EP2164393A2

EP2164393A2 - Method for detecting information relevant for the characterization of joint movements

Info

Publication number: EP2164393A2
Application number: EP08774805A
Authority: EP
Inventors: Markus Heller; William Taylor; Georg Duda; Rainald Ehrig
Original assignee: Heller Markus
Current assignee: Heller Markus
Priority date: 2007-07-06
Filing date: 2008-07-04
Publication date: 2010-03-24
Also published as: US20110054851A1; WO2009007332A3; WO2009007332A2

Abstract

The present invention relates to a method for detecting information relevant for the characterization of joint movements, wherein markers mounted on both sides of a body joint are used for the analysis of joint movements and wherein the method comprises the following: Determination of a mean marker configuration and determination of time-dependent discrepancies from the mean configuration, wherein an orthogonal distance regression is carried out for the determination of a mean marker configuration and wherein markers mounted on each side of the body joint are used; carrying out of a weighted orthogonal distance regression with the use of the time-dependent discrepancies from the mean configuration for weighting, wherein markers mounted on each side of the body joint are used; and solution of a linear equalization problem with the use of information which has been determined by the carrying out of the weighted orthogonal distance regression.

Description

Method for determining information relevant for the characterization of joint movements

FIELD OF THE INVENTION

The invention is concerned with the determination of information relevant for the characterization of joint movements. In particular, the invention is concerned with the analysis of joint motions based on the time and / or motion dependent measurement of markers mounted on or in the involved body segments. The present invention permits a quantification of dermal marker shifts and a determination of the elasticity of the skin when the markers used are skin markers. Further, the invention is concerned with determining joint parameters (eg, body joint centers and axes) and determining the accuracy of the particular joint parameters. In addition, the invention allows information to be obtained which relates generally to movements of inter-related bone fragments or parts, such as fractured bone fragments of a fracture. The concept of a joint thus has a broad meaning. BACKGROUND OF THE INVENTION

Motion analysis, functional movement deficits, diagnosis of musculoskeletal disorders and injuries (eg, osteoarthritis, cruciate ligament injury), planning, performing and monitoring surgical procedures, monitoring therapy success, disease prevention and rehabilitation In the musculoskeletal system, as well as in the development of orthoses or endoprostheses, it often requires a precise analysis, characterization and determination of movements of joints (eg a knee or a hip). The movement of a skeleton can be measured by a variety of methods such as percutaneous tracking markers in combination with videofluroscopy and bone pins. However, these procedures are very limited because of their invasive nature.

Measurements of markers attached to the skin can provide information on predetermined body segments and are also used in the determination of in vivo joint kinematics. When reflective markers are used, a non-invasive determination of the motion of predetermined body segments is typically made by directly measuring positions of these reflective markers with infrared optical measuring systems during a certain period of time. From the data obtained by means of a noninvasive method, various information relevant to motion analyzes, such as e.g. Joint axes or joint pivot points are derived. However, the previous methods have the disadvantage that they are too inaccurate. While measuring marker positions, there is relative movement between the markers and the bone to be examined. The errors that occur in such noninvasive measurements usually originate in such movements of the markers, which are due to skin elasticity and slight tissue deformities or irregularities. To improve the accuracy of these procedures, manual and time-consuming corrections often need to be made.

It is the goal of invasive or noninvasive procedures to determine, for a given body joint, eg, a knee joint or hip joint, one or more joint parameters (ie, time-dependent), such as joint axes or one or more pivot points, which may be dependent on the position of the segments. However, previous methods that enable this have the common problem that one segment must be transformed into the coordinate system of another segment to allow the use of a common coordinate system. With this transformation, however, all measurement errors arising in relation to a segment are also included in the Coordinate system of the other segment transformed; this is another reason for the inaccuracy and thus the unreliability of the previous methods.

Such previous methods and aspects of such methods are described, for example, in Taylor, WR et al., "On the influence of soft tissue coverage in the determination of bone kinematics using skin markers", J. of Orthopedic Research, (2005), in Ehrig, RM, et al. Ehrig, RM, et al., "A survey of formal methods for determining the center of rotation of ball joints," J. of Biomechanics (2006), J. of Biomechanics (2007).

All in all, all procedures relating to the determination of information relevant for the characterization of joint movements (eg skin marker displacements, skin elasticity, joint parameters such as body joint centers or axes) are so far too flawed, inaccurate and therefore unreliable. To compensate for this disadvantage usually time-consuming and complicated manual analyzes must be carried out.

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SUMMARY OF THE INVENTION

The aim of the present invention, in addition to the most accurate determination or determination of relevant for the characterization of joint movements information (eg skin marker displacements, skin elasticity, joint parameters such as Körperge steering centers or axes) and the determination of a statement about the reliability of the determined or determined Information.

