Knee joint inflammation detection device and knee joint inflammation detection program

Abstract

To provide a knee joint inflammation detection device and the like that can accurately specify the three-dimensional position of inflammation of the knee joint from a plurality of sensors attached to the front and back of the knee.SOLUTION: A knee joint inflammation detection device comprises: AE sensors 12 that each detect an elastic wave generated from a knee joint part during the movement of the knee joint part as an ultrasonic detection signal; and an inflammation position calculation unit 33 that, based on the detection signals, specifies the presence or absence of inflammation occurring in the knee joint of a subject 11 and the position of the inflammation. During examination, the subject 11 is attached with a plurality of front sensors that are attached to surround a joint part of the femur and the tibia when seen from the front of the knee of the subject 11, and a plurality of rear sensors that are attached to the back of the knee on the outside and / or the back of the knee on the inside of the subject 11.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a knee joint inflammation detection device for detecting inflammation in the knee joint, and particularly to a knee joint inflammation detection device that accurately detects the three-dimensional position of inflammation, etc.

Background Art

[0002] When diagnosing inflammation occurring in the knee joint, generally X-rays, magnetic resonance imaging (MRI), computed tomography (CT), etc. are used. Since MRI uses a high-energy magnetic field, caution is required when substances such as metal are contained in the body, and in some cases, it cannot be used by some people and diagnosis may not be possible. Since CT uses X-rays, special caution is required during pregnancy, etc., and there is also a problem that imaging can only be performed in a static mode.

[0003] In response to such problems, the inventors have disclosed the technology shown in Patent Document 1. The technology shown in Patent Document 1 is such that a joint inflammation detection device includes a plurality of AE sensors that are arranged in plurality at a joint part of an examination subject and detect elastic waves generated from bones at the joint part during the operation of the joint part as ultrasonic detection signals, an amplifier that amplifies the detection signals, and an abnormality diagnosis unit that determines the presence or absence of inflammation occurring in the bones of the examination subject based on the amplified detection signals.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The technology described in Patent Document 1 can detect inflammation occurring in the knee joint area by detecting elastic waves emanating from the bone, thereby determining to some extent the presence, location, and size of inflammation. However, because it detects inflammation using only four AE sensors viewed from the front of the subject's knee, it has the problem of being difficult to accurately determine the three-dimensional location of the inflammation.

[0006] In other words, although theoretically it is possible to determine a three-dimensional position from four sensors, the inventors found through repeated experiments that it is extremely difficult to pinpoint a three-dimensional position using only four sensors. The reason for this is that depending on the state of inflammation, some inflammations can detect elastic waves with all four sensors, while others cannot. Elastic waves that can only be detected by three or fewer sensors cannot be located.

[0007] Furthermore, there is a challenge in that while some severe inflammations generate elastic waves that cannot be detected by all four sensors, there are also minute inflammations and noises that cannot be detected by all four sensors, and it is desirable to be able to distinguish and diagnose these different types of conditions.

[0008] The present invention provides a knee joint inflammation detection device and a knee joint inflammation detection program that can accurately identify the three-dimensional location of knee joint inflammation from multiple sensors attached to the anterior and posterior sides of the knee. [Means for solving the problem]

[0009] The knee joint inflammation detection device according to the present invention comprises a sensor that detects elastic waves generated from the knee joint during movement of the knee joint as an ultrasonic detection signal, and inflammation location identification means that identifies the presence or absence of inflammation in the knee joint of the person being examined and the location of the inflammation based on the detection signal. During the examination, the person being examined is fitted with a plurality of anterior sensors arranged to surround the joint between the femur and tibia when viewed from the front of the knee, and a plurality of posterior sensors arranged on the lateral posterior and / or medial posterior of the knee.

[0010] As described above, the knee joint inflammation detection device according to this embodiment includes a sensor that detects elastic waves generated from the knee joint during movement of the knee joint as an ultrasonic detection signal, and inflammation location identification means that identifies the presence or absence of inflammation in the knee joint of the person being examined and the location of the inflammation based on the detection signal. During the examination, multiple anterior sensors are placed around the joint between the femur and tibia when viewed from the front of the knee of the person being examined, and multiple posterior sensors are placed on the posterior outer side and / or posterior inner side of the knee of the person being examined. This provides the effect of accurately identifying the three-dimensional location of inflammation in the knee joint based on the signals detected by the sensors.

