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Traditional Chinese medication (TCM) has analgesic and anti-inflammatory effects in patients with knee osteoarthritis (OA). We conducted the first systematic review of the best quantitative and qualitative evidence currently available in order to evaluate the effectiveness of TCM in relieving pain in knee OA. A comprehensive literature search was conducted using three English and four Chinese biomedical databases from their inception through March 1, 2015. We included randomized controlled trials of TCM for knee OA with intervention durations of at least two weeks. The effects of TCM on pain and other clinical symptoms were measured with the visual analog scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). The total effectiveness rate, which was used to assess overall pain, physical performance and wellness, was also measured. Two researchers independently extracted data on study design, population characteristics, duration, intervention, outcomes, risk of bias, and primary results. We performed a random-effects meta-analysis when appropriate. We also explored factors that could explain the heterogeneity by conducting subgroup and meta-regression analyses. Twenty-three studies, totaling 2362 subjects, met the eligibility criteria. Treatments were formulated with an average of 8 Chinese herbs and were prescribed based on the traditional Chinese diagnostic method of syndrome differentiation. The mean treatment duration was seven weeks, with oral administration occurring one to three times a day. Compared with non-steroidal anti-inflammatory drugs and intra-articular hyaluronate injections, 18 of the studies showed significantly improved VAS pain scores (Mean Difference [MD] $=$ 0.56; 95% confidence interval [CI], 0.18 to 0.94; $p=0.004$), six of the studies showed significantly improved WOMAC pain subscale scores (MD $=$ 2.23; 95% CI, 0.56 to 3.91; $p=0.009$), and 16 of the trials showed significantly improved total effectiveness rates (risk ratio $=$ 1.12; 95% CI, 1.05 to 1.19; $p=$ 0.0003). In addition, TCM showed a lower risk of adverse events than standard western treatments. This evidence suggests that TCM is safe and effective for improving pain, function, and wellness in treatments of knee OA. However, there is inherent clinical heterogeneity (diverse TCM formulations, controls, and treatment regimens) among the included trials. Despite these limitations, the potential analgesic effects of TCM warrant further methodologically rigorous research to determine the clinical implications of TCM on pain management in knee OA.

Knee osteoarthritis (OA) often leads to altered balance control, joint motion and loading patterns during gait. Acupuncture has been proven to be effective in pain relief but its effects on inter-joint load-sharing for body balance have not been reported. The current study bridged the gap by quantifying the immediate effects of acupuncture on the inter-joint and inter-limb load-sharing in patients with knee OA during level walking in terms of the total support moment (Ms) and the contribution of individual joints to the total support moment. Gait analysis was performed on fifteen healthy controls and on fifteen patients with mild to moderate bilateral medial knee OA. After acupuncture treatment the patients with bilateral knee OA walked with significantly increased speed ($p=0.031$), and were able to resist greater and closer-to-normal knee flexion moments ($p=0.038$). They also changed the inter-joint sharing of the support moments with increased knee ($p=0.031$) contributions, but reduced hip contributions ($p=0.022$) to the sagittal Ms during single-limb support. They showed an asymmetric inter-limb load-sharing similar to the normal controls, with increased sharing of the time integral of both the sagittal and frontal whole body support moment by the leading limb during double-limb support ($p=0.024$). The altered intra- and inter-limb contributions to the demand of supporting the body during gait suggests that acupuncture treatment led to immediate changes in the control strategy toward a normal pattern. However, the effects of these changes on the progression of the disease in the long term would require further investigation.

