according to the UOMAM marker set. Participants completed five trials of stairs task on a three step instrumented stair case to measure ground reaction forces while 10 Vicon MX-13 cameras recorded the marker trajectories. Data was processed using Nexus software and divided into stair ascent and stair descent tasks. The trials were imported into custom written MatLab software to extract peak pelvis and hip kinematics and hip kinetic variables. Non-parametric Kruskal-Wallis tests were used to determine significant (p < 0.05) differences between the groups. No significant differences occurred during the stair descent task between any of the groups. During the stair ascent task, the CTRL group had significantly greater peak hip flexion angle (Pre-Op=58±7.1°, Post-Op=58.1±6.6°, CTRL=64.1±5.1°) and sagittal hip range of motion (ROM) (Pre-Op=56.7±6.7°, Post-Op=56.3±5.5°, CTRL=61.7±4.2°) than both the pre- and post-operative groups. Pre-operatively, the FAI group had significantly less peak hip adduction angle (Pre-Op=2±4.5°, Post-Op=3.4±4.4°, CTRL=5.5±3.7°) and hip frontal ROM (Pre-Op=9.9±3.4°, Post-Op=11.9±5.4°, CTRL=13.4±2.5°) compared to the CTRL group. No significant differences occurred in the kinetic variables. Our findings are in line with the Rylander and colleagues (2013) who also found that hip sagittal ROM did not improve following corrective surgery. Their study included a mix of cam and pincer-type FAI, and had a mean follow-up of approximately one year. Our cohort included only cam FAI and they had a mean follow-up of approximately two years, indicating with the extra year, the patients still did not show sagittal hip kinematics improvement. In the frontal plane, there was no significant difference between the post-op and the CTRL, indicating that the postoperative FAI reached the level of the CTRLs. This is in line with recent work that indicates a more medialized hip contact force vector following surgery, suggesting better hip stabilization

The glenohumeral joint is an important joint with large mobility of the human upper extremity. In shoulder arthroplasty patients often has an unsatisfactory outcome. In order to understand the biomechanical complexity of the shoulder, a novel computer controlled experimental shoulder simulator with an innovative muscle control were constructed. The main component of the simulator includes the active pneumatic muscles to replicate the deltoid and the rotator-cuff function and two springs as passive muscle. The aim of this study is to evaluate the impact of a variation of shoulder joint geometries on shoulder biomechanics in the basis of motion analysis. The radius of the glenoid cavity varied from 28–33mm with 2.5mm increment while the radius the humeral head are varied from 20.1–25.1 with 2.5mm increment. The “teach-in” function of the simulator allows an operator to assign the movement to the simulator where the lengths of the pneumatic muscles are recorded. Then the simulator repeats the assigned movement according to the recorded muscles length. The daily living activities includes abduction/adduction, internal/external rotation with adducted arm, and circumduction. The results show promising repeatability of the simulator with minor deviation. However, damage on the surface of the humeral head has been found which should be further studied for both shoulder behavior investigation and the shoulder simulator optimisation. Therefore, this study is a decent initial study toward the verification of the simulator and lead to a better understanding of shoulder biomechanical behavior to cope with the clinical problems in the future

Purpose

The purpose of this study was to clarify the relationship between the laxity of surrounding soft tissue and artificial joint kinetics during knee articulation, where total knee arthroplasty had been performed using ceramic LFA artificial knee joints (LFA-TKA below) from Japan Medical Materials (JMM).

Introduction

Compared with the cruciate-retaining (CR) insert for total knee arthroplasty (TKA), the cruciate-substituting (CS) insert has a raised anterior lip, providing greater anterior constraint, and thus, can be used in cases of posterior cruciate ligament (PCL) sacrifice. However, studies have shown that the PCL maintains femoral rollback during flexion, acts as a stabilizer against distal traction force and aids knee joint proprioception; therefore, the argument for PCL excision in CS TKA remains controversial. The purpose of this study was to analyze CS TKA kinematics and identify the role of the PCL.

Introduction

After total hip arthroplasty, dislocation is one of the most frequent serious early complications. This occurs in part due to impingement (catching and leverage of the neck-cup on the inlay/cup border). Impingement may also negatively impact long-term outcomes.

