Normative Three-Dimensional Patellofemoral and Tibiofemoral Kinematics: A Dynamic, in Vivo Study

In order to advance biomechanical modeling, knee joint implant design and clinical treatment of knee joint pathology, accurate in vivo kinematic data of the combined patellofemoral and tibiofemoral joint during volitional activity are critical. For example, one cause of the increased prevalence of anterior knee pain in the female population is hypothesized to be altered tibiofemoral kinematics, resulting in pathological patellofemoral kinematics. Thus, the objectives of this paper were to test the hypothesis that knee joint kinematics vary based on gender and to explore the correlation between the 3-D kinematics of the patellofemoral and tibiofemoral joints. In order to accomplish these goals, a large (n = 34) normative database of combined six degree of freedom patellofemoral and tibiofemoral kinematics, acquired noninvasively during volitional knee extension-flexion using fast-PC (dynamic) magnetic resonance imaging, was established. In this normative database, few correlations between tibiofemoral and patellofemoral kinematics were found. Specifically, tibial external rotation did not predict lateral patellar tilt, as has been stated in previous studies. In general, significant differences could not be found based on gender. Further investigation into these relationships in the presence of pathology is warranted.     

Development of a force amplitude- and location-sensing device designed to improve the ligament balancing procedure in TKA

To improve the ligament balancing procedure during total knee arthroplasty a force-sensing device to intraoperatively measure knee joint forces and moments has been developed. It consists of two sensitive plates, one for each condyle, a tibial base plate and a set of spaces to adapt the device thickness to the patient-specific tibiofemoral gap. Each sensitive plate is equipped with three deformable bridges instrumented with thick-film piezoresistive sensors, which allow accurate measurements of the amplitude and location of the tibiofemoral contact forces. The net varus-valgus moment is then computed to characterize the ligamentous imbalance. The developed device has a measurement range of 0-500 N and an intrinsic accuracy of 0.5% full scale. Experimental trials on a plastic knee joint model and on a cadaver specimen demonstrated the proper function of the device in situ. The results obtained indicated that the novel force-sensing device has an appropriate range of measurement and a strong potential to offer useful quantitative information and effective assistance during the ligament balancing procedure in total knee arthroplasty.     

Vibration arthrometry in the patients with failed total knee replacement

This is a preliminary research on the vibration arthrometry of artificial knee joint in vivo. Analyzing the vibration signals measured from the accelerometer on patella, there are two speed protocols in knee kinematics: 1) 2 degrees/s, the signal is called "physiological patellofemoral crepitus (PPC)", and 2) 67 degrees/s, the signal is called "vibration signal in rapid knee motion". The study has collected 14 patients who had revision total knee arthroplasty due to prosthetic wear or malalignment represent the failed total knee replacement (FTKR), and 12 patients who had just undergone the primary total knee arthroplasty in the past two to six months and have currently no knee pain represent the normal total knee replacement (NTKR). FTKR is clinically divided into three categories: metal wear, polyethylene wear of the patellar component, and no wear but with prosthesis malalignment. In PPC, the value of root mean square (rms) is used as a parameter; in vibration signals in rapid knee motion, autoregressive modeling is used for adaptive segmentation and extracting the dominant pole of each signal segment to calculate the spectral power ratios in f < 100 Hz and f > 500 Hz. It was found that in the case of metal wear, the rms value of PPC signal is far greater than a knee joint with polyethylene wear and without wear, i.e., PPC signal appears only in metal wear. As for vibration signals in rapid knee motion, prominent time-domain vibration signals could be found in the FTKR patients with either polyethylene or metal wear of the patellar component. We also found that for normal knee joint, the spectral power ratio of dominant poles has nearly 80% distribution in f < 100 Hz, is between 50% and 70% for knee with polyethylene wear and below 30% for metal wear, whereas in f > 500 Hz, spectral power ratio of dominant poles has over 30% distribution in metal wear but only nonsignificant distribution in polyethylene wear, no wear, and normal knee. The results show that vibration signals in rapid knee motion can be used for effectively detecting polyethylene wear of the patellar component in the early stage, while PPC signals can only be used to detect prosthetic metal wear in the late stage.     