According to the invention, this object is achieved by a method of the type mentioned above, in the course of which markers are applied to both sides of a body joint on the skin and which has the following method steps:

Determining a mean marker configuration and determining time-dependent deviations from the mean configuration, wherein an orthogonal distance regression (ODR) is performed to determine a mean marker configuration, and wherein markers attached to each side of the body hinge are used;

Perform a weighted ODR using the time-dependent

Deviations from the mean weighting configuration, using markers attached to one side of the body joint; and

Solving a linear balance problem using information determined by performing the weighted ODR.

Furthermore, the target is achieved by means of a device for evaluating the joint function of a subject and / or by means of a device for evaluating musculoskeletal loads of a subject, wherein the devices are each configured with suitable means for carrying out the method outlined above, the devices each having different means for Performing various process steps of the method outlined above may have and wherein these means may be designed in various combinations.

The above object is achieved by means of a motion analysis system, in particular a gait analysis system, wherein the motion analysis system is coupled to the above-mentioned device for evaluating the joint function of a subject The target is also achieved by means of a navigation system for computer-assisted surgery, wherein the navigation system is configured with suitable means for carrying out the method outlined above, wherein the navigation system can have different means for carrying out different method steps of the method outlined above, and wherein these means different combinations can be implemented.

Furthermore, the above-mentioned goal is achieved by means of a medical imaging method, in particular by means of a magnetic resonance-based method, wherein the medical imaging method is coupled to at least one of the above-mentioned devices - device for evaluating the joint function of a subject, device for evaluating musculoskeletal loads of a subject ,

The above steps, as indicated in part in the background of the invention, after attaching skin tags to areas of skin on both sides of a body joint and after picking up the marker trajectories during joint movement of the body joint by means of an optical, infrared or another suitable system. Fig. 1a shows by way of example skin tags attached to the skin of a subject's leg. 1 b shows, by way of example, the joint centers and axes for the hip, knee and ankle derived after the recording of skin markers and the corresponding skin marker trajectories.

One of the first steps in analyzing articular motions from marker data is to perform an ODR that determines an average marker configuration of markers attached to one side of the body joint. In the first step, time-dependent corrections of individual markers, i. time-dependent deviations from the mean configuration, calculated. The ODR performed in this step may be a conventional ODR, e.g. such as the ODR shown in Taylor, W.R. et al., "On the influence of soft tissue coverage in the determination of bone kinematics using skin markers", J. of Orthopedic Research, (2005).

Furthermore, the already determined time-dependent corrections of individual markers or the time-dependent deviations from the mean configuration are used to perform a weighted ODR. In doing so, the skin markers that move most strongly relative to the other skin markers are determined, and the skin markers are weighted according to their relative movement in such a way that relatively more heavily weighted skin markers are weighted less. This determines an optimal marker configuration to which all of the markers associated with the configuration contribute according to their stability within the experimental configuration. This way will enables robust, automatic preprocessing of the marker data and takes into account the different time-dependent stability of individual markers. Furthermore, a quantification of the skin marker shifts of individual markers and thus a description of the elasticity of the soft tissues is made possible in this way.

In a further step, a linear compensation problem is solved using information determined by performing the weighted ODR. This information is the ODR-corrected marker data or the optimal marker configuration. The determination of the linear balance problem is done using transformation matrices. These transformation matrices can be calculated for each measurement time and each side of the body joint.

Since the sides of the joint are taken into account when performing both the conventional ODR and the weighted ODR and / or solving the linear balance problem, the motion of two articulating joint bodies will be described.

By means of the solution of the compensation problem, parameters for a description of joint movement (joint parameters) through a joint center, joint axes and / or the primary joint axis are determined. This method is completely symmetrical with respect to the joint segments involved and furthermore offers the advantage that no error-prone transformations into local (coordinate) systems of the segments are required.

The solving of the linear balance problem itself can be performed using a singular value analysis. By using all singular values and the associated singular vectors, the method provides an analysis of the primary and secondary components of the joint motion. Here, joint movements in rotations are divided by three (rotational) main axes and the singular values associated with the main axes. The singular values associated with the major axes provide weighting for all components of a joint movement that can be automatically classified and evaluated in this way. In this way, the hinge type (e.g., ball joint, hinge joint) can be clearly deduced from experimental data. Furthermore, the concept of breaking any joint motion into rotations about three major rotation axes allows quantification of joint motion not only with respect to the major axis, which is the rule in existing methods, but with respect to all three principal axes.

From the residual of the linear compensation problem, the accuracy of the specific joint parameters can be determined directly and thus automatically quantified. On In this way, a direct representation of the quality of the measurement is allowed, without the need for further manual analysis. This ensures comparability of the measurement results in longitudinal studies on the same subject or allows routine optimization of the placement of markers in different subjects. Further, taking into account corrections made by the ODR results in automatic separation of marker movements into collective motions and movements of individual markers.