[0011] In particular, it is possible to accurately identify inflammation, including its location, at the contact point between the femur and tibia in the posterior aspect of the knee joint (in the depth direction when viewed from the front of the knee).

[0012] The knee joint inflammation detection device according to the present invention has four anterior sensors arranged in a rectangular shape around the joint between the femur and tibia, and two posterior sensors arranged vertically on the posterior outer side of the knee or the posterior inner side of the knee.

[0013] Thus, in the knee joint inflammation detection device according to this embodiment, four anterior sensors are arranged in a rectangular shape surrounding the joint between the femur and tibia, and two posterior sensors are arranged vertically on the outer posterior side of the knee or the inner posterior side of the knee. This provides the effect of accurately and reliably identifying the three-dimensional location of inflammation in the knee joint.

[0014] The knee joint inflammation detection device according to the present invention is equipped with output control means that outputs the presence or absence and location of inflammation for each angle of the knee joint during knee flexion and extension movements.

[0015] Thus, the knee joint inflammation detection device according to this embodiment is equipped with an output control means that outputs the presence and location of inflammation for each angle of the knee joint during knee flexion and extension movements. This allows for the diagnosis of the effects of inflammation during knee movement, and also enables specialists such as doctors to infer the state of inflammation according to the angle to some extent.

[0016] The knee joint inflammation detection device according to the present invention outputs the location of inflammation corresponding to a detection signal when a detection signal is obtained from a predetermined number or more of the multiple sensors attached, and outputs the detection signal from less than the predetermined number of sensors as the number of detections.

[0017] Thus, in the knee joint inflammation detection device according to this embodiment, if a detection signal is obtained from a predetermined number or more of the multiple sensors attached, the location of inflammation corresponding to the detection signal is output, and the detection signals from fewer than the predetermined number of sensors are output as the number of detections. Therefore, it is possible to output a distinction between major inflammation and other minor inflammations depending on the number of responding sensors, which has the effect of assisting physicians in diagnosing inflammation.

[0018] The knee joint inflammation detection device according to the present invention outputs the location of inflammation on the inside of the knee and inflammation on the outside of the knee in different ways.

[0019] Thus, in the knee joint inflammation detection device according to this embodiment, when outputting the location of inflammation, inflammation on the inside of the knee and inflammation on the outside of the knee are output in different ways. This has the effect of allowing for instantaneous determination with simple processing, for example, when it is necessary to know the approximate location of inflammation during an examination.

[0020] The knee joint inflammation detection device according to the present invention includes a means for identifying whether the inflammation corresponding to the detection signal detected by the sensor is cartilage, meniscus, or bone inflammation, according to the frequency of the detection signal.

[0021] Thus, in the knee joint inflammation detection device according to the present embodiment, according to the frequency of the detection signal detected by the sensor, in order to identify whether the inflammation corresponding to the detection signal is inflammation of cartilage, meniscus, or bone, there is an effect that it becomes easier to determine a diagnosis policy or the like according to the state of inflammation.

Brief Description of Drawings

[0022] [Figure 1] It is a functional block diagram showing the configuration of a knee joint inflammation detection device according to the first embodiment. [Figure 2] It is a diagram showing the positional relationship when six AE sensors are attached to the knee joint of a subject. [Figure 3] It is a schematic diagram showing the three-dimensional arrangement of AE sensors and the inflammation position. [Figure 4] It is a functional block diagram showing the configuration of the arithmetic unit of the knee joint inflammation detection device according to the first embodiment. [Figure 5] It is a diagram showing the result of mapping the source position of the AE signal on the coordinates. [Figure 6] It is a diagram showing the number of detected AE signals with respect to the knee angle. [Figure 7] It is a diagram showing the signal detection time of the AE signal with the source position specified with respect to the knee angle. [Figure 8] It is a diagram showing the number of detected AE signals of each sensor and the source position of the AE signal with respect to the knee flexion and extension angle according to the measurement time. [Figure 9] It is a first diagram showing the clinical examination results of the knee joint. [Figure 10] It is a second diagram showing the clinical examination results of the knee joint. [Figure 11] It is a flowchart showing the operation of the arithmetic unit in the knee joint inflammation detection device according to the first embodiment.

Modes for Carrying Out the Invention

[0023] Embodiments of the present invention will be described below. Throughout these embodiments, the same elements are denoted by the same reference numerals.