Analysis of knee vibration signals using linear prediction

Clinical methods used at present for the diagnosis of cartilage pathology in the knee are invasive in nature, and carry some risks. There exists a need for the development of a safe, objective, noninvasive method for early detection, localization, and quantification of cartilage pathology in the knee. This paper investigates the possibility of developing such a method based on an analysis of vibrations produced by joint surfaces rubbing against one another during normal movement. In particular, the method of modeling by linear prediction is used for adaptive segmentation and parameterization of knee vibration signals. Dominant poles are extracted from the model system function for each segment based on their energy contributions and bandwidths. These dominant poles represent the dominant features of the signal segments in the spectral domain. Two-dimensional feature vectors are then constructed using the first dominant pole and the ratio of power in the 40-120 Hz band to the total power of the segment. The potential use of this method to distinguish between vibrations produced by normal volunteers and patients known to have cartilage pathology (chondromalacia) is discussed.     

Vibration arthrometry in patients with knee joint disorders

Physiological patellofemoral crepitus (PPC) is the vibration signal produced by the knee joint during slow motion (less than 5 degrees per second), which can be measured by vibration arthrometry (VAM). By using the autoregressive (AR) model for the PPC signals of patients with knee osteoarthritis, the study analyzes the PPC signals to evaluate the condition of patellar-femoral joint cartilage. Accordingly, we can divide osteoarthritis into three types, type 1: the cartilage of patellar-femoral joint is intact, the osteoarthritis found in the femoral-tibial joint surface; type 2: degeneration occurs in the surface cartilage of both the femoral-tibial joint and the femoral trochlea, but not on the patellar surface; type 3: both patellar-femoral and femoral-tibial joints have osteoarthritis. For the analysis, the intraclass distance of AR coefficients and spectral power ratio of dominant poles are adopted. Based on the proposed method, two cases of type 1, six of type 2, and 28 of type 3 were found in 36 cases of knee osteoarthritis. This is in agreement with the operative findings. For comparison, the PPC signals of 10 subjects with normal knees (without pain or wound history) were also measured. The results of analysis of the 10 normal subjects were consistent and clearly differentiable from those of the osteoarthritis patients. Therefore, the proposed method is efficient for the analysis of the condition of patellar-femoral joint cartilage and VAM may become an alternative way of noninvasive diagnosis of knee osteoarthritis.     

Modeling the human knee for assistive technologies

In this paper, we use motion capture technology together with an EMG-driven musculoskeletal model of the knee joint to predict muscle behavior during human dynamic movements. We propose a muscle model based on infinitely stiff tendons and show this allows speeding up 250?times the computation of muscle force and the resulting joint moment calculation with no loss of accuracy with respect to the previously developed elastic-tendon model. We then integrate our previously developed method for the estimation of 3-D musculotendon kinematics in the proposed EMG-driven model. This new code enabled the creation of a standalone EMG-driven model that was implemented and run on an embedded system for applications in assistive technologies such as myoelectrically controlled prostheses and orthoses.     

Adaptive time-frequency analysis of knee joint vibroarthrographic signals for noninvasive screening of articular cartilage pathology

Vibroarthrographic (VAG) signals emitted by human knee joints are nonstationary and multicomponent in nature; time-frequency distributions (TFD's) provide powerful means to analyze such signals. The objective of this paper is to construct adaptive TFD's of VAG signals suitable for feature extraction. An adaptive TFD was constructed by minimum cross-entropy optimization of the TFD obtained by the matching pursuit decomposition algorithm. Parameters of VAG signals such as energy, energy spread, frequency, and frequency spread were extracted from their adaptive TFD's. The parameters carry information about the combined TF dynamics of the signals. The mean and standard deviation of the parameters were computed, and each VAG signal was represented by a set of just six features. Statistical pattern classification experiments based on logistic regression analysis of the parameters showed an overall normal/abnormal screening accuracy of 68.9% with 90 VAG signals (51 normals and 39 abnormals), and a higher accuracy of 77.5% with a database of 71 signals with 51 normals and 20 abnormals of a specific type of patellofemoral disorder. The proposed method of VAG signal analysis is independent of joint angle and clinical information, and shows good potential for noninvasive diagnosis and monitoring of patellofemoral disorders such as chondromalacia patella.     