The idea of directly determining and automatically quantifying the accuracy of the specific joint parameters from the residuals of the linear compensation problem represents an independent idea of the invention which can also be implemented independently of the remaining method steps, in particular independently of performing a weighted ODR ,

An independently inventive method for determining information relevant for the characterization of joint movements comprises, for example, the following method steps:

Specifying or determining at least two matrices that describe marker points before and after a joint movement,

Determining a transformation matrix for the two matrices by solving a linear balance problem,

- Evaluating the residuals of the solution of the linear compensation problem and determining a quality index for the procedure performed from the residuals.

Furthermore, from a movement of the joint, the primary axis and at least one secondary axis of this movement can be determined. In this case, the stability of the primary axis of the movement of the joint can be determined by means of information about the at least one secondary axis of the movement.

Further, if repeated motions are performed and the secondary axes and the stability of the primary axes are repeatedly determined, it is possible to determine, from the information thus obtained, a cycle which provides a characterization of the function of the corresponding joint (joint function). In addition, a space of individual dynamic joint stability and / or range of motion of the joint can be determined by information on secondary axes of several movements.

In addition, the above object is achieved by means of a method of determining joint stiffness, by which method steps according to the method outlined above are carried out, wherein the steps can be performed in any meaningful combination apparent to a person skilled in the art, and wherein the joint rigidity is determined using Information on forces of joint movement is determined. The information on external forces during joint movements can be determined using a robot or using a robot assistance system. In this case, joint movements are carried out by a robot integrated in the robot assistance system and detected by the robot assistance system together with the forces and moments required to carry out the movement. The information obtained in this way contains information on forces for the execution of joint movements by means of which joint rigidity (rigidity of the corresponding joint) as a whole or for specific directions can be determined.

The above-mentioned object is further also achieved by means of a system for determining information relevant to the characterization of joint movements, the system comprising at least one means configured to perform the method for determining the joint stiffness and the robot assistance system for detection, analysis and / or for determining information relevant to joint movements.

Furthermore, the above object is achieved by a method for determining information relevant for the characterization and / or evaluation of orthotics, wherein the method performs steps according to the method outlined above for determining information relevant for the characterization of joint movements and wherein the Linking and analyzing information relevant for the characterization of joint movements with information on orthoses. By means of this method statements can be made about various features such as the effectiveness of the corresponding orthoses. The knowledge about the corresponding joints or joint movements, which is determined inter alia by the abovementioned methods according to the invention, is brought in a suitable manner in connection with the knowledge about the corresponding orthoses or linked and analyzed accordingly, and thus one achieved comprehensive characterization and / or evaluation of orthoses. The present invention thus enables a robust analysis of joint movements with simultaneous automatic quantification of accuracy. Furthermore, an analysis of the errors caused by marker movements and a classification of the joint movement with respect to orthogonal rotational principal axes is achieved. Further, the present invention provides various options for determining or determining information relevant to the characterization of joint motions, thereby providing various aspects of joint functionality.

As already mentioned, the invention allows to obtain information which is generally related to movements of inter-related bone fragments or parts such as bone fragments or parts thereof. Obtain bone fragments of a fracture or fracture. The concept of a joint thus has a broad meaning. The terms joint movement, movement, movement of a joint thus also include movements of such bone fragments which, as in the case of bone fractures or fractures, are movably related to one another and have a kind of abstract joint movement when moving. By the term "joint" is meant not only a concrete joint, e.g. It can also be a kind of abstract joint around which a movement of bones or bone fragments or parts takes place.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following, the invention will be described in detail by way of example with reference to the accompanying figures, in which:

Figure 1a shows skin-attached markers;

Fig. 1b shows a typical marker configuration with derived joint centers and axes for hip, knee and ankle;

Fig. 2 is a block diagram illustrating the determination of the movement of a hinge of marker trajectories;

Fig. 3 is a block diagram illustrating the determination and evaluation of joint parameters;

Fig. 4 illustrates the definition of local coordinates for two positions of a segment; Fig. 5 the center and the major axis of the knee movement and two secondary

Axes (tibia and femur);

6a shows a comparison of the position of the mean flexion axis for a first defined flexion angle range in 7 subjects with a rupture of the anterior cruciate ligament in comparison to the position of the axis in healthy subjects in a lateral view; and

6b shows a second comparison of the position of the mean flexion axis for a further defined flexion angle range in 7 subjects with rupture of the anterior cruciate ligament (pink) compared to the position of the axis in healthy subjects in a view from the front; and

6c shows a third comparison of the position of the mean flexion axis for a first defined flexion angle range in 7 subjects with anterior cruciate ligament rupture (pink) compared to the position of the axis in healthy subjects in a front view.

DESCRIPTION OF THE EMBODIMENTS

The block diagram shown in Fig. 2 shows an embodiment for determining the movement of a hinge of marker trajectories.

