WO2010007383A2

WO2010007383A2 - Method of predicting a vibration response from a human or animal joint

Info

Publication number: WO2010007383A2
Application number: PCT/GB2009/001779
Authority: WO
Inventors: Steven C. Abbot
Original assignee: Anglia Ruskin University
Priority date: 2008-07-14
Filing date: 2009-07-14
Publication date: 2010-01-21
Also published as: GB0812842D0

Description

METHOD OF PREDICTING A VIBRATION RESPONSE FROM A HUMAN OR

ANIMAL JOINT

Field of the Invention

The present invention relates to a method of predicting the vibration response from a human or animal joint, for example, during flexion or extension.

Background of the Invention

It is often desirable to obtain information about the internal state of a human or animal joint. Such information may be obtained using, for example, x-ray or magnetic resonance imaging, but these procedures are generally expensive and require non-portable equipment.

Attempts have been made to obtain this information through analysis of the vibration response of a moving joint (see: Barr, D.A., Long, L., Kernohan, W.G. , Mollan, R.A. B.:

Continuous passive motion in computer assisted auscultation of the knee, Computer Methods and Programs in Biomedicine, 1994, 43, 159-169; Kernohan, W.G. , Barr, D.A., McCoy, G. F., Mollan, R.A.B. : Vibration arthrometry in assessment of knee disorders: The problem of angular velocity, Journal of Biomedical Engineering, 1991, 13(January), 35-38; Krishnan, S., Rangayyan, R.M. , Bell, G.D., Frank, CB. : Auditory display of knee-joint vibration signals, Journal of the Acoustical Society of America, 2001, 110(6), 3292-3304; and Tavathia, S., Rangayyan, R.M. , Frank, CB. , Bell, G.D., Ladly, K. O. , Zhang, Y. T. : Analysis of Knee Vibration Signals Using Linear Prediction, IEEE Transactions on Biomedical Engineering, 1992, 39(9), 959-970).

However, these attempts have been hindered by variability in the vibration responses, which have prevented researchers from being able to establish meaningful correlations between the vibration response and other parameters associated with the joint or its movement.

Summary of the Invention

In general terms, the present invention provides a method of predicting the vibration response of a human or animal joint e.g. a human knee joint, based on an analysis of flexion or extension motion of that joint. Having predicted an expected response, comparison with an actual vibration response can then be performed. The comparison can lead to the establishment of meaningful correlations, allowing for example the health of the joint to be determined.

Thus, a first aspect of the present invention provides a method of predicting the vibration response from a human or animal joint during flexion or extension, comprising the steps of:

receiving a trace of angular displacement against time for a bending movement of the joint;

analysing the trace to identify involuntary changes in velocity of said joint during the bending movement; and

predicting the expected vibration response of said joint during the bending movement based on the pattern of involuntary changes in velocity identified in the trace.

This method may include the preliminary step of recording the trace during the bending of the joint.

The present invention is based on the discovery that the motion of a human joint during flexion or extension is not smooth or fluid, but rather comprises a series of hops or jerks from one angular position to the next. This jerky motion is involuntary i.e. it cannot be controlled by the subject .

Thus, a trace of angular displacement against time, obtained for the bending movement of a joint, comprises repeating sequences of very short accelerations, decelerations and periods of constant motion.

It is thought that this microscale activity is a result of muscle motor units firing in a series of bursts, combined with the physical effects of the various surfaces within the joint sliding against one another.

Thus, the pattern of involuntary changes in velocity identified in a trace of angular displacement against time may correlate with the vibration response of the joint, allowing this response to be predicted with increased precision.

The analysis and prediction steps may be performed using a computer .

Typically, the involuntary changes in velocity identified in the trace of angular displacement against time are matched to predetermined categories in order to identify the pattern of the involuntary changes. This pattern is then used to predict the vibration response of the joint.

For example, a classification structure of categories of involuntary changes in velocity may be defined, the categories underlying the types of bending motion performed by a human or animal joint. The involuntary changes in velocity may be thought of as microscale motion. Each sequence of microscale motion may extend over a specified angular range e.g. of about 4°. By determining which of these categories are present in a trace of angular displacement against time, the vibration response of the joint may be predicted. Generally, when matching involuntary changes in velocity to predetermined categories, the predetermined categories of the classification structure are considered in turn according to a hierarchical order, e.g. until a category is found that is a match for that section of the trace. Categories low on the hierarchical list are generally only used to fill any gap at the end of the trace.