Knee osteoarthritis (KOA) is a common chronic degenerative disease of the elderly. Electro-acupuncture (EA) is considered as a beneficial treatment for KOA, but the conclusion is controversial. This systematic review compiled the evidence from 11 randomized controlled trials to objectively assess the effectiveness and safety of EA for KOA. Eight databases including PubMed, Cochrane Library, Clinic trials, Foreign Medical Literature Retrial Service (FMRS), Science Direct, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP), and Wanfang Data were extensively searched up to 5 July 2016. The outcomes included the evaluation of effectiveness, pain and physical function. Risk of bias was evaluated according to the Cochrane risk of bias tool. Eleven RCTs with 695 participants were included. Meta-analysis indicated that EA was more effective than pharmacological treatment (RR $=$ 1.14; 95% CI $=$ 1.01,1.28; $P=0.03$) and manual acupuncture (RR $=$ 1.12; 95% CI $=$ 1.02,1.22; $P=0.02$). Also, EA had a more significant effect in reducing the pain intensity (SMD $=-1.11$; 95% CI $=-1.33,-0.88$; $P<0.00001$) and improving the physical function in the perspective of WOMAC (MD $=-9.81$; 95% CI $=-14.05$, 5.56; $P<0.00001$) and LKSS (pharmacological treatment: MD $=5.08$; 95% CI $=3.52$, 6.64; $P<0.00001$). Furthermore, these studies implied that EA should be performed for at least 4 weeks. Conclusively, the results indicate that EA is a great opportunity to remarkably alleviate the pain and improve the physical function of KOA patients with a low risk of adverse reaction. Therefore, more high quality RCTs with rigorous methods of design, measurement and evaluation are needed to confirm the long-term effects of EA for KOA.

Objective: To identify what extent different patterns and severities of involvement affect quality of life of people suffering knee osteoarthritis.

Methods: This population-based survey involved 288 women and 288 men aged 40 years or older from Songkhla province, southern Thailand. Quality of life was measured using the Medical Outcome Study Short Form Health sutvery (SF-36) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Radiographic investigation included antero-posterior and skyline view of both knees. Osteoarthritis was categorized into 3 patterns; isolated patellofemoral, isolated tibiofemoral and combined with diagnosis based on Kellgren & Lawrence grade 2 or higher.

Results: Quality of life as measured by SF-36 and WOMAC showed poorer score in moderate or severe grade than in mild grade of severity. Isolated patellofemoral and combined patterns demonstrated showed poorer scores on both WOMAC and SF-36 than isolated tibiofemoral pattern. Body mass index, income level and pattern of involvement could independently predict total scores of WOMAC, while age, marital status and pattern of involvement affected total score of SF-36.

Conclusion: Pattern of involvement is a better predictor of quality of life than disease severity in patients with knee osteoarthritis.

Purpose: The purpose of this study was to assess the association of the knee flexion excursion to the vertical center-of-mass (COM) amplitude and to the lower-extremity muscle work during stance phase for subjects with knee osteoarthritis. Method: Twenty subjects scheduled for total knee replacement and 20 controls performed level walking during standard gait analysis. Dependent variables included stance-phase knee flexion excursion, vertical COM amplitude, and lower-extremity muscle work. Results: Compared to healthy control, subjects with knee osteoarthritis walked with significantly less stance-phase knee flexion and vertical COM excursion. Knee flexion excursion was found to have a strong positive correlation to vertical COM amplitude. The lower-extremity muscle work during single stance phase was found to have a moderate negative correlation to vertical COM amplitude. Conclusions: Osteoarthritis of the knee alters both the stance-phase knee flexion and vertical COM excursions. As these variables show a strong positive relation, efforts to restore stance-phase knee flexion based on the 3rd determinant of gait require a new justification.

Background: Patellar taping has long been reported to be effective in relieving pain in patients with patello-femoral pain syndrome (PFPS). Yet, there is lack of knowledge that supports its use in knee osteoarthritis (OA) management. Purpose: This study examined the effect of therapeutic patellar taping on concentric and eccentric quadriceps muscle peak torques, VAS pain scores, 6-minute walking distance and stair climbing time in patients with knee OA. Methods: A total of 30 female patients with symptomatic knee OA with mean age 51.8 ± 6.3 years and BMI 32.56 ± 3.26 m²/kg participated in the study. They were tested under three taping conditions that were tested randomly; therapeutic, placebo and no-tape. Results: Repeated measure MANOVA revealed that the quadriceps muscle peak torques and 6-minute walking distance increased significantly (p < 0.05) and the VAS scores and stair climbing time decreased significantly with therapeutic tape use compared with the other two tapes. Moreover, the quadriceps muscle peak torques increased significantly and the VAS scores decreased significantly with placebo tape use compared with no-tape use, with no significant difference (p > 0.05) in between for the 6-minute walking distance and stair climbing time. Conclusion: The findings indicate that therapeutic patellar taping is effective in improving quadriceps strength and functional performance and reducing pain in patients with knee OA.