[0024] (First embodiment of the present invention) The knee joint inflammation detection device according to this embodiment will be described with reference to Figures 1 to 11. The knee joint inflammation device according to this embodiment uses five or more (preferably six or more) AE sensors (acoustic emission sensors) to identify the three-dimensional location of inflammation in the knee joint and outputs information that serves as an indicator for determining the extent and type of inflammation. In the following embodiment, the case in which six AE sensors are used will be described.

[0025] Figure 1 is a functional block diagram showing the configuration of the knee joint inflammation detection device according to this embodiment. The knee joint inflammation detection device 1 according to this embodiment includes a plurality of AE sensors 12 (12a to 12f) attached to the knee joint of a subject 11, a goniometer 13 positioned on either side of the knee joint at a position corresponding to the femur and a position corresponding to the tibia to detect the angle of the knee joint, a preamplifier 14 connected to each AE sensor 12, a gonioamp 15 connected to the angle sensor 13, and a calculation device 16 that calculates the location of inflammation in the knee joint based on information from each sensor.

[0026] The AE sensor 12 is generally used to measure the location and size of cracks and deformations that occur in structures using elastic waves, and to diagnose the degree of deterioration of the structure. In this embodiment, since bones also deteriorate over time in the same way as structures, the AE sensor 12 is applied to detect inflammation in the knee joint.

[0027] Figure 2 shows the positional relationship when six AE sensors 12a to 12f are attached to the knee joint of a subject 11. Figure 2(A) shows the anatomical position of the knee joint, and Figure 2(B) shows the attachment coordinates. S1 to S6 in the figures correspond to AE sensors 12a to 12f. When attaching the six AE sensors 12a to 12f, as shown in Figure 2(A), four AE sensors 12a, 12b, 12c, and 12d are attached so as to surround the joint 23 between the femur 21 and tibia 22 in a rectangular shape (a rectangle with two opposite sides in the horizontal and vertical directions) when viewed from the front of the subject 11's knee, and two AE sensors 12e and 12f are attached in a straight line vertically on the medial posterior side of the subject 11's knee, flanking the joint 23 between the femur 21 and tibia 22. The distance between each AE sensor 12 is measured to form the coordinates shown in Figure 2(B). The process of identifying the three-dimensional location of inflammation based on the generated coordinates will be described in detail later.

[0028] Furthermore, four AE sensors 12a, 12b, 12c, and 12d, which are mounted in a rectangular shape when viewed from the front of the knee of subject 11, are designated as anterior sensors, and two AE sensors 12e and 12f, which are mounted on the medial posterior side of the knee, are designated as posterior sensors, and these posterior sensors may be mounted on the lateral posterior side of the knee.

[0029] The six AE sensors 12 are connected to a preamplifier 14, which provides each sensor with a predetermined gain. In this embodiment, for example, a gain of 40 dB is obtained. The goniometer 13 is connected to a goniometer 15, and the detected signal is amplified. The signals detected by the AE sensors 12 and the goniometer 15, and amplified by their respective amplifiers, are input to the arithmetic unit 16, where the inflammation location and other parameters are calculated.

[0030] Here, we will explain how to determine the source location of inflammation using six AE sensors 12. Figure 3 is a schematic diagram showing the three-dimensional arrangement of the AE sensors and the location of inflammation. The coordinates of the six AE sensors 12 are denoted as S1(x1,y1,z1), S2(x2,y2,z2), S3(x3,y3,z3), S4(x4,y4,z4), S5(x5,y5,z5), and S6(x6,y6,z6), and P(xs ,y s ,z s ) is assumed to be an arbitrary AE source position.

[0031] From Figure 3, the governing equations for determining the 3D AE source position from the six sensors can be expressed as follows.

[0032]

number

[0033] Here, t0 is the arrival time of the AE wave from the source position to the nearest sensor to which the AE signal first reaches. The signal arrival time difference (TDOA) between sensor 12a and sensors 12b, 12c, 12d, 12e, and 12f is given by t 12 ,t 13 ,t 14 ,t 15 ,t 16 This is shown as follows. The propagation speed of the AE wave is given by v. According to spatial geometry, equations (1) to (6) represent spheres, each considering its respective sensor position as its geometric center. Therefore, the solutions to these equations can be determined as the source position points of the AE signal (the simultaneous generation points of all spheres). The coordinates of this intersection point are expressed as the three-dimensional coordinates of the source position.