Introduction:

The widespread use of TKA promoted studies on kinematics after TKA, particularly of the femorotibial joint. Knee joint kinematics after TKA, including the range of motion (ROM) and the physical performance, are also influenced by the biomechanical properties of the patella. Surgeons sometimes report complications after TKA involvinganterior knee pain, patellofemoral impingement and instability. However, only few studies have focused specially on the patella. Because the patella bone is small and overlapped with the femoral component on scan images. In addition, the patellar component in TKA is made of x-ray–permeable ultra-high molecular weight polyethylene. It is impossible to radiographically determine the external contour of the patellar component precisely. No methods have been established to date to track the dynamic in vivo trajectory of the patella component. In this study, we analyzed the in vivo three-dimensional kinematics of the patellar component in TKA by applying our image matching method with image correlations.

During total knee replacement (TKR), knee surgical navigation systems (KSNS) report in real time relative motion data between the tibia and the femur from the patient under anaesthesia, in order to identify best possible locations for the corresponding prosthesis components. These systems are meant to support the surgeon for achieving the best possible replication of natural knee motion, compatible with the prosthesis design and the joint status, in the hope that this kinematics under passive condition will be then the same during the daily living activities of the patient. Particularly, by means of KSNS, knee kinematics is tracked in the original arthritic joint at the beginning of the operation, intra-operatively after adjustments of bone cuts and trial components implantation, and after final components implantation and cementation. Rarely the extent to which the kinematics in the latter condition is then replicated during activity is analysed. As for the assessment of the active motion performance, the most accurate technique for the in-vivo measurements of replaced joint kinematics is three-dimensional video-fluoroscopy. This allows joint motion tracking under typical movements and loads of daily living. The general aim of this study is assessing the capability of the current KSNS to predict replaced joint motion after TKR. Particularly, the specific objective is to compare, for a number of patients implanted with two different TKR prosthesis component designs, knee kinematics obtained intra-operatively after final component implantation measured by means of KSNS with that assessed post-operatively at the follow-up by means of three-dimensional video-fluoroscopy.

Thirty-one patients affected by primary gonarthrosis were implanted with a fixed bearing posterior-stabilized TKR design, either the Journey® (JOU; Smith&Nephew, London, UK) or the NRG® (Stryker®-Orthopaedics, Mahwah, NJ-USA). All implantations were performed by means of a KSNS (Stryker®-Leibinger, Freiburg, Germany), utilised to track and store joint kinematics intra-operatively immediately after final component implantation (INTRA-OP). Six months after TKR, the patients were followed for clinical assessment and three-dimensional video fluoroscopy (POST-OP). Fifteen of these patients, 8 with the JOU and 7 with the NRG, gave informed consent and these were analyzed. At surgery (INTRA-OP), a spatial tracker of the navigation system was attached through two bi-cortical 3 mm thick Kirschner wires to the distal femur and another to the proximal tibia. The conventional navigation procedure recommended in the system manual was performed to calculate the preoperative deformity including the preoperative lower limb alignment, to perform the femoral and tibial bone cuts, and to measure the final lower limb alignment. All these assessment were calculated with respect to the initial anatomical survey, the latter being based on calibrations of anatomical landmarks by an instrumented pointer. Patients were then analysed (POST-OP) by three-dimensional video-fluoroscopy (digital remote-controlled diagnostic Alpha90SX16; CAT Medical System, Rome-Italy) at 10 frames per second during chair rising-sitting, stair climbing, and step up-down. A technique based on CAD-model shape matching was utilised for obtaining three-dimensional pose of the prosthesis components. Between the two techniques, the kinematics variables analysed for the comparison were the three components of the joint rotation (being the relative motion between the tibial and femoral components represented using a standard joint convention, the translation of the line through the medial and lateral contact points (being these points assumed to be where the minimum distance between the femoral condyles and the tibial baseplate is observed) on the tibial baseplate and the corresponding pivot point, and the location of the instantaneous helical axes with the corresponding mean helical axis and pivot point.

In all patients and in both conditions, physiological ranges of flexion (from −5° to 120°), and ab-adduction (±5°) were observed. Internal-external rotation patterns are different between the two prostheses, with a more central pivoting in NRG and medial pivoting in JOU, as expected by the design. Restoration of knee joint normal kinematics was demonstrated also by the coupling of the internal rotation with flexion, as well as by the roll-back and screw-home mechanisms, observed somehow both in INTRA- and POST-OP measurements. Location of the mean helical axis and pivot point, both from the contact lines and helical axes, were very consistent over time, i.e. after six months from intervention and in fully different conditions. Only one JOU and one NRG patient had the pivot point location POST-OP different from that INTRA-OP, despite cases of paradoxical translation.