For example, the vibration response of the joint may be predicted by reference to a database relating patterns of categorised involuntary changes in velocity to the corresponding vibration response obtained from a healthy joint .

The vibration response of a joint may, however, be dependent on other factors and not just the patterns of involuntary motion identified in the trace of angular displacement against time. Thus, prediction of the vibration response of the joint during a bending movement may further be improved by receiving further data measuring values for any of the following parameters, taken alone or in combination:

the angle of the joint,

the angular displacement relative to the starting position for the bending movement,

the contact force between opposing surfaces in the joint,

characterisation of the bending movement as flexion or extension,

characterisation of the bending movement as acceleration, deceleration, or constant velocity, and

characterisation of the mechanism of friction within the joint; and using these parameters in the prediction of the vibration response.

Typically, these values will be recorded as a preliminary step to their use in the prediction of the vibration response.

Typically, a multidimensional database is constructed to correlate these parameters to the vibration response obtained from a healthy joint.

The bending movement of a joint may be tracked using a motion capture technique. This technique may be based on optical measurements (e.g. using an optical tracking system or taking a video recording of the subject), inertial measurements (e.g. using inertial sensors affixed to the subject's body that communicate directly with a computer) , magnetic measurements (e.g. using magnetic field sensors to determine the position of magnetic field generators affixed to the subject's body), or mechanical/electromechanical measurements (e.g. those recorded by a goniometer or an electro-goniometer) .

Typically, the bending movement is tracked using an optical tracking system or a goniometer or electro-goniometer.

The angular displacement may be recorded at a frequency of at least 25 Hz, preferably at least 50 Hz, most preferably at least 100 Hz.

The angular displacement may be recorded in increments of 2° or less, preferably 1° or less.

The vibration response of a joint during bending may be measured using a microphone and/or an accelerometer .

The method of the present invention may further include the step of receiving a recording of the actual vibration response of the joint for comparison with the predicted response. This comparison may allow the health of the joint to be determined, since the relationship between the trace of angular displacement against time and the corresponding vibration response is different in damaged joints compared to healthy joints.

Typically, the actual vibration response will be recorded as a preliminary step to its comparison with the predicted response.

Indeed, another aspect of the present invention provides a method for determining the health of a joint comprising performing the method of the first aspect (including the comparison with the actual vibration response) and determining the health of the joint on the basis of the comparison between the actual and predicted vibration response.

The methods of the present invention have the advantage that they are relatively quick and cheap ways to obtain information about the internal state of a joint. They do not require large or complex equipment and are suitable for routine use by nurses and general practitioners. The methods may particularly be used to monitor the health of athletes' joints in order to identify damage to joints at an early stage.

Brief Description of the Drawings

Embodiments of the invention will now be described by way of example with reference to the accompanying drawings in which:

Figure 1 shows a schematic view of a goniometer attached to a subject's leg.

Figure 2 shows 13 categories of involuntary changes in velocity of a joint during bending motion. Figure 3 shows a trace of angular velocity against angular displacement and the pattern of involuntary changes in velocity that has been identified in the trace.

Figure 4 shows a comparison of the predicted and measured z- axis accelerometer trace for a knee joint of a 14 year old female subject having no history of knee joint injury and no current pain or discomfort.

Figure 5 shows a comparison of the predicted and measured x- axis accelerometer trace for a knee joint of a 53 year old female having an unstable patella due to ligament laxity.

Figure 6 shows a comparison of the predicted and measured z- axis accelerometer trace for the knee joint of Figure 5.

Figure 7 shows a comparison of the predicted and measured x- axis accelerometer trace for a knee joint of a 23 year old male having a type-3 chondral detect to the underside of the patella .

Figure 8 shows a comparison of the predicted and measured y- axis accelerometer trace for the knee joint of Figure 7.

Detailed Description

Tracking bending movement of joints

The bending movement of a joint may be tracked using a motion capture technique based on e.g. an optical tracking system or a goniometer.

Optical tracking system

Optical tracking systems use optical sensors to locate targets affixed to the subject, typically to the skin of the subject. The system records the x,y,z coordinates of each target as a function of time, thus allowing a trace of the movement of the subject to be recorded.