In step SO, markers are attached to the skin or attached. Fig. 1a shows an example of such markers attached to the skin of a subject's leg. Subsequently, marker trajectories are measured during a movement of the subject. The result of SO are time-dependent, spatial positions of all markers. Any standard method of biomechanics may be used to perform SO. When reflective skin markers are used, the marker trajectory data may be acquired using an optical, infrared, or other suitable system during joint movement of a body joint.

The result data (information on marker trajectories or time-dependent positions of all markers) and a possible set of additional information relevant for further calculation and analysis represent input data D1 for the further step S1. A user interface for recording or reading in may be used here Data D1 can be used. Optionally, a graphical 3D visualization of the data D1 can be offered. The various ways of treating data will be apparent to one of ordinary skill in the art. In step S1, a conventional ODR is performed, whereby the ODR for each body segment determines the marker configuration that best describes the measured configurations for all times. This is done by minimizing the function

Here, Ri, ti are the rotations and translations to be determined for the mark substitute Ai, n the number of observations. In mathematics, this is a so-called "Generalized Procrustes Analysis", which is solved with an orthogonal distance regression to obtain an optimal mean configuration

Ap = Σ (R _j + A _j t _j) / n and minimally modified time-dependent configurations t _j with identical geometries. The ODR thus corrects the deviations of individual markers from the optimal mean configuration. Such a method is described, for example, in the above publication Taylor et al. 2005 describe.

In a further step S2, a calculation of time-dependent deviations of the configuration is performed based on raw data for the optimal mean configuration. For this calculation, the less the position of a marker within the configuration varies, the lower the corrections made to the experimentally measured marker positions by the ODR. These are therefore a direct measure of the stability of the markers. This allows them to be used to determine the most stable marker configurations, ie to optimize the placement of markers. Optimal marker positions can be considered, for example, on the one hand, small corrections by the ODR result and these corrections are also for all markers as equal as possible. In addition, a routine detection of erroneous measurements (eg marker exchanges) is possible because they can be detected and excluded by much larger corrections. Furthermore, they allow the creation of a database DB1, which collects the connection between these deviations of age, gender, BMI, diseases, measuring methods and measuring location and allows an analysis of such relationships. For this purpose, the relevant for the database DB1 result data D2 of S2 are included in the database DB1 and possibly stored. From the steps S1 and S2 information relevant for the characterization of joint movements, such as muscle activity and / or local elasticity of the soft tissues, can be determined.

In step S3, a second ODR - a weighted ODR using the detected deviations - is performed. From the correction factors determined by the S2, it is possible to determine weighting factors which are used for carrying out the second, weighted ODR. The weight factors are e.g. from the inverses of the correction terms of the ODR. The weighting can be carried out on the one hand independently of time by using an averaged correction term for each marker. A time-dependent application is achieved by using the current correction of the ODR for weighting at each point in time. In both cases, all markers, according to their experimental stability, contribute to the determination of the optimal mean configuration. Moreover, when using a time-dependent weighting, the weighting of a marker can be greatly affected by the relative position of the segments to each other, e.g. a deflection angle, be dependent. In S3, an optimal configuration of the markers is determined to which all markers contribute according to their stability within the experimental configuration.

In step S4, an evaluation of the optimum configuration is performed. The results are evaluated in accordance with S2. In particular, significant differences between the results from steps S1 and S3 are analyzed - robust marker placements are evident, for example. due to small differences between the simple and the weighted ODR.

The steps S1-S3 and / or S4 enable a robust automatic preprocessing of the marker data. Time-consuming manual corrections, which are caused by different time-dependent stability, can thus be avoided. Furthermore, a quantification of the skin marker shifts of individual markers and thus a determination of the elasticity of the soft tissues is possible.

The block diagram of FIG. 3 shows an exemplary embodiment with steps for determining and evaluating joint parameters, in particular positions of a joint center and joint axes, wherein these positions may also be time-dependent. Furthermore, secondary motion components can also be determined.

The data obtained from the evaluation of the optimal configuration and / or the result data of steps S1-S3 can serve as input data D3 for the determination of joint parameters and their evaluation. Since steps S1-S4 are based on the It should be noted here that the determination and evaluation of joint parameters exemplified by FIG. 3 does not necessarily require information on markers applied to the skin. Here, for example, also on bone fixed markers (eg pins in the bone) into consideration. The determination of joint parameters and their evaluation finds its place both in invasive and in non-invasive procedures. Invasive procedures such as pins in bone are used, for example, for intraoperative use in the context of computer-assisted navigation in orthopedic / traumatological procedures (replacement / reconstruction of the cruciate ligaments, corrective osteotomies, endoprosthetic joint replacement). It allows the use of different markers - optically reflective markers that are attached to the skin, electromagnetic markers that can then be attached to the skin or in / on the bone. Also conceivable is the method for calculating a joint center or an axis together with tantalum markers which are used for so-called RSA examinations (in doing so, small tantalum markers in the bones (intra-operative) or on / in prostheses (components) and then reconstruct the 3D position of the markers with an X-ray method). Furthermore, it is also conceivable that, for example, surfaces or contours of bones / joints are determined from a possibly dynamic nuclear spin recording. The result is then "point clouds" (collections of points) with which the joint centers and / or axes can be determined.