In all TKR knees analysed, a good restoration of normal joint motion was observed, both during operation and at the follow-up. This supports the general efficacy of the surgery and of both prosthesis designs. Particularly, the results here reported show a good consistency of the measurements over time, no matter these were taken in very different joint conditions and by means of very different techniques. Intra-operative kinematics therefore does matter, and must be taken into careful consideration for the implantation of the prosthesis components. Joint kinematics should be tracked accurately during TKR surgery, and for this purpose KSNS seem to offer a very good support. These systems not only supports in real time the best possible alignment of the prosthesis components, but also make a reliable prediction of the motion performance of the replaced joint. Additional analyses will be necessary to support this with a statistical power, and to identify the most predicting parameters among the many kinematics variables here analysed preliminarily.

Cervical spine collars are applied in trauma situations to immobilise patients' cervical spines. Whilst movement of the cervical spine following the application of a collar has been well documented, the movement in the cervical spine during the application of a collar has not been. There is universal agreement that C-spine collars should be applied to patients involved in high speed trauma, but there is no consensus as to the best method of application.

The clinical authors have been shown two different techniques on how to apply the C-spine collars in their Advanced Life Support Training (ATLS). One technique is the same as that recommended by the Laerdal Company (Laerdal Medical Ltd, Kent) that manufactures the cervical spine collar that we looked at. The other technique was refined by a Neurosurgeon with an interest in pre-hospital care. In both techniques the subjects' head is immobilised by an assistant whilst the collar is applied.

We aimed to quantify which of these techniques caused the least movement to the cervical spine. There is no evidence in the literature quantifying how much movement in any plane in the unstable cervical spine is safe. Therefore, we worked on the principle: the less movement the better.

The Qualisys Motion Capture System (Qualisys AB, Gothenburg, Sweden) was used to create an environment that would measure movement on the neck during collar application. This system consisted of cameras that were pre-positioned in a set order determined by trial and error initially. These cameras captured reflected infra-red light from markers placed on anatomically defined points on the subject's body. As the position of the cameras was fixed then as the patients moved the markers through space, a software package could deduce the relative movement of the markers to each camera with 6 degrees of freedom (6DOF).

Six healthy volunteers (3 M, 3 F; age 21-29) with no prior neck injuries acted as subjects. The collar was always applied by the same person. Each technique was used 3 times on each subject. To replicate the clinical situation another volunteer would hold the head for each test.

The movements we measured were along the x, y, and z axes, thus acting as an approximation to flexion, extension and rotation occurring at the C-spine during collar application. The average movement in each axis (x, y and z) was 8 degrees, 8 degrees and 5 degrees respectively for both techniques. No further data analysis was attempted on this small data set.

However this pilot study shows that our method enables researchers to reproducibly collect data about cervical spine movement whilst applying a cervical collar.

To assess long and short term kinematic gait outcomes after rectus femoris transfers (RFT) in ambulatory children with cerebral palsy (CP). A retrospective review was conducted of ambulatory children with spastic diplegic CP, who had RFT plus motion analysis preoperatively and 1 year post-operatively. Those with 5 and 10 year post-operative motion analysis were also included. The primary variables were: peak knee flexion range of motion in swing (PKFSW), timing of peak knee flexion in swing as a percent of the gait cycle (PKF%GC), and knee range of motion from peak to terminal swing (KROM). Responders and non-responders were identified. Descriptive, kinematic and kinetic variables were evaluated as predictors of response. 119 ambulatory children (237 limbs) with spastic diplegic CP who had RFT were included. Mean age at surgery was 10.2 years (range 5.5 to 17.5). Sixty-seven participants were classified at GMFCS Level II and 52 at GMFCS Level III. All participants (237 limbs) had a preoperative and 1 year postoperative motion analysis. Motion analysis at 5 and 10 years post-operatively included 82 limbs and 28 limbs, respectively. Ninety-three (39%) limbs improved in both PKFSW and PKF%GC. PKFSW improved in 59% of limbs. Responders started 1.2 SD below the mean PKFSW preoperatively, and improved by an average of 1.9 SD to reach a normal range at 1 year post-operatively (p < 0.05). Improvement was maintained at 5 and 10 years postoperatively. Those at GMFCS level II were more likely [OR 1.71, CI 1.02, 2.89] to have improved PKFSW at 1 year postoperatively than those at GMFCS level III. PKF%GC improved in 70% of limbs. Responders had delayed PKF%GC, starting 10 SD above the mean (later in the gait cycle) preoperatively. Their timing improved towards normal values: 5 SD, 5.9 SD, 3.5 SD from the mean, (earlier in the gait cycle) at 1, 5 and 10 years postoperatively, respectively (p<0.05). KROM improved in only 24% of limbs. For all variables, there was a significant difference in mean preoperative values between responders and non-responders (p<0.05). RFT improves short and long-term kinematic gait outcomes. The majority of children responded to RFT with improvements in PKFSW or PKF%GC at 1, 5, and 10 years post RFT. GMFCS level is a predictor of improved PKFSW, with children at GMFCS Level II having an increased likelihood of improvement at 1 year post surgery. Children who have worse preoperative values of PKFSW, PKF%GC, and KROM have a greater potential for benefit from RFT. Characteristics associated with responders who maintain long term positive outcomes need to be identified