A practical strategy for sEMG-based knee joint moment estimation during gait and its validation in individuals with cerebral palsy

Individuals with cerebral palsy have neurological deficits that may interfere with motor function and lead to abnormal walking patterns. It is important to know the joint moment generated by the patient's muscles during walking in order to assist the suboptimal gait patterns. In this paper, we describe a practical strategy for estimating the internal moment of a knee joint from surface electromyography (sEMG) and knee joint angle measurements. This strategy requires only isokinetic knee flexion and extension tests to obtain a relationship between the sEMG and the knee internal moment, and it does not necessitate comprehensive laboratory calibration, which typically requires a 3-D motion capture system and ground reaction force plates. Four estimation models were considered based on different assumptions about the functions of the relevant muscles during the isokinetic tests and the stance phase of walking. The performance of the four models was evaluated by comparing the estimated moments with the gold standard internal moment calculated from inverse dynamics. The results indicate that an optimal estimation model can be chosen based on the degree of cocontraction. The estimation error of the chosen model is acceptable (normalized root-mean-squared error: 0.15-0.29, R: 0.71-0.93) compared to previous studies (Doorenbosch and Harlaar, 2003; Doorenbosch and Harlaar, 2004; Doorenbosch, Joosten, and Harlaar, 2005), and this strategy provides a simple and effective solution for estimating knee joint moment from sEMG.     

Ambulatory estimation of knee-joint kinematics in anatomical coordinate system using accelerometers and magnetometers

Knee-joint kinematics analysis using an optimal sensor set and a reliable algorithm would be useful in the gait analysis. An original approach for ambulatory estimation of knee-joint angles in anatomical coordinate system is presented, which is composed of a physical-sensor-difference-based algorithm and virtual-sensor-difference-based algorithm. To test the approach, a wearable monitoring system composed of accelerometers and magnetometers was developed and evaluated on lower limb. The flexion/extension (f/e), abduction/adduction (a/a), and inversion/extension (i/e) rotation angles of the knee joint in the anatomical joint coordinate system were estimated. In this method, since there is no integration of angular acceleration or angular velocity, the result is not distorted by offset and drift. The three knee-joint angles within the anatomical coordinate system are independent of the orders, which must be considered when Euler angles are used. Besides, since there are no physical sensors implanted in the knee joint based on the virtual-sensor-difference-based algorithm, it is feasible to analyze knee-joint kinematics with less numbers and types of sensors than those mentioned in some others methods. Compared with results from the reference system, the developed wearable sensor system is available to do gait analysis with fewer sensors and high degree of accuracy.     

A model-based method for the reconstruction of total knee replacement kinematics

A better knowledge of the kinematics behavior of total knee replacement (TKR) during activity still remains a crucial issue to validate innovative prosthesis designs and different surgical strategies. Tools for more accurate measurement of in vivo kinematics of knee prosthesis components are therefore fundamental to improve the clinical outcome of knee replacement. In the present study, a novel model-based method for the estimation of the three-dimensional (3-D) position and orientation (pose) of both the femoral and tibial knee prosthesis components during activity is presented. The knowledge of the 3-D geometry of the components and a single plane projection view in a fluoroscopic image are sufficient to reconstruct the absolute and relative pose of the components in space. The technique is based on the best alignment of the component designs with the corresponding projection on the image plane. The image generation process is modeled and an iterative procedure localizes the spatial pose of the object by minimizing the Euclidean distance of the projection rays from the object surface. Computer simulation and static/dynamic in vitro tests using real knee prosthesis show that the accuracy with which relative orientation and position of the components can be estimated is better than 1.5 degrees and 1.5 mm, respectively. In vivo tests demonstrate that the method is well suited for kinematics analysis on TKR patients and that good quality images can be obtained with a carefully positioning of the fluoroscope and an appropriate dosage. With respect to previously adopted template matching techniques, the present method overcomes the complete segmentation of the components on the projected image and also features the simultaneous evaluation of all the six degrees of freedom (DOF) of the object. The expected small difference between successive poses in in vivo sequences strongly reduces the frequency of false poses and both the operator and computation time.     

In vivo measurement of 3-D skeletal kinematics from sequences ofbiplane radiographs: Application to knee kinematics

Current noninvasive or minimally invasive methods for evaluating in vivo knee kinematics are inadequate for accurate determination of dynamic joint function due to limited accuracy and/or insufficient sampling rates. A three-dimensional (3-D) model-based method is presented to estimate skeletal motion of the knee from high-speed sequences of biplane radiographs. The method implicitly assumes that geometrical features cannot be detected reliably and an exact segmentation of bone edges is not always feasible. An existing biplane radiograph system was simulated as two separate single-plane radiograph systems. Position and orientation of the underlying bone was determined for each single-plane view by generating projections through a 3-D volumetric model (from computed tomography), and producing an image (digitally reconstructed radiograph) similar (based on texture information and rough edges of bone) to the two-dimensional radiographs. The absolute 3-D pose was determined using known imaging geometry of the biplane radiograph system and a 3-D line intersection method. Results were compared to data of known accuracy, obtained from a previously established bone-implanted marker method. Difference of controlled in vitro tests was on the order of 0.5 mm for translation and 1.4 degrees for rotation. A biplane radiograph sequence of a canine hindlimb during treadmill walking was used for in vivo testing, with differences on the order of 0.8 mm for translation and 2.5 degrees for rotation.     