In view of these facts, it must be stated that the execution of the method steps in accordance with. of the embodiment of Fig. 3 is not necessarily the implementation of steps of Fig. 2, in particular of S1 - S3, requires. A person skilled in the art will be aware of this from the following statements. In addition to D3, it is thus also generally possible to use data for markers or "point clouds" and / or their configurations as input data D4.

However, the embodiment will be exemplified based on the steps of FIG. 2.

The marker positions determined by means of the two-time ODR are now used to calculate the joint parameters. These are the (possibly also time-dependent) positions of the joint center and joint axes, as well as the detection of secondary components of movement. For this purpose, local coordinate systems are defined in the associated body segments with the help of three markers and the rotations Ri and translations ti. (Body segment 1), or Si and di (body segment 2) of global coordinates in these local systems, see FIG. 4. The conditions for a joint center or a joint axis result in the following n equations, which together define an over-determined linear system of equations, ie a linear compensation problem:

R, C ₁ - S, C ₂ = ei, - 1,

Here, d and c2 are the coordinates of the joint center in the respective local systems, n is the number of measurements. This approach is characterized by being completely symmetric with respect to both segments and requiring no prior transformation. The corrections made by the ODR make the marker configurations identical for all time points, so the results are completely independent of the choice of the three markers for constructing local coordinates.

With an extended approach, the determination of the axes of rotation is also possible in the case that these axes have no point of intersection. This not only allows an accurate determination of the direction of the axes, but also of their position. This results in important new, unambiguous criteria for the differentiation of different patterns of joint movements in the context of diagnostics, for example by comparing a typical movement pattern of a healthy knee and a cruciate ligament-injured knee. The unambiguous determination of the position of the axes also makes it possible to monitor and ensure the success of a surgical intervention (for example, reconstruction of the cruciate ligaments, correctional osteotomy close to the knee, endoprosthetic joint replacement) in a pre-post-operative comparison.

In order to determine the positions of axes of rotation that do not have a common point of intersection, the method according to the invention of solving a specific linear compensation problem is used. It supplies the direction vectors U ₁₁ V ₁₁ W ₁ (segment 1) or u ₂ , v ₂ , W ₂ (segment 2) of the three axes of rotation. For both segments, the rotation matrices R ₁ and S are decomposed into elementary rotations for n measurements.

I DΛ _/ - - I PΛ? _/ ^u1 I PΛ? _/ ^v1 I PΛ? _/ ^w1 , O ς _/ - - O ς _/ u2 O ς. _/ v2 O ς. _/ w2

Here, approximately R _{1 is} the rotational component of R ₁ about the axis U ₁ . Using these rotations thus obtained can be solved by solving a further linear compensation problem, that of the n equations

((R, - RΓ RΓ) C _W1 + (RΓ RΓ- RΓ) C "+ RΓC _U1 )

- ((S, - S, ^u2 S, " ² ) c _w2 + (S, ^u2 S," ² - S, ^u2 ) c _v2 + S, ^u2 c _u2 ) = (d, - t,) is given, also points c _u1i c _v1i c _w1 (segment 1) or c _u2, c _v2, c _w2 (segment 2) determine on the axes of rotation. Together with the already known direction vectors, therefore, the axes are uniquely determined. The solution of this compensation problem can be advantageously carried out with a singular value decomposition (SVD).

The solution of the compensation problem is calculated in step S5 by means of a singular value decomposition (SVD) of the matrix of the linear compensation problem. This provides a local description of the joint center (d, c2) for each body segment. If the joint moves like an ideal hinge joint, there is no clear solution to the compensation problem. This means that the one-dimensional solution space, which is associated with the singular value with the value zero, then represents the joint axis in local coordinates. In the practical case, the ratio of the smallest singular value relative to the others describes exactly the behavior of the joint, i. it results in a simple classification of the joint between ball and hinge joint. The description of the center or axis obtained in the segment coordinates can finally be transformed into time-dependent global coordinates.

Since the compensation problem is usually not exactly solvable, results in a residual r, which reflects the accuracy of the measurement. In step S6, an analysis of the residual r of the compensation problem is performed.

A mathematical analysis of the residuum shows that it is directly related to the extent of marker movements. Assuming, for example, only collective marker movements in both segments, one obtains

\ r \ ² = (6/1 - 12) σ ² For pure single-marker movements the following results

\ r \ ² = 0.5 (n - 2) σ ² (| _C1 | ² + Ic ₂ I ² I) σ is the mean deviation of the markers from the optimal position. For the error d in the position of a joint center, the estimation results under the same conditions:

| δ | ² = 12 σ ² / σ ₆ ² 'where σ6 is the smallest singular value of the SVD.