Knee osteoarthritis is highly prevalent in middle-aged and older people, and biomechanical interventions include modifications of the gait and activities of daily living (ADL). This study investigated the effects of gait and ADL modifications compared with conventional exercise for improving knee function in community-dwelling middle-aged and older people. Fifty middle-aged and older people were randomly allocated to the control ($n=22$) or intervention ($n=28$) groups. The control group performed conventional straight leg raising and knee joint range of motion exercises, and the intervention group modified their gait by decreasing the knee adduction moment and increasing hip muscle activities, and performed range of motion exercises in a bathtub. In both groups, the program was implemented for 12 weeks. The Japan knee OA measure score, walking speed, and hip abduction strength significantly improved in both the control and intervention groups. The health-related quality of life (Short Form 8: SF-8) was significantly improved in the intervention group compared with the control group. Gait and ADL modifications achieved effects similar to those of conventional knee joint exercise, and might be more effective for improving physical function-related quality of life.

Objective: Detection of the knee joint’s early osteoarthritis (OA) is important for its early management and prognosis; however, no reliable single biomarker is available for this purpose. This study aimed to determine the correlation between serum and synovial fluid calprotectin level in detecting early knee OA.

Method: In a case-control study, serum and synovial fluid were collected from 283 patients with primary early OA knee and 50 healthy controls. Serum and synovial levels of calprotectin levels were measured using an enzyme-linked immunosorbent assay.

Results: The mean serum calprotectin level was 3141 ± 2634 ng/mL in patients with OA knee and 607.08 ± 163.79 ng/mL in the healthy control group ($p$ < 0.001). The mean synovial fluid calprotectin level was 626.1 ± 67.32 ng/mL in the study population and 424.98 ± 78.41 ng/mL in the control group ($p$ < 0.05). Calprotectin levels were significantly higher in the early stages of OA knee.

Conclusion: Serum calprotectin level correlates with the synovial fluid level. In the early OA knee, serum calprotectin level increases significantly and decreases afterward. However, the synovial fluid calprotectin level remains static or increases on the progression of the disease. Calprotectin may be used as a biochemical marker for early knee OA.

Cartilage repair can greatly alleviate the symptoms of the patients with knee osteoarthritis (KOA). However, some imaging results suggest that the patients with obvious cartilage repair may receive insignificant or even no improvement in their symptoms. This study aims to explore the possible reasons based on the structural feature of the knee joint and construct the models used to predict the progression of knee joint symptoms. 551 subjects from Osteoarthritis Biomarkers Consortium FNIH Project in the Osteoarthritis Initiative (OAI) were included and divided into training and test sets. A total of 153 structural features from five quantitative structural feature sets were included to access the structural characteristics of the knee joints. The Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index was used to evaluate the symptoms of the knee joints. A three-step feature selection method were used to screen the structural features. Finally, Naive Bayes (NB), logistic regression (LR), $K$-nearest neighbor (KNN), support vector machine (SVM) and random forest (RF) models were constructed based on the selected features, and then compared using the receiver operating characteristic (ROC) curve. The distribution in the demographics and WOMAC symptoms scores of the participants was consistent in the training and test sets. Two demographic features and several structural features were selected using the three-step feature selection method. Among the constructed models, the models used for the progression prediction of pain, stiffness and total scores were better than that of physical function. The performance of RF model was the best while SVM model was the second best, and the performance of the remaining three models in predicting the progression of knee symptoms is indistinguishable. Structural feature-based models for the prediction of knee joint symptoms’ progression were constructed and compared. The constructed model showed good feasibility and accuracy, and may assist clinicians to predict the occurrence or progression of the knee joints symptoms in the evaluation and prognosis of cartilage repair.