Modified local discriminant bases algorithm and its application in analysis of human knee joint vibration signals

Knee joint disorders are common in the elderly population, athletes, and outdoor sports enthusiasts. These disorders are often painful and incapacitating. Vibration signals [vibroarthrographic (VAG)] are emitted at the knee joint during the swinging movement of the knee. These VAG signals contain information that can be used to characterize certain pathological aspects of the knee joint. In this paper, we present a noninvasive method for screening knee joint disorders using the VAG signals. The proposed approach uses wavelet packet decompositions and a modified local discriminant bases algorithm to analyze the VAG signals and to identify the highly discriminatory basis functions. We demonstrate the effectiveness of using a combination of multiple dissimilarity measures to arrive at the optimal set of discriminatory basis functions, thereby maximizing the classification accuracy. A database of 89 VAG signals containing 51 normal and 38 abnormal samples were used in this study. The features extracted from the coefficients of the selected basis functions were analyzed and classified using a linear-discriminant-analysis-based classifier. A classification accuracy as high as 80% was achieved using this true nonstationary signal analysis approach.     

Soft tissue artifact compensation in knee kinematics by double anatomical landmark calibration: performance of a novel method during selected motor tasks

The purpose of the present work was to describe and assess the performance on two selected subjects of a new method for the compensation of soft tissue artifact on knee rotations and translations during the execution of step up/down, sit-to-stand/stand-to-sit, and flexion against gravity. Soft tissue artifact has been recognized as the most critical source of error in gait analysis data. Its propagation strongly affects joint angles, in particular those characterized by a small range of motion, such as knee ab/adduction and internal/external rotation. This may be critical in the exploitation of gait analysis data for clinical decisions. The proposed method is based on the flexion/extension angle interpolation of two anatomical landmark calibrations taken at the extremes of motion. Its performance on knee rotation and translations was tested on a kinematics data-set obtained by the synchronous combination of traditional stereophotogrammetry and 3-D fluoroscopy. The newly proposed method was extremely effective on the compensation of soft tissue artifact propagation to knee rotations, in particular mean values of the root mean square error on ab/adduction and internal/external rotation angles decreased from 3.7 degrees and 3.7 degrees to 1.4 degrees and 1.6 degrees, respectively, with respect to single calibration. Mainly, knee translations calculated from stereophotogrammetric data using the proposed compensation method were found to be reliable with respect to the fluoroscopy-based gold standard. The residual mean values of the root mean square error were 2.0, 2.8, and 2.1 mm for anterior/posterior, vertical, and medio/lateral translations, respectively.     

基于激光测距的微型机械臂关节控制模型

为了更加深入探究并提升机械臂关节控制效果,提出一种基于激光测距的微型机械臂关节控制模型,通过激光测距技术对微型机械臂周边环境进行感知,同时进行数据点扫描,将全部数据点集进行直线分割以及拟合等相关操作,获取二维环境地图。在上述基础上,通过坐标变换矩阵获取微型机械臂的正运动学模型,利用正运动学模型得到机械臂逆运动学模型。将获取的动力学模型转换为仿射非线性系统的形式,利用输入输出反馈线性化方法选取合适的状态变换和反馈变换,通过滑膜控制方法构建微型机械臂关节控制模型,采用模型进行关节控制。仿真实验结果表明,所提模型可以获取理想的微型机械臂关节控制结果。     

Volume manipulations for simulating bone and joint surgery.

Bone and joint surgery is widely used in orthopedic, oral, and maxillofacial, and dental and plasty departments to correct bone and joint pathology such as bone and joint tumors and fractures, and skeletal morphological deformities. This article presents a voxel structure to represent topologically and geometrically correct surfaces and algorithms to accurately compute intersections of tool swept surfaces with bones based on this voxel structure. This article then presents various volume manipulation algorithms to operate on virtual bones, bone grafts, and prostheses for bone and joint surgery simulations. A complicated knee arthroplasty illustrates the practicality and versatility of the proposed method.     