For single-marker movements, the following applies in turn: | δ | ² = σ ² (| _C1 | ² + Ic ₂ I ² I) / (2 σ ₆ ² )

These relationships can be used effectively to determine the actual accuracy of the determined joint parameters. In combination with the experimentally determined deviations from the mean configuration, collective movements of the markers and motions of individual markers can thus be described quantitatively. This makes it possible to specifically optimize the placement of the markers in test subjects.

In step S7, a decomposition of any joint movement in rotations is performed around three main axes of rotation. The SVD analysis of the compensation problem thus allows a more thorough analysis of the actual joint movements. The singular vectors associated with the individual singular values can be understood as axes of primary and secondary motion components and provide a decomposition of the motion into three major rotational axes. FIG. 5 shows a joint center and three joint axes using the example of a knee. The joint center is marked Z1, the major axis of the knee movement is A1, and two secondary axes are A2 and A3, with the A2 pointing to the tibia and the A3 to the femur. The smaller the associated singular value, the greater the proportion of the associated rotation (see FIG. 5). This allows for routine detection of motion components such as internal rotation and abduction / adduction for the knee joint without the need for additional measurements. While these components of motion are small in a stable joint, loss of joint stability may occur as a result of injury to the internal structures of the joint (eg, a tear in the anterior cruciate ligament) or degenerative joint disease (gonarthrosis) Internal / external rotation or ab / adduction and can be quantified with the new approach. Similarly, the influence of interventions on the stabilizing elements (ligaments / bone) in the context of a corrective osteotomy or artificial joint replacement (resection / construction of the bone, manipulation of the soft tissues (ligaments) on the function of the joint accurately and reliably determined In order to make this information usable intraoperatively for the surgeon, the connection of the method with a navigation system is advantageous, eg, the joint axes can be displayed in relation to the individual bony anatomy and, for example, the position of ligament attachment points during different phases of the operation For example, to allow the surgeon to more accurately assess the success of the joint's surgical function by comparing it to the position of the axis in the healthy or otherwise optimal axis. The relationship between the proportion of a rotation and the associated singular value can be further mathematically specified. For the three smallest singular values, which are assigned to the rotation axes, the following relationship can be derived

σ / = n (1-r ₂ r ^ n ² ), σ ₅ ² = n (1-nr ^ n ² ), σ / = n (1-nr ₂ / n ² )

Here, the quantities r-, r ₂ , r _{3 are} directly interpretable quantities by the relation with the statistic known measure for the angular dispersion (1-r / n) of the rotations about the axes i = 1,2,3. Thus, from the singular values, values can be derived for the angular ranges Φ, which comprise the rotations about the three rotation axes. If a continuous distribution of the measurements in this range is assumed, this assumption will usually be fulfilled well, this correlation results a

r / n = sin (Φ,) / Φ _l

This relationship makes it possible to immediately quantify the angular range within which they take place, even in a very good approximation, for the secondary components of motion. Thus, not only information on the position and orientation of the main axes of the movement is available for assessing the joint function, but also a further, quantitative measure to characterize the respective joint condition and to reliably detect deviations from the norm quickly and even small deviations.

The results of S6, which characterize the residuals, can be stored or stored in a database or another data container D2. D2 will then contain data on residuals depending on various factors such as age, gender, BMI, disease, severity of disease, site, type of joint, etc.

In step S8, an evaluation of the joint configuration, the data relevant to the joint movements, may be performed. In this case, the results of step S6 and / or step S7 can be compared with the results of step S4, whereby data from D2 can also be used to determine the evaluation.

The data determined by the method, information from D1 and / or from D2 and / or further information can be output at will as data D6 in various combinations and detail levels and, if necessary, visualized graphically (3D). To visualize the results, the axes can be visualized by means of a color scale (eg blue ... red), which links the singular values of the axes with a corresponding color. Furthermore, the diameters of the axes can also be varied and visualized in accordance with the associated singular values. The above-mentioned visualization variants can also be combined and thus also make it possible to obtain and visualize the conditions for the overall movement or specific areas of the movement. In this way, the user is able to quickly record the results.

Furthermore, both the steps that perform ODR and the formulation of the balance problem can be implemented so that new data can be added with very little computational overhead. In this way, real-time measurements can be made possible in which joint parameters as well as data for accuracy are already available during the movement.

In addition, it should be noted that by executing the ODR-related steps S1 and S3, the (skin) marker-related data are determined with sufficient accuracy that good primary joint axes can also be determined for small movements (ROM, range of motion). The secondary axes together with the associated singular values are then a sensitive criterion for distinguishing between normal or conspicuous movement behavior.

Furthermore, the present invention can be applied to the function of a joint e.g. of the knee joint at various hierarchical levels (global: joint, specific: structures) to quantify, if necessary by means of special feedback mechanisms for interaction with the user of the method.