Objective. Emergence of low-cost wearable systems has permitted extended data collection for unsupervised subject monitoring. Recognizing individual activities performed during these sessions gives context to recorded data and is an important first step towards automated motion analysis. Convolutional neural networks (CNNs) have been used with great success to detect patterns of pixels in images for object detection and recognition in many different applications. This work proposes a novel image encoding scheme to create images from time-series activity data and uses CNNs to accurately classify 13 daily activities performed by instrumented subjects. Methods. Twenty healthy subjects were instrumented with a previously developed wearable sensor system consisting of four inertial sensors mounted above and below each knee. Each subject performed eight static and five dynamic activities: standing, sitting in a chair/cross-legged, kneeling on left/right/both knees, squatting, laying, walking/running, biking and ascending/descending stairs. Data from each sensor were synchronized, windowed, and encoded as images using a novel encoding scheme. Two CNNs were designed and trained to classify the encoded images of both static and dynamic activities separately. Network performance was evaluated using twenty iterations of a leave-one-out validation process where a single subject was left out for test data to estimate performance on future unseen subjects. Results. Using 19 subjects for training and a single subject left out for testing per iteration, the average accuracy observed when classifying the eight static activities was 98.0% ±2.9%. Accuracy dropped to 89.3% ±10.6% when classifying all dynamic activities using a separate model with the same evaluation process. Ascending/descending stairs, walking/running, and sitting on a chair/squatting were most commonly misclassified. Conclusions. Previous related work on activity recognition using accelerometer and/or gyroscope raw signals fails to provide sufficient data to distinguish static activities. The proposed method operating on lower limb orientations has classified eight static activities with exceptional accuracy when tested on unseen subject data. High accuracy was also observed when classifying dynamic activities despite the similarity of the activities performed and the expected variance of individuals’ gait. Accuracy reported in existing literature classifying comparable activities from other wearable sensor systems ranges between 27.84% to 84.52% when tested using a similar leave-one-subject-out validation strategy[1]. It is expected that incorporating these trained models into the previously developed wearable system will permit activity classification on unscripted instrumented activity data for more contextual motion analysis

Introduction. Motion analysis is a validated method of assessing technical dexterity within surgical skills centers. A more accessible and cost-effective method of skills assessment is to use a global rating scale (GRS). We aimed to perform a validation experiment to compare an arthroscopic GRS against motion analysis for monitoring orthopaedic trainees learning simulated arthroscopic meniscal repairs. Methods. An arthroscopic meniscal repair task on a knee simulator was set up in a bioskills laboratory. Nineteen orthopaedic trainees with no experience of meniscal repair were recruited and their performance assessed whilst undertaking a standardized meniscal repair on 12 occasions. An arthroscopic GRS, assessing parameters such as “depth perception,” “bimanual dexterity,” “instrument handling,” and “final product analysis” was used to evaluate technical skill. Performance was assessed blindly by watching video recordings of the arthroscopic tasks. Dexterity analysis was performed using a motion analysis tracking system which measured “time taken,” “total path length of the subject's hands,” and “number of hand movements”. Results. Motion analysis objectively defined the learning curves and demonstrated significant improvement in performance over the 12 tasks (p< 0.0001). The GRS demonstrated the same learning curve with a significant improvement in performance (p< 0.0001). Importantly, for each individual subject, there was significant improvement in performance as assessed by GRS over the 12 tasks (p< 0.0001). There was a moderate correlation (p< 0.0001) between GRS and all the motion analysis parameters (r values: time=−0.58, path length=−0.58, hand movements=−0.51). Conclusion. Established arthroscopic GRSs have not previously been used to monitor learning curves during complex arthroscopic tasks. The results demonstrate that both the GRS and motion analysis are able to detect performance improvement during such tasks. This further validates the arthroscopic GRS for use in monitoring individual trainees and has the advantage over motion analysis of being directly transferrable to the operating room