Adaptive cancellation of muscle contraction interference invibroarthrographic signals

Vibroarthrography (VAG) is an innovative, objective, noninvasive technique for obtaining diagnostic information concerning the articular cartilage of a joint. Knee VAG signals can be detected using a contact sensor over the skin surface of the knee joint during knee movement such as flexion and/or extension. These measured signals. However, contain significant interference caused by muscle contraction that is required for knee movement. Quality improvement of VAG signals is an important subject, and crucial in computer-aided diagnosis of cartilage pathology. While simple frequency domain high-pass (or band-pass) filtering could be used for minimizing muscle contraction interference (MCI), it could eliminate possible overlapping spectral components of the VAG signals. In this work, an adaptive MCI cancellation technique is presented as an alternative technique for filtering VAG signals. Methods of measuring the VAG and reference signals (MCI) are described, with details on MCI identification. Characterization, and step size optimization for the adaptive filter. The performance of the method is evaluated by simulated signals as well as signals obtained from human subjects under isotonic contraction     

四自由度模块化移动机械臂建模与运动学分析

为了对模块化移动机械臂的模块化组成和控制系统建模,对受非完整约束的差分驱动的移动平台运动学模型进行了分析。并在考虑机械臂运动学约束的基础上,采用Denavit-Hartenberg法描述了四自由度模块化机械臂操作空间,获得以关节角度为变量的正运动学模型。运用矩阵逆乘的解析法,进一步得到了机械臂逆运动学的完整解析解。最后,在实验室平台MT-ARM上做了仿真与实验验证,结果证明了正运动学模型及运动学逆解的正确性。     

半导体激光照射联合透明质酸钠和运动疗法对膝关节骨性关节炎的疗效影响

目的:探讨半导体激光穴位照射联合膝关节腔注射透明质酸钠和运动疗法对膝关节骨性关节炎的的临床疗效。方法:将86例膝关节骨性关节炎患者随机分成观察组及对照组,各43例。对照组采用膝关节腔注射透明质酸钠结合运动疗法,观察组在对照组的基础上采用半导体激光穴位照射,两组患者治疗后均随访6个月。结果:采用lysholm膝关节量表在治疗前后分别对两组患者进行评价,观察组其疗效优于对照组(P﹤0.05)。结论:采取半导体激光结合运动疗法并膝关节腔注射透明质酸钠治疗膝关节骨性关节炎安全有效,能预防膝关节骨性关节炎的反复发作。     

Automatic stance-swing phase detection from accelerometer data forperoneal nerve stimulation

The development of implantable peroneal nerve stimulators has increased interest in sensors which can detect the different phases of walking (stance and swing). Accelerometers, having a potential for implantation, are studied as detectors for the swing phase of walking to replace footswitches. Theoretically, we could show that accelerometers can be used to distinguish between stance and swing phase. Attaching accelerometers between ankle and knee joint the equivalent acceleration of the ankle joint was calculated. This resulted in a typical and reproducible signal in which the different walking phases were identified. Automatic detection algorithms, based on cross correlation calculation were developed and tested. Measurements from four healthy and four hemiplegic subjects resulted in a total of 317 and 272 steps, respectively. One of the hemiplegic subjects was considered to be a failure due to large disturbances in the acceleration signal during the swing phase of walking, which may be related to the use of crutches. Taking part of the data as a learning set and the other part as an evaluation set we found two errors in the push-off detection for both the healthy subjects and the remaining three hemiplegic subjects, out of 152 and 106 steps, respectively. In addition, we showed that when using one accelerometer closely below the knee joint almost identical results can be achieved. This could lead to a combination of sensor and stimulator into one implantable device.     

Model-based estimation of knee stiffness

During natural locomotion, the stiffness of the human knee is modulated continuously and subconsciously according to the demands of activity and terrain. Given modern actuator technology, powered transfemoral prostheses could theoretically provide a similar degree of sophistication and function. However, experimentally quantifying knee stiffness modulation during natural gait is challenging. Alternatively, joint stiffness could be estimated in a less disruptive manner using electromyography (EMG) combined with kinetic and kinematic measurements to estimate muscle force, together with models that relate muscle force to stiffness. Here we present the first step in that process, where we develop such an approach and evaluate it in isometric conditions, where experimental measurements are more feasible. Our EMG-guided modeling approach allows us to consider conditions with antagonistic muscle activation, a phenomenon commonly observed in physiological gait. Our validation shows that model-based estimates of knee joint stiffness coincide well with experimental data obtained using conventional perturbation techniques. We conclude that knee stiffness can be accurately estimated in isometric conditions without applying perturbations, which presents an important step toward our ultimate goal of quantifying knee stiffness during gait.