It is known that the flexion / extension axis is the main axis of movement of the knee joint. Therefore, in the method for characterizing the function of the joint, the knee is first flexed, and the main and minor axes of the movement are calculated from the flexion or flexion extension movement by the method according to the invention. Calculated are both over the entire range of motion as well as on special sub-areas of the range of motion, eg flexionswinkelabhängig, averaged axes. Knowledge about the present pathology can also be used to decide which areas are used to determine the axes (eg angle of rotation dependent significance of the anterior cruciate ligament for the stability of the joint with regard to rotation / translation). The secondary axes determined in accordance with the invention (size of the associated singular values, position of the secondary axes, eg in the medio-lateral, anterior-posterior, superior-inferior direction in comparison to the position of the Primary axis) provide direct, quantitative information on the stability of the primary axis and thus of the joint. As an additional information for the evaluation and presentation of the results, the position of the axes to the individual anatomy (eg transepicondylar axis, axis of the posterior condyles, position of the band insertions eg the sidebands) can also be used compared to the situation in the healthy. To quantify the difference in the position of the axes, a joint center can be identified, and thus an excellent point on the axis can be determined. As a result, differences in the position of the various axes can be determined. One possible way of such a calculation of the differences in the position of the various axes is given, for example, in Ehrig et al., "A survey of formal methods for determining functional joint axes" Journal of Biomechanics 2007; 40: 2150-57 The primary axis to the anatomy is shown in Figures 6a and 6b Figures 6a, 6b and 6c respectively show a comparison of the location of the medial flexion axis 61-67 for a defined flexion angle range in seven subjects with anterior cruciate ligament rupture compared to the location of the axis In contrast, the normal deviation of the position of the axis in the healthy is indicated by the oval 69 and by the length of the semiaxes correlated with standard calibration in Fig. 6. The anterior cruciate ligament contributes little to joint stability in Fig. 6b that the axes for the patients deviate only slightly from the axis of a healthy person In Fig. 6c, in turn, the anterior cruciate ligament carries clearly for joint stability, so that the axes for the patient differ significantly from the axis of a healthy.

The information on the secondary axes can also be used to directly provide feedback to the user as to whether the measurement met the accuracy requirements or whether the recording of the movement / function may need to be repeated to reliably characterize the function of the joint , For this purpose, the user can be given feedback on how the movement is best carried out, in which e.g. the singular values associated with the secondary axes are displayed and the user can optimize them. By evaluating the magnitude of the singular values of the secondary axes of several cycles of motion, it is also possible to automatically determine the cycle which is best suited for characterizing the joint function.

To further analyze the joint function further movements may be performed so that secondary degrees of freedom of movement of the knee joint are at the maximum or minimum of the possible range of motion. Thus, for example, the joint is rotated for one cycle as far as possible inside or outside, or if possible abducted or adducted, and / or, if possible, anteriorly or posteriorly, or medially or laterally postponed. The secondary axes of the movement determined according to the invention (position of the axes and size of the associated singular values) are calculated and specified, thus allowing the direct control and determination of how far secondary degrees of freedom have actually been eliminated. Through the totality of the axes from the analysis of the various movements, the space of individual dynamic joint stability is described overall. Thus, the present invention allows for a comprehensive characterization of the individual joint function over the entire range of motion that can be used in the practice of everyday activities or even during sports activities.

The stabilizing effect of the structures of the knee joint (e.g., ligaments, bones, cartilage, muscles) is dependent on knee joint position. Therefore, a detailed analysis of the configuration of joint axes for specific joint positions provides detailed information on the function of different structures. For this purpose, the joint in different, as constant as possible flexion angles, exposed to such external loads by the user, which primarily in movements of the joint with respect to the secondary axes of the knee joint result (ab / adduction, internal / external rotation). For example, the user induces a maximum internal or external rotation of the joint or abduction / adduction of the joint for a given flexion angle. To control how far this movement has actually been induced by the user, the calculation according to the invention of all axes (position of the axes, and / or size of the singular values assigned to the axes) is carried out for these specific movements. By means of the method according to the invention for determining the axes, the range of motion (each maximum minus minimum) can then be calculated with reference to these degrees of freedom. The circumferences as well as the largest and the smallest spikes, respectively, become data of e.g. healthy subjects (possibly age and / or sex-matched and mapped) are proportioned and evaluated.

In addition, the position of the axes with respect to the previously determined main axis of motion and / or the joint center, possibly also the anatomy (such as bone, Bandinsertionen, anatomical axes of the knee joint) is determined. In comparison with the relative positional relationship of the axes or the size of the singular values belonging to the axes for healthy subjects, the deviation of a pathological joint condition can be quantified exactly. This is done, for example, by calculating the difference in the medio-lateral, anterior-posterior, or superio-inferior position of the axis during internal / external rotation or ab / adduction of the subject in comparison to the healthy. Thus, with the inventive method additionally the exact quantitative Characterization of the function and interaction of selected structures of the joint performed.