Knee osteoarthritis (OA) is a degenerative articular disease. The knee joint space width (JSW) is used for grading the severity of knee OA. However, there is a lack of research on differences in the widths of knee joints between both lower limbs in unilateral OA. The purpose of this research was to examine the radiological difference in the affected knee joint and contralateral knee joint by analyzing unilateral older adults with medial knee OA using both knees’ JSW differences. Twenty-five subjects with unilateral medial knee OA participated. X-ray radiographs were used to assess knee JSW, and the paired $t$-test was performed to assess the knee joint gap width between the affected side and the unaffected side in the respective medial and lateral sides. The independent $t$-test compared the differences between the lateral and medial knee JSWs on the affected side and unaffected side. The paired $t$-test did not show a significant difference in the medial and lateral knee JSW on the affected side compared to the unaffected side ($P=0.56$; 0.11). Meanwhile, the independent $t$-test revealed a significant difference between the affected and unaffected sides ($P<0.02$). This study showed no significant changes in affected knee JSWs compared to unaffected sides, but the difference between the lateral and medial JSWs was significant between the knees affected and unaffected by OA in the older adults with medial knee OA.

A customized knee implant numerical modeling using finite element analysis (FEA) during flexion extension has been investigated in this paper with varying loads with an objective of studying its kinematics. Computed tomography (CT) images of 15 osteoarthritis subjects’ images were used in this work. Various morphological characteristics were extracted from clinical images using a commercial CAE software and biomechanical properties were studied on applying standard loads on customized implant and off-the-shelf (OTS) implants. Patient-specific knee implants have been designed according to the morphological characteristics and bone dimension of patient with compressive loads (1500, 1700 and 3000N) during normal gait and were compared with the normal knee. Results showed that the stresses are distributed equally to the spacer and the tibial plate, unlike the standard femoral component where the stresses get concentrated on the cut edges. In compressive load, active stress and strain ($\sim 5$–20MPa) are lesser ($\sim 5\%$) and in flexion extension also lesser with a scaling factor of 0.785 and 1.0. The designed implant was found to produce similar biomechanical properties when compared to normal knee joint and thus it can be considered as a valuable implant and could replace the standard OTS knee implants.

This study aims to develop effective predictive models to assess knee replacement (KR) risk in knee osteoarthritis (KOA) patients, which is important in the personalized diagnosis, assessment, and treatment of KOA. A total of 269KOA patients were selected from the osteoarthritis initiative (OAI) public database and their clinical and knee cartilage image feature data were included in this study. First, the clinical risk factors were screened using univariate Cox regression and then used in the construction of the Clinical model. Next, their image features were selected using univariate and least absolute shrinkage and selection operator (LASSO) Cox methods step by step, and then used in the construction of the Image model. Finally, the Image+Clinical model was constructed by combining the Image model and clinical risk factors, which was then converted into a nomogram for better visualization and future clinical use. All models were validated and compared using the metric of C-index. In addition, Kaplan–Meier (KM) survival curve with log-rank test and calibration curve were also included in the assessment of the model risk stratification ability and prediction consistency. Age and three Western Ontario and McMaster Universities (WOMAC) scores were found significantly correlated with KR, and thus included in Clinical model construction. Fifty-eight features were selected from 92knee cartilage image features using univariate cox, and four image features were retained using the LASSO Cox method. Image+Clinical model and nomogram were finally constructed by combining clinical risk factors and the Image model. Among all models, the Image+Clinical model showed the best predictive performance, and the Image model was better than the Clinical model in the KR risk predictive consistency. By determining an optimal cutoff value, both Image and Image+Clinical models could effectively stratify the KOA patients into KR high-risk and low-risk groups (log-rank test: $p<0.05$). In addition, the calibration curves also showed that model predictions were in excellent agreement with the actual observations for both 3-year and 6-year KR risk probabilities, both in training and test sets. The constructed model and nomogram showed excellent risk stratification and prediction ability, which can be used as a useful tool to evaluate the progress and prognosis of KOA patients individually, and guide the clinical decision-making of KOA treatment and prognosis.