[0034] Figure 4 is a functional block diagram showing the configuration of the calculation unit of the knee joint inflammation detection device according to this embodiment. The calculation unit 16 includes an input unit 31 that receives amplified signals from the AE sensor 12 and the goniometer 13, a signal information storage unit 32 that stores the input signal information, an inflammation location calculation unit 33 that identifies the three-dimensional location of inflammation based on the acquired signal information, and an output control unit 34 that outputs information related to the inflammation detected based on the information stored in the signal information storage unit 32 and the identified three-dimensional location information of inflammation.

[0035] Signals from each sensor input to the arithmetic unit 16 are stored in the signal information storage unit 32, and based on this information, calculations for 3D position determination and editing of the output are performed. The processing of the inflammation position calculation unit 33 can be determined by solving equations (1) to (6) as described above. A specific example of the processing performed by the inflammation position calculation unit 33 and the output control unit 34 is shown below.

[0036] After attaching six AE sensors 12 to the subject 11, the arrangement of each AE sensor 12 was as follows:

[0037] [Table 1]

[0038] With the AE sensor 12 and goniometer 13 attached, the subject 11 was asked to perform knee flexion and extension (for example, 5 sets of 3 flexion and extension movements, i.e., a total of 15 flexion and extension movements). As a result, the inflammation location calculation unit 33 processed the obtained AE signals and obtained the following source position coordinates of the AE signals.

[0039] [Table 2]

[0040] Figure 5 shows the result of mapping the source locations of the AE signals in Table 2 onto a coordinate system. As shown in Figure 5, the inflammation location calculation unit 33 can calculate the three-dimensional source location of the AE signal. The output control unit 34 outputs detection results as shown in Figures 6 to 8 from the calculated source location information of the AE signal and the signal information acquired from each AE sensor 12.

[0041] Figure 6 is a graph showing the number of AE signals detected (Hits) against the knee angle. The number of detections shown in this graph is the total number of signals detected by each AE sensor 12. In areas (angles) where detections exceed the threshold, it can be inferred that some kind of abnormality is occurring at the contact points between the cartilage and bone in the knee joint region. In Figure 6, many signals are detected between 50 and 80 degrees, so it can be concluded that inflammation is widespread in the areas of contact within this angle range.

[0042] Figure 7 is a graph showing the signal detection time of an AE signal whose source position has been identified relative to the knee angle. The vertical axis represents the start time of the flexion and extension movement (0s) to the end time (140s), and the circles and triangles in the graph indicate the source position of the AE signal. In order to identify the source position of the AE signal using the method described above, it is necessary for each of the six (or at least five) AE sensors 12 to detect a signal. Therefore, the circles and triangles in the graph indicate that the source position has been identified because six (or five) AE sensors 12 detected a signal. In other words, the results in Figure 6 include the detection signal when the source position of the AE signal is not identified, while the results in Figure 7 only include the detection signal when the source position of the AE signal is identified, output according to the detection time (elapsed time from the start of measurement). In addition, the cases where the source position is on the inside or outside of the knee are distinguished and output using circles and triangles based on the identified 3D coordinates.

[0043] In Figure 7, the source of the AE signal is detected from the beginning to the end of the flexion and extension movement from 0 to 10 degrees, suggesting inflammation at the cartilage and bone contact points in the 0 to 10-degree range, and that this inflammation is located in the lateral region of the knee. Furthermore, the source of the AE signal is detected around 30 degrees and between 70 and 90 degrees, suggesting a high probability of inflammation at the cartilage and bone contact points at these angles, and that this inflammation is located in the medial region of the knee. The inflammation estimated here is detectable by all AE sensors 12, indicating a high possibility of significant damage and requiring attention. Doctors can then decide whether or not to perform a CT scan based on these detection results.

[0044] Figure 8 combines the results from Figures 6 and 7, showing the number of AE signals detected by each sensor (Hits, shown as a bar graph) and the source location of the AE signals as a function of the knee flexion and extension angle over time. The source location is shown separately for the inner (○) and outer (△) sides of the knee.