A quick, portable and reliable tool for predicting ACL injury could be an invaluable instrument for athletes, coaches, and clinicians. The gold standard, Vicon motion analysis, despite having a high sensitivity and risk specificity, is not practical for coaches or clinicians to use on a routine basis for assessing athletes. The present study validated the Kinect device to the currently used method of chart review in predicting athletes at high risk. A total of 114 participants were recruited from both the men and women McGill Varsity Sports Program. 69 males and 45 female athletes were evaluated to assess the specificity and sensitivity of the Kinect device in predicting athletes at high risk of injury. Each athlete performed three-drop vertical jumps off of a 31cm box and the data was recorded and risk score was generated. Generation of this data is done by our uniquely programmed software that measures landing angles at different time frames and compares live results to previously known data of injured athletes. A chart review was then performed by a clinician, blinded to these risk scores, to risk stratify the same athletes as high or low risk of ACL injury based on their medical charts. Data reviewed incorporated pre-season physical exams along with documented known risk factors for ACL injury, including previous knee injuries, family history of ACL injury, gender, sport, and BMI. Positive risk factors were assigned one point while negative risk factors assigned zero points. The Kinect device, powered by our software, identified 40 athletes as having a high-risk score (> 55%), and subsequently, five (4.39%) sustained an ACL injury by the end of their respective sport seasons. Two male and two female basketball players along with one male soccer player sustained non-contact ACL injuries. Given that all five of the injured athletes were in the cohort of 40 identified as high risk by the Kinect, this yielded a sensitivity of 100% for the device. As for the specificity, the Kinect computed 35 false positives, yielding a specificity of 68% for the duration of the study. The medical chart review identified 36 athletes as high risk and 60 as being low risk of ACL injury. Four of the athletes that sustained an ACL injury were in the group of 36 identified as high risk by the clinician. However, one of the five participants who sustained an ACL injury was not captured by the medical chart assessment, yielding a sensitivity of 80% and a specificity of 65% for the clinician. When it comes to injury prediction, it is preferred to have a high sensitivity even if the specificity is slightly lower as this ensures that all athletes who are at risk will be captured. Our data demonstrated that the chart analysis provided one false negative and led to missing one high-risk athlete who ended up sustaining an ACL injury. Based on the comparison of sensitivity and specificity, the Kinect system provides a slightly better predictive analysis for predicting ACL injury compared to chart review

Introduction. Bicruciate-retaining (BiCR) total knee replacements (TKRs) were designed to improve implant performance; however, functional advantages during daily activity have yet to be demonstrated. Although level walking is a common way to analyze functionality, it has been shown to be a weak test for identifying gait abnormalities related to ACL pathologies. The goal of this study is to set up a functional motion analysis test that will examine the effects of the ACL in TKR patients by comparing knee kinematics, kinetics, and muscle activation patterns during level and downhill walking for patients with posterior-cruciate retaining (PCR) and BiCR TKRs. Methods. Motion and electromyography (EMG) data were collected simultaneously for 12 subjects (4/8 m/f, 64±11 years, 31.3±7.3 BMI, 6/6 right/left) with BiCR TKRs and 15 subjects (6/9 m/f, 67±7 years, 30.5±5.1 BMI, 4/11 right/left) with PCR TKRs during level and downhill walking using the point cluster marker set. Surface electrodes were placed on the vastus medialis obliquus (VMO), rectus femoris (RF), biceps femoris (BF), and semitendinosus (ST) muscles. EMG data are reported as percent relative voluntary contraction (%RVC), normalizing the signal during downhill walking to the mean maximum EMG value during level walking. Results. For level walking, there were no significant differences between groups in knee kinematics, kinetics, and EMG patterns. During downhill walking, subjects with BiCR implants showed significantly lower peak muscle activity in the VMO (73.9 ± 49.1%RVC for BiCR vs. 113 ± 24.0%RVC for PCR; p=0.045) and RF (96.0 ± 25.7%RVC for BiCR vs. 128 ± 28.6%RVC for PCR; p=0.018). There was also a trending higher knee peak flexion moment for the BiCR subjects (2.0 ± 0.6% BW*HT vs. 1.5 ± 0.6% BW*HT, p = .076), as well as significantly more knee flexion at heel strike (5.1 ± 4.7 degrees vs. 1.8 ± 2.8 degrees, p = 0.044) compared with the PCR group. Discussion. Retention of the ACL led to altered muscle recruitment during downhill walking in BiCR subjects compared with PCR subjects. In BiCR subjects, quadriceps activity was reduced during downhill walking compared to level walking. PCR subjects on average did not show this reduction, possibly in compensation for decreased knee stability. While there were only a few significant kinematic/kinetic differences, it appears that BiCR TKRs may offer some neuromuscular benefits during more strenuous tasks like downhill walking. In conclusion, level and downhill walking knee kinematics and kinetics together with the corresponding quadriceps and hamstrings EMG signals begin to build an overall picture of implant functionality during motion analysis testing