This study aimed to analyze and predict various types of knee pain in knee osteoarthritis (KOA) patients based on Semi-Quantitative MRI Osteoarthritis Knee Score (SQ-MOAKS) features. The goal was to identify structural abnormalities in the knee joint associated with different types of pain, thereby aiding in the development of personalized treatment plans. Subjects were selected from the Osteoarthritis Initiative (OAI) database, including 297 patients who underwent both SQ-MOAKS assessment on knee MRI images and WOMAC knee pain assessment. Univariate and multivariate logistic regression analyses were used for feature selection, followed by the construction of multi-risk factor models and corresponding nomograms for each pain type. The predictive values of the models were evaluated using ROC curves and related metrics (AUC, accuracy, sensitivity, specificity), and the DeLong test was used to assess the significance of differences between various ROCs and AUCs. Significant associations were found between specific SQ-MOAKS features and different types of knee pain. Bone marrow lesions (BML) and cartilage morphology (CM) features were crucial in predicting the walking pain and rest pain, while osteophytes (OS) were more associated with nocturnal pain and pain during stair climbing. The models demonstrated high predictive accuracy, particularly for walking pain and rest pain. This study demonstrated that SQ-MOAKS features could effectively predict different types of knee pain, revealing the structural basis of knee pain in KOA patients. These results prompted the use of SQ-MOAKS in developing personalized treatment strategies, enhancing clinical decision-making, and improving patient quality of life.

Background: Knee osteoarthritis (KOA) is a common degenerative articular disease that causes disability and poor quality of life (QoL) of the individuals. Electrotherapeutic agents such as therapeutic ultrasound (US), interferential current (IFC), and infrared radiation are used in the treatment. It is not clear which of these agents is the best in improving these variables.

Objective: The study aimed to compare the effects of the combined application of US and IFC therapies and infrared radiation on pain, functional activities, and QoL in people with KOA.

Methods: In a randomized controlled study, 60 participants were randomized into two groups, the combination therapy group (CTG) and the infrared radiation group (IRG). Each group received 15-min treatment three times per week for 12 weeks. The visual analog scale (VAS) was used to assess the pain, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) for functional activities and the Short Form Health Survey questionnaire for QoL.

Results: Participants in the CTG had a significant ($p<0.05$) reduction in pain and significant ($p<0.05$) improvement in functional activities and QoL compared to the IRG.

Conclusion: The results of this study support the use of the combination of IFC and US therapies to reduce pain and improve function and QoL for KOA patients.

In this paper, optical coherence tomography (OCT) and surface-enhanced Raman spectroscopy (SERS) were used to characterize normal knee joint (NKJ) tissue and knee osteoarthritis (KOA) tissue ex vivo. OCT images show that there is a clear hierarchical structure in NKJ tissue, including surface layer, transitional layer, radiation layer and cartilage matrix calcification layer tissue structure, while the hierarchical structure of KOA tissue is not clear and unevenly distributed, and the pathological tissues at different stages also show significant differences. SERS shows that NKJ tissue and mild osteoarthritic knee cartilage (MiKOA) tissue have strong characteristic Raman peaks at 964, 1073 (1086), 1271, 1305, 1442, 1660 and 1763cm${}^{-1}$. Compared with the Raman spectrum of NKJ tissue, the Raman characteristic peaks of MiKOA tissue have some shifts, moving from 1073cm${}^{-1}$ to 1086cm${}^{-1}$ and from 1542cm${}^{-1}$ to 1442cm${}^{-1}$. There is a characteristic Raman peak of 1271cm${}^{-1}$ in MiKOA tissue, but not in NKJ tissue. Compared with NKJ tissue, severely degenerated cartilage (SdKOA) tissues show some new SERS peaks at 1008, 1245, 1285, 1311 and 1321cm${}^{-1}$, which are not seen in SERS spectra of NKJ tissue. Principal component analysis (PCA) was used to analyze the Raman spectra of 1245–1345cm${}^{-1}$ region. The results show that PCA can distinguish NKJ, MiKOA and SdKOA tissues and the accuracy is about 90%. These results indicate that OCT can clearly distinguish NKJ, MiKOA, moderate osteoarthritic knee cartilage (MoKOA) and SdKOA tissue, while SERS can provide further judgment basis. The results also prove that the contents of protein and polysaccharide in knee tissue are changed during the pathological process of knee tissue, which is the cause of pain caused by poor friction in knee joint during movement.