An optical tracking system may use active markers, e.g. light- emitting diodes, as targets. Alternatively, passive markers, e.g. reflective markers, may be used.

Goniometer

Figure 1 shows a goniometer 10 mounted on a subject for measuring angular displacement of the knee joint. A goniometer comprises two endblocks 12,14 connected by a wire 16. A first endblock 12 is secured to the subject above the knee e.g. to the subject's thigh, while the second endblock 14 is secured to the subject below the knee e.g. to the subject's calf. Typically, the endblocks 12,14 are secured to the subject using double-sided medical adhesive tape. Preferably, the first endblock 12 is secured to the lateral surface of the subject's thigh, while the second endblock 14 is preferably secured to the lateral surface of the subject's calf on the same side of the subject's leg as the first endblock 12.

The wire 16 may be a composite wire having a plurality of strain gauges that are positioned to record the bending angle of the wire 16. Alternatively, the goniometer may be an electro-goniometer, in which case the wire 16 is an electrically-conducting wire and bending of the wire 16 results in the generation of a voltage that is recorded by a potentiometer. In this case, the bending angle of the wire 16 is calculated from the recorded voltage.

Measuring the vibration of joints

Microphone

The microphone is typically a digital stethoscope that is held manually against the joint during flexion or extension of the joint. In the case of measurement from the knee joint, it has been found that a strong signal is obtained if the microphone is held against the inner lateral surface of the knee.

Preferably in this case, the microphone is held against a location slightly posterior to the medial condyle.

Accelerometer

The accelerometer may be a standard commercially-available accelerometer. The accelerometer typically has an active head for sensing the movement of the subject and a cable for transmitting the data obtained by the head. The head typically includes a piezoelectric crystal for generating a voltage in response to the vibration of the joint. The head is typically secured to the subject by means of double sided adhesive tape or a Velcro® strap. In general, the accelerometer records motion of the subject along each of three orthogonal axes.

In the case of measurement from a knee joint, the accelerometer is typically secured to the subject's patella. Vibration data is generally obtained for each of three axes, the first axis being generally orthogonal to the surface of the patella, the second axis extending generally in a lateral direction relative to the knee, and the third axis extending generally along the length of the subject's leg.

Examples

Example 1: Tracking a bending movement of a joint

(a) The bending movement (extension) of the knee of an 18-year old female subject was monitored to record a trace of angular displacement against time. The measurement was carried out using an optical tracking system. The data obtained is listed below:

(b) The bending movement (extension) of the knee of an 18-year old male subject was monitored to record a trace of angular displacement against time. The measurement was carried out using an electro-goniometer and the data obtained is given below:

Example 2: Identifying involuntary changes in velocity of joint

The data obtained in Example 1 was converted to provide graphs of angular velocity against angle of displacement. This allowed the pattern of involuntary changes occurring during bending of the joint to be identified, by matching the involuntary changes to the predetermined categories shown in Figure 2. These predetermined microscale motion categories are listed in Figure 2 and were obtained by analysing 980 angular displacement traces of flexion and extension motion of the knee. The traces were taken from 42 subjects, both male and female, aged between 11 and 60 years.

The predetermined microscale motion categories each comprise a different combination of features of acceleration, deceleration and constant velocity. These features represent, respectively, a period of acceleration, deceleration, or constant velocity between two successive measurements. Each microscale motion category typically represents a total angular displacement of about 4°.

The microscale motion categories are assigned to a trace following the order set out in Figure 2. That is, the microscale motion categories are arranged according to a hierarchical list. When assigning a motion category to a section of the trace, the motion categories of the list are considered in turn according to their hierarchical order, until a category is found that is a match for that section of the trace. Motion categories low on the hierarchical list are only used to fill any gap at the end of the recorded trace.