Background:. Few clinical hip score include toe-reach motion after THA (put-on-socks, nail-cutting). Some reports have shown whether THA patients can put on socks or not in daily activity, and not shown how they can do it. The purpose of this study is to investigate real pattern of put-on-socks motion in daily activities after THA, and to evaluate safe range of motion for prevention of hip dislocation. Materials and Methods:. Reviewing clinical chart, we investigated highly frequent pattern in wearing socks motion that would cause hip dislocation in ADL in 100 patients with normal lower extremities except for hip joint more than one year after THA, then, we classified the motion pattern. Using an optical 3-D motion analysis (MAC3D system, Motion Analysis, USA), we measured necessary angle of the hip in 10 THA subjects (mean age at operation 61 years old) one year postoperatively, while the patients make such frequent patterns of movement as above. Simultaneously, individual 3-dimensional skeletal model was reconstructed from CT data and implant CAD data. Driving 3-D skeletal model combined with motion analysis data on display (Zed Hip, LEXI), we calculated angle from posture that hip flexion angle was maximum during wearing-socks motion to impingement point (implant and/or bone) for each direction. ALL joint angle was defined as “zero” in supine position. Results:. Resulting from clinical chart, high incident pattern of the motion was “Leg raising pattern” (26%), and “Trunk flexion pattern” (23%) (Figure 1). For above two pattern of the socks-wearing motion, 3-D motion analysis showed that maximum hip flexion angle was 85 ± 13 degrees for leg raising pattern, 88 ± 14 degrees for trunk flexion pattern. Hip angle of abduction/adduction or external/internal rotation was within mean 15 degrees during each motion. 3-D model simulation combined with motion data showed that 39 ± 15 degrees, 33 ± 9.7 degrees for direction of hip flection, 34 ± 17 degrees, 32 ± 11 degrees for direction of hip adduction and 78 ± 21 degrees, 51 ± 21 degrees for direction of hip internal rotation from posture on maximum hip flexion angle to impingement point for each motion, respectively. All cases showed safe range of more than 20 degrees for all direction and impingement occurred between cup and stem in all cases (Figure 2, 3). Discussion:. Recently, there have been trend to decrease limitation of motion in ADL after THA. Safe range of motion without impingement have been enlarged resulting from development of implant design, proper alignment and operative technique. This study showed safe range without impingement in frequent socks-wearing pattern in daily living among THA patients one year after surgery. More research for motion in ADL can lead to remove postoperative restrictions in THA patients