Another field of application of the present invention is, for example, the calculation and representation of functional hinge axes by integration of the method according to the invention in medical imaging devices, such as e.g. Magnet resonance tomographs. Combined with medical imaging, these devices can be used to display and evaluate dynamic musculoskeletal function, in terms of musculoskeletal functional imaging.

Further, the present invention allows combination of anatomy with function for the detailed calculation of musculoskeletal loads. This connection may also be relevant to the motion capture / film industry for more realistic rendering and motion animation.

Although the invention is explained above with reference to the embodiments in accordance with the accompanying drawings, it is to be understood that the invention is not limited thereto, but may be modified within the scope of the inventive idea disclosed above and in the appended claims. It will be understood that there may be other embodiments which are illustrative and equivalent in nature to the invention, and thus that various modifications may be implemented without departing from the scope of the invention. In particular, this concerns the choice of markers, which also permits independent execution of steps S5-S8, the design of the data containers D1 and D2 and the evaluation steps S4 and S8, which can be carried out in a modified manner according to the interests of the user. Furthermore, various embodiments of the above-mentioned devices, systems and imaging methods are made possible, these will be apparent to those skilled in the art from the above description of the present invention and from the content of the claims. The present invention offers a variety of uses (e.g., the above-described evaluation of orthoses) which will also be apparent to one skilled in the art. In particular, the broad definition of the terms joint or joint movement allows for a variety of applications.

Claims

claims

A method for determining information relevant to the characterization of joint movements, wherein markers attached to the skin on both sides of a body joint are used to analyze joint movement, and wherein the method comprises:

Determining a mean marker configuration and determining time-dependent deviations from the mean configuration, wherein an orthogonal distance regression is performed to determine a mean marker configuration and wherein markers attached to each side of the body hinge are used;

Performing a weighted orthogonal distance regression using the time-dependent deviations from the mean weighting configuration, each using markers attached to one side of the body joint; and

Solving a linear balance problem using information determined by performing the weighted orthogonal distance regression.

2. The method of claim 1, wherein performing the weighted orthogonal distance regression determines an optimal marker configuration.

A method according to any one of the preceding claims, wherein the linear compensation problem is determined using transformation matrices.

4. The method of claim 3, wherein the transformation matrices are calculated for each measurement time and each side of the body joint.

5. The method of claim 1, wherein solving the balance problem determines parameters for a description of a joint movement through a joint center and / or joint axes.

6. The method of claim 5, wherein stability of a primary axis by means of information about the at least one secondary axis of the joint movement is determined.

7. The method of claim 6, wherein after at least one repeated execution of the determination of at least one secondary axis and the determination of the stability of the primary axis, a cycle is determined which provides a characterization of a joint function.

8. The method of claim 6 or 7, wherein a space of the individual dynamic joint stability and / or range of motion of the joint is determined by secondary axes of multiple joint movements.

A method according to any one of the preceding claims, wherein the solving of the linear balance problem is performed by a singular value analysis.

10. The method of claim 9, wherein the method comprises performing singular value decomposition and description of joint motion through rotational principal axes using singular values and singular vectors.

11. The method of claim 9 or 10, wherein articulation movements are decomposed in rotations about three major axes and wherein the singular values are associated with the major axes.

12. The method according to any one of claims 9 or 10, wherein the singular values determine weights for all components of a joint movement.

13. The method according to any one of the preceding claims, wherein the accuracy of the specific joint parameters is determined directly from the residuals of the linear compensation problem.

14. An apparatus for evaluating a joint function of a subject with means which are designed to carry out the method according to any one of the preceding claims.

15. motion analysis system, in particular gait analysis system, characterized in that it is coupled to a device according to claim 14.

16. An apparatus for evaluating musculoskeletal loads of a subject with means which are designed to carry out the method according to one of claims 1 - 13.

17. Navigation system for computer-assisted surgery, wherein the navigation system is configured to carry out a method according to claims 1-13.

18. A medical imaging method, in particular magnetic resonance-based method, the medical imaging method coupled with a device according to claim 14.

19. A medical imaging method, in particular magnetic resonance-based method, the medical imaging method coupled with a device according to claim 16.

20. A method of determining joint stiffness, the method comprising performing steps according to the method of any one of claims 1-13, and wherein the joint stiffness is determined using information about forces during joint motions, wherein the information on forces of joint movement is determined using a joint Robot be determined.

21. A system for determining information relevant for the characterization of joint movements, the system having at least one means configured to carry out the method according to claim 20 and coupled to a robot assistance system for analyzing and / or determining information relevant for joint movements is.

22. A method for determining information relevant for the characterization and / or evaluation of orthotics, wherein the method performs steps according to the method according to one of claims 1-13 and wherein the information relevant for the characterization of joint movements links information with orthoses and analyzed.