The process of identifying the involuntary velocity changes present in the trace recorded from a subject is illustrated in Figure 3. During the process of assigning a microscale motion category to the start of the recorded trace, microscale motion category class 1 (shown in Figure 2) is first taken into consideration. Both class 1 and the recorded trace begin with a period of deceleration. However, in class 1, the period of deceleration is followed by a period of constant velocity, whereas in the recorded trace, this period is followed by a period of acceleration. Therefore, class 1 is rejected. Classes 2 and 3 are then considered in turn. Neither of these classes starts with a period of deceleration and so they are both rejected. Class 4 is then taken into consideration. This class consists of a period of deceleration followed by a period of constant velocity, whereas in the recorded trace, the period of deceleration is followed by a period of acceleration. Therefore, class 4 is rejected. Class 5 is also rejected, since it does not start with a period of deceleration .

After this, class 6 is taken into consideration. This class consists of a period of deceleration followed by a period of acceleration and therefore matches the start of the recorded trace. Thus, predetermined microscale motion category class 6 is assigned to the start of the trace, and the process is repeated for the next section of the trace.

Microscale motion category classes 11-13 are generally only assigned to the end section of a trace.

Example 3: estimating the variation in contact force and characterising friction behaviour as stick or slip

The traces of angular displacement against time were also used to estimate the contact force between opposing surfaces within the joint. The estimates obtained for the contact forces were normalised values in which periods of acceleration or deceleration were assigned a normalised contact force of 100, while the mid-point of a period of constant motion was assigned a normalised contact force of 0. Other periods of constant motion were assigned a scaled contact force dependent on their proximity to a period of acceleration or deceleration. Thus, periods of constant motion occurring immediately before or after periods of acceleration or deceleration were assigned values close to 100; other periods of constant motion were assigned lower values of contact force .

The traces of angular displacement against time were also characterised as sequences of stick or slip friction, i.e. periods of acceleration or deceleration were considered to represent stick friction and periods of constant motion were considered to represent slip friction.

The normalised contact force estimated from the trace of angular displacement obtained from a 19-year old female subject is given below, along with characterisation of the motion as stick or slip friction:

Example 4 : Creating a source database A source database was created using angular displacement traces obtained from 2000 recordings of knee flexion or extension from 20 subjects aged 14-20. The subjects were all considered to have healthy knees.

For each data point on the angular displacement trace, the database also stores the following related parameters:

o the angle of the joint

o the angular displacement relative to the starting position for the bending movement

o the estimated normalised contact force between opposing surfaces in the joint

o characterisation of the bending movement as flexion or extension

o characterisation of the bending movement as acceleration, deceleration, or constant velocity

o characterisation of the mechanism of friction within the joint as stick or slip

The database also recorded the vibration response associated with each angular displacement trace and related parameters, the vibration response being recorded both through a microphone held against the inner lateral surface of the knee and through an accelerometer secured to the subject's patella.

Example 5: Investigation of the health of a joint

The health of a subject's knee joint was examined by obtaining a trace of angular displacement against time for a flexion or extension movement and recording the corresponding related parameters listed in Example 4. The source database discussed in Example 4 was then used to predict the vibration response of a healthy knee. The predicted vibration response was compared to the vibration response measured using a microphone and an accelerometer in order to determine the health of the knee .

Figures 4 to 8 show a comparison of the predicted and measured vibration response from the knee joints of different subjects.

In each of Figures 4 to 8, the total absolute amplitude of the vibration response is plotted against the angle of displacement, all other parameters being held constant. The total absolute amplitude of the vibration response corresponds to the sum of the absolute amplitudes of each of the vibration readings recorded in the time taken to cover one degree of arc. The sign of each vibration reading (i.e. positive or negative) is not taken into account when calculating the total absolute amplitude, that is, only the modulus of the vibration reading is taken into account.

Each value of the total absolute amplitude of the vibration response obtained from a subject is associated with a given combination of the parameters listed in Example 4. Thus, for each such value of the total absolute amplitude, it is possible to call up from the source database stored vibration responses corresponding to the same combination of parameters. In particular, it is possible to call up the minimum and maximum stored vibration responses corresponding to this combination of parameters. These are, in effect, the predicted minimum and maximum vibration responses for a healthy joint.

These predicted minimum and maximum vibration responses are shown in Figures 4 to 8 as dashed lines, a first line (labelled "CaI Min") representing the predicted minimum vibration response for a given combination of parameters and a second line (labelled "CaI Max") representing the predicted maximum vibration response.