Objective. To investigate the effect of lab-based simulator training, on the ability of surgical trainees to perform diagnostic knee arthroscopy. Method. 20 orthopaedic SHOs with minimal arthroscopic experience were randomised to 2 groups. 10 received a fixed protocol of simulator based arthroscopic skills training using a bench-top knee model. Learning curves were clearly demonstrated using motion analysis equipment to monitor performance. All 20 then spent an operating list with a blinded consultant trainer. They received instruction and demonstration of diagnostic knee arthroscopy before performing the procedure independently. Their performance was assessed using the intra-operative section of the Orthopaedic Competence Assessment Project (OCAP) procedure based assessment (PBA) protocol for diagnostic arthroscopy. Performance was further quantified with a ten point global rating assessment scale. Results. Motion analysis demonstrated objective and significant improvement in performance during simulator training. In theatre the simulator-trained group performed significantly better than the untrained group. The simulator trainees were scored as OCAP competent on more than 70% of occasions, compared to less than 15% for the untrained group (p<0.01). The mean global rating score of the trained group was 24.5 out of 45 compared with 12 for the untrained group (p<0.01). Conclusion. Learning curves showing significantly improved performance at simulated diagnostic knee arthroscopy are clearly demonstrated using motion analysis assessment. Arthroscopic simulator training led to subsequent significant improvement in operating theatre performance as determined by OCAP and a global rating assessment scale. This demonstrates a degree of transfer validity from lab based arthroscopic simulator training using motion analysis assessment to the operating theatre. In addition OCAP PBAs appear to provide a useful framework for in theatre assessment; however questions are raised about the need for more objective assessment tools in order to truly distinguish between trainees varying levels of competence

Background. Few clinical hip score include toe-reach motion after THA (put-on-socks, shoe-ties, nail-cuttingãf»ãf»ãf») Some reports have shown whether THA patients can put on socks or not in daily activity, and not shown how they can do it. The purpose of this study is to investigate real pattern of put-on-socks motion in daily activities after THA, and to evaluate the characteristics of the motion quantitatively. Materials and Methods. 1st step. Reviewing clinical chart, we investigated highly frequent pattern in wearing socks motion that would cause dislocation in ADL in 100 patients with normal lower extremities except for hip more than one year after THA, then, we classified the motion pattern. 2nd step:. Using an optical 3-D motion analysis we measured necessary angles on trunk, hip, knee and ankle in 10 healthy volunteers and 20 THA subjects one month postoperatively, while the volunteers or THA subjects make such frequent patterns of movement based on the 1. st. step. ALL joint angle was defined as “zero” in static standing position. We also compared the angles in THA subjects with those of the volunteers. Motion analysis technology with optical sensors is;. 1). Track 30 infrared reflection sensors on subjects' body surface with infrared camera in the requested motions (MAC3D system, Motion Analysis, USA). 2). Collect 3-D coordinates of 30 sensors' positions over time during subjects' motions. 3). Calculate joint angle, driving 3-D installed skeletal model combined with motion data collected in 2) on display over time (SIMM, Musculographics). Results. Resulting from clinical chart, most patients (78%) behave in an individual manner regardless of postoperative guidance for prevention of hip dislocation more than 1 year after THA. High incident pattern of the motion was “Leg raising pattern” (26%), and “Trunk flexion pattern” (23%) (Fig. 1). For above two pattern of the socks-wearing motion, 3-D motion analysis showed that maximum hip flexion angle was 78.7±5.2 degrees for leg raising pattern, 80.4±6.8 degrees for trunk flexion pattern, and they were significantly lower than those of the volunteers. Moreover, it showed that maximum ankle dorsal flexion angle was 13.6±10.5 degrees, 9.5±10.5 degrees respectively and they were significantly larger than those of the volunteers. It was not significant between THA patients and volunteers for maximum trunk and knee joint angle during each motion, respectively (Fig. 2, Fig. 3). Hip angle of abduction/adduction or external/internal rotation was within 15 degrees during each motion. Discussion. Most reports refer to early postoperative period, and express ability to do the motion, as indicated posture for prevention of hip dislocation. However, current study showed that most patients (78%) behave in an individual manner more than 1 year after THA. During wearing socks motion, in THA group, compared to control group, hip flexion was lower and ankle dorsal flexion was higher, suggesting compensation for the disability of hip joint with the ankle motion one month after THA