Knowledge of the control of the body's dynamic stability in patients with knee osteoarthritis (OA) is helpful for the management of these patients and for the evaluation of treatment outcomes. The purpose of the current study was to investigate the dynamic stability of patients with knee OA during level walking using variables describing the motion of the body's center of mass (COM) and its relationship to the center of pressure (COP). Kinematic and kinetic data during level walking were obtained from 10 patients with bilateral knee OA and 10 normal controls using a motion analysis system and two forceplates. Compared to the normal controls, patients with knee OA exhibited normal COM positions and velocities at key instances of gait but with significant changes in COM accelerations. In the sagittal plane, adjustments to the anterioposterior acceleration of the COM throughout the complete gait cycle were needed for better control of the COM during the more challenging latter half of single leg stance. Diminished A/P COM–COP separation was also used to maintain body stability with reduced joint loadings. In the frontal plane, this was achieved by increasing the acceleration of the body's COM towards the stance leg. The more jerky motion of the body's COM observed may be a result of reduced ability associated with knee OA in the control of the motion of the COM. Strengthening of the muscles of the lower extremities, as well as training of the control of the COM through a dynamic balance training program, are equally important for the dynamic stability of patients with knee OA.

Accurately identifying the various types of knee osteoarthritis aids in an accurate diagnosis. The unique kind and severity of osteoarthritis enable medical specialists to offer the best management and treatment plans. Knee osteoarthritis greatly affects the living style of people by causing higher anxiety, mental issues, and health issues. Early treatment is possible because of early prediction, which may improve patient outcomes. Individuals may be able to prevent or postpone the development of knee osteoarthritis symptoms. An efficient categorization method for knee osteoarthritis employing the Military Scrutolf optimization-tuned deep Convolutional Neural Network (MSO-DCNN) and the advancement of study into this crippling disorder and the improvement of diagnosis, therapy, resource allocation, and disease monitoring are all made possible by the CNN classifier. The preprocessing of the data, which is carried out in three parts and involves the Circular Fourier Transform, Histogram Equalization, and Multivariate Linear Function, also contributes significantly to the success of this study. The proposed MSO technique, which improves convergence time and fine-tunes the classifier’s weight and Bias parameters, was built utilizing the features of military dogs and scrutolf to assist in getting increased seeking and hunting qualities. The MSO-tuned DCNN classifier’s adjusted weights and bias to give more effective desired classification results without using up more time or storage. By examining the performance measures and comparing the existing techniques to the MDO-based DCNN, the suggested MSO-DCNN improved based on TP accuracy by 1.33%, f1 measure by 2.9%, precision by 0.8%, and recall by 2.905%.

Knee osteoarthritis (KOA) is a common chronic degenerative disease of the elderly. Electro-acupuncture (EA) is considered as a beneficial treatment for KOA, but the conclusion is controversial. This systematic review compiled the evidence from 11 randomized controlled trials to objectively assess the effectiveness and safety of EA for KOA. Eight databases including PubMed, Cochrane Library, Clinic trials, Foreign Medical Literature Retrial Service (FMRS), Science Direct, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP), and Wanfang Data were extensively searched up to 5 July 2016. The outcomes included the evaluation of effectiveness, pain and physical function. Risk of bias was evaluated according to the Cochrane risk of bias tool. Eleven RCTs with 695 participants were included. Meta-analysis indicated that EA was more effective than pharmacological treatment (RR = 1.14; 95% CI = 1.01,1.28; P = 0:03) and manual acupuncture (RR = 1.12; 95% CI = 1.02,1.22; P = 0:02). Also, EA had a more significant effect in reducing the pain intensity (SMD = − 1:11; 95% CI = − 1:33, − 0:88; P < 0:00001) and improving the physical function in the perspective of WOMAC (MD = − 9:81; 95% CI = − 14:05, 5.56; P < 0:00001) and LKSS (pharmacological treatment: MD = 5:08; 95% CI = 3:52, 6.64; P < 0:00001). Furthermore, these studies implied that EA should be performed for at least 4 weeks. Conclusively, the results indicate that EA is a great opportunity to remarkably alleviate the pain and improve the physical function of KOA patients with a low risk of adverse reaction. Therefore, more high quality RCTs with rigorous methods of design, measurement and evaluation are needed to confirm the long-term effects of EA for KOA.

Modern gait analysis results in large quantities of correlated data. A current challenge in the field is the development of appropriate data analysis techniques for the representation and interpretation of these data. Knee osteoarthritis is a common debilitating disease of the musculoskeletal system that has been the focus of many gait studies in recent years. Various data analysis techniques have been used to extract pathological information from gait data in these studies. The following review discusses the successes and limitations of many of these analysis techniques in the attempt to understand the biomechanics of knee osteoarthritis.