Figure 4 shows the predicted and measured vibration response (recorded as a z-axis accelerometer trace) of the knee joint of a 14 year old female subject with no history of knee joint injury and no current pain or discomfort. It can be seen that the measured vibration response for this subject (shown as a solid line labelled "Sub 14") fits within the range predicted by the source database. Thus, for a healthy joint, the predicted and recorded vibration responses are in agreement.

Figure 5 shows the predicted and measured vibration response (recorded as a x-axis accelerometer trace) of the knee joint of a 53 year old female subject having an unstable patella due to ligament laxity. It can be seen that the measured vibration response for this subject (shown as a solid line labelled "Sub 63") lies outside the range predicted by the source database.

Figure 6 shows the predicted and measured vibration response (recorded as a z-axis accelerometer trace) of the knee joint of Figure 5. Again, it can be seen that the measured vibration response for this subject (shown as a solid line labelled "Sub 63") lies outside the range predicted by the source database.

Figure 7 shows the predicted and measured vibration response (recorded as a x-axis accelerometer trace) of the knee joint of a 23 year old male subject having a type 3 chondral defect to the underside of the patella. It can be seen that the measured vibration response for this subject (shown as a solid line labelled "Sub 64") lies outside the range predicted by the source database. Figure 8 shows the predicted and measured vibration response (recorded as a y-axis accelerometer trace) of the knee joint of Figure 7. Again, it can be seen that the measured vibration response for this subject (shown as a solid line labelled ^λΛSub 64") lies outside the range predicted by the source database.

Thus, it can be seen that the vibration response of healthy knee joints lies within the range predicted by the source database, while the vibration response of damaged knee joints lies outside this range. Hence, the present invention may allow knee damage to be detected.

While the invention has been described in conjunction with the exemplary embodiments described above, many equivalent modifications and variations will be apparent to those skilled in the art when given this disclosure. Accordingly, the exemplary embodiments of the invention set forth above are considered to be illustrative and not limiting. Various changes to the described embodiments may be made without departing from the spirit and scope of the invention.

All references mentioned herein are incorporated by reference.

Claims

1. A method of predicting the vibration response from a human or animal joint during flexion or extension, comprising the steps of:

receiving a trace of angular displacement as a function of time for a bending movement of said joint;

analysing said trace to identify involuntary changes in velocity of said joint during said bending movement; and

predicting the expected vibration response of said joint during said bending movement based on the pattern of involuntary changes in velocity identified in said trace.

2. The method of claim 1, further comprising the preliminary step, before the analysing step, recording said trace during the bending of said joint.

3. The method of claim 1 or claim 2, further comprising the step, between the analysing and predicting steps, of matching said involuntary changes in velocity to predetermined categories, to identify the pattern of involuntary changes.

4. The method of any of the preceding claims, wherein the expected vibration response of said joint is predicted by reference to a database relating patterns of categorised involuntary changes in velocity to the corresponding vibration response obtained from a healthy joint.

5. The method of any of the preceding claims, further comprising the step of receiving further data measuring values for any one or combination of the following parameters:

the angle of said joint, the angular displacement relative to the starting position for said bending movement,

the contact force between opposing surfaces in said joint,

characterisation of the bending movement as flexion or extension,

characterisation of the mechanism of friction within said joint;

and

using the value or values obtained in the prediction of the expected vibration response of said joint during said bending movement.

6. The method of claim 5, further comprising the preliminary- step, before the step of receiving said further data measuring values for said parameters, of measuring said values.

7. The method of any one of the preceding claims, wherein said trace is recorded using an optical tracking system.

8. The method of any one of claims 1 to 6, wherein said trace is recorded using a goniometer.

9. The method of any of the preceding claims, wherein said angular displacement is recorded at a rate of at least 50 Hz.

10. The method of any of the preceding claims, wherein said angular displacement is measured in increments of 2° or less.

11. The method of any of the preceding claims, wherein said joint is a human knee joint.

12. The method of any one of the preceding claims, further comprising the steps of:

receiving a recording of the actual vibration response of said joint during said bending movement; and

comparing said actual vibration response and said predicted vibration response.

13. The method of claim 12, further comprising the step, before the step of receiving said recording of said actual vibration response, of recording said actual vibration response during the bending of said joint.

14. A method of determining the health of a joint comprising performing the method of claim 13, and determining the health of the joint on the basis of the comparison between the actual and predicted vibration response.