To evaluate the impact of a knee prosthesis on the soft-tissue envelope or knee kinematics, cadaveric lower extremities are often mounted in a custom test rig, e.g. Oxford knee rig. Using such test rig, the knee is tested while performing a squatting motion. However, such motion is of limited daily-life relevance and clinical practices has shown that squatting commonly causes problems for knee patients. As a result, a new test rig was developed that allows a random, controlled movement of the ankle relative to the hip in the sagittal plane. Mounting the specimen in the test rig, restricts five degrees of freedom (DOF) at the hip; only the rotation in the sagittal plane is not restrained (Figure 1). On the other hand, at the ankle, only two degrees of freedom are restrained, namely the movement in the sagittal plane. The ankle has thus three rotational degrees of freedom, all rotation axis intersect in a single point: the center of the ankle. In addition, the out-of-plane translational movement of the ankle remains free. This is achieved by means of a linear bearing. The other translational degrees of freedom, in the sagittal plane, are controlled by two actuators. As a result, the knee has five degrees of freedom left; flexion-extension is controlled. This represents typical closed chain applications, such as cycling. In a first step, the knee kinematics have been evaluated under un-loaded conditions (no quadriceps or hamstring forces applied). To evaluate the knee kinematics, an infrared camera system (OptiTrack, NaturalPoint Inc, USA) is used. Therefore, three infrared markers are placed on the femur and tibia respectively. In addition, markers are placed on the test rig itself, to evaluate the accuracy of the applied motion. All markers are tracked using eight infrared cameras. At the ankle, a 2D circular motion with a radius of 100 mm was applied. Based on the 3D motion analysis, it was demonstrated that the control system has an accuracy of ± 0.5 mm. The evaluation of the knee kinematics in accordance to Grood and Suntay (J. of Biomechanical Engineering, 1983), additionally requires the evaluation of the knee anatomy. To that extent, the cadaveric specimen has been visualized using a CT scan, with the infrared markers in place. From these CT images, a 3D reconstruction has been created (Mimics, Materialise, Belgium). Subsequently, custom software has been developed that combines the CT data with the motion analysis data (Matlab, The MathWorks Inc., USA). As a result, knee motion is visualized in 3D (Figure 2.a) and clinical relevant kinematic parameters can be derived (Figure 2.b). In conclusion, the presented test rig and analysis framework is ready to evaluate more complex knee kinematics with reasonable accuracy and stability of the control loops. Future research will however primarily focus on the evaluation and validation of the impact of forces applied onto the specimen

Background. The cruciate ligaments are important structures for biomechanical stability of the knee. For total knee arthroplasty (TKA), understanding of the exact function of the (PCL) and anterior (ACL) cruciate ligament during walking is important in the light of recent designs of bicruciate TKAs. However, studies evaluating in vivo function of the PCL during daily activities such as walking are scarce. We aimed to assess the role of the PCL during gait by measuring kinematics and kinetics of individuals with PCL deficiency and compare them with individuals with ACL deficiency and healthy young adults. Methods. Individuals with unilateral PCL deficiency (PCLD; n=9), unilateral ACL deficiency (n=10) and healthy young adults performed (n=10) 10 walk trials (5 for each leg) in which they walked over a force platform. Motion analysis (Vicon Motion Capture System) was used to calculate joint angles and internal moments around the knee, hip and ankle in the sagittal plane. Joint angles and moments of the injured knee (in PCLD and ACLD) or left knee (in HYA) were compared between groups at weight acceptance, mid-stance and push-off phases (see Fig. 1). Clinical assessment included passive knee laxity (Kneelax) for anterior (in 20–30° knee flexion) and posterior tibia translation (in 70–90° knee flexion) and Lysholm questionnaires. Results. Lysholm scores were significantly lower in PCLD and ACLD individuals compared to HYA (p's ≤ .001). PCLD subjects had more passive anterior (p = .001) and posterior tibia translation (p = .041) compared to HYA, but no significant differences were found in both directions between ACLD and HYA (p's > .10). During gait, knee angles at weight acceptance, late stance and around toe-off were not significantly different between the PCLD and HYA, and between ACLD and HYA (all p's > .06). However, the knee extension moment during mid-stance was significantly lower in the PCLD group when compared to the HYA group (p = .001; Fig. 2). Interestingly, the knee moment in the PCLD group remained positive (i.e. extension moment) throughout the stance phase, whereas HYA and ACLD groups created a substantial flexion moment around the knee at this instant. We did not observe any significant differences in hip and ankle joint angles and moments between groups. Discussion. We observed a difference in gait pattern in individuals with PCL deficiency compared to HYA, that was confined to an absence of knee flexion moments during the mid-stance phase. We hypothesize that this difference reflects a compensation strategy employed by individuals with PCL deficiency to avoid external knee (hyper)extension moments. Gait adaptations related to PCL deficiency might also have implications for design of total knee prosthesis and calls for careful evaluation of gait patterns after TKA with a specific focus on the role of the PCL. For any figures or tables, please contact the authors directly