[0045] In Figure 8, it is possible to make a comprehensive judgment based on the results of Figures 6 and 7. In the 0-10 degree range, the number of detected signals is low, and there are many inflammations with identifiable sources, so it can be determined that the inflammation with significant damage is on the outside of the knee. Similarly, around 30 degrees, although the number of detected signals is low, there are inflammations with identifiable sources, so it can be determined that the inflammation with significant damage is on the inside of the knee. However, compared to the 0-10 degree range, the number of identified inflammations is low and they occur in the latter half of the measurement, so it can be determined that the injury does not require urgent treatment. In the 70-90 degree range, the number of detected signals is high, and multiple inflammations with identifiable sources are detected in the first half of the measurement. Since multiple inflammations with identifiable sources are detected in the first half of the measurement, it can be determined that there is a very high possibility that the inflammation with significant damage is on the inside of the knee. In addition, since the number of detected signals is high over a wide area, it can be determined that there is widespread, shallow inflammation, or widespread bone and cartilage deterioration and deformation. Based on these findings, it can be concluded that in the 70-90 degree range, there is widespread inflammation, deterioration, and deformation on the inside of the knee, and that this is likely causing significant inflammation and damage.

[0046] Figures 9 and 10 show the clinical examination results of the knee joint obtained in Figures 6 to 8. Figure 9(A) is anterior and lateral X-ray images of the knee joint, Figure 9(B) is anterior and lateral MRI images of the knee joint, Figure 10(A) is an arthroscopic image of the lateral region of the tibia, and Figure 10(B) is an arthroscopic image of the medial region of the femur and meniscus. As shown in Figure 9, the physician's diagnosis of the X-ray and MRI images revealed damage in the areas corresponding to the results obtained in Figures 6 to 8.

[0047] Furthermore, Figure 10(A) shows that the surface of the tibia is fibrotic and has a frayed appearance. This corresponds to the inflammation indicated by the triangle in Figure 8. Also, Figure 10(B) shows images of the inner side of the femur and meniscus, where the cartilage is extensively damaged and surface damage is visible. This corresponds to the results indicated by the circle and the number of detected lesions in Figure 8. In other words, clinical verification of the results obtained in Figures 6 to 8 revealed that the degree and location of damage are consistent, and the results from Figures 6 to 8 can be used as important information when diagnosing knee joint inflammation.

[0048] Figure 11 is a flowchart showing the operation of the calculation unit in the knee joint inflammation detection device according to this embodiment. When the AE sensor 12 and goniometer 13 are attached to the subject 11 and the examination begins, the input unit 31 of the calculation unit 16 receives the signals detected by the AE sensor 12 and the signals detected by the goniometer 13 and stores them in the signal information storage unit 32 (S1). The inflammation location calculation unit 33 identifies the three-dimensional location of the inflammation based on the signal information of the AE sensor 12 stored in the signal information storage unit 32 (S2). The output control unit 32 uses the signal information of the AE sensor 12, the signal information of the goniometer 13, and the identified three-dimensional location of the inflammation stored in the signal information storage unit 32 to output the information shown in Figures 6 to 8 described above (S3) and terminate the process.

[0049] The output information from the output control unit 32 may include all of the information shown in Figures 6 through 8, or it may include only one of them.

[0050] Furthermore, the AE sensor 12 may be configured to identify whether the cause of inflammation is cartilage, meniscus, or bone, depending on the frequency of the signal it detects. That is, since cartilage, meniscus, and bone all have different constituent components and different hardnesses, the elastic waves generated by cracks, deformations, etc., each exhibit corresponding characteristics in terms of frequency. By classifying these frequency characteristics, it is possible to identify whether the cause of inflammation is cartilage, meniscus, or bone.

[0051] As described above, in the knee joint inflammation detection device according to this embodiment, multiple anterior sensors are attached to the subject 11 so as to surround the joint between the femur and tibia when viewed from the front of the subject 11's knee during the examination, and multiple posterior sensors are attached to the posterior outer and / or posterior inner sides of the subject 11's knee. Therefore, the three-dimensional location of inflammation in the knee joint can be accurately identified based on the signal detected by the AE sensor 12.

[0052] Furthermore, since four anterior sensors are arranged in a rectangular shape surrounding the joint between the femur and tibia, and two posterior sensors are arranged vertically on the posterior outer side or posterior inner side of the knee, the three-dimensional location of inflammation in the knee joint can be accurately and reliably identified.

[0053] Furthermore, by outputting the presence and location of inflammation at each angle of the knee joint during knee flexion and extension, it is possible to diagnose the effects of inflammation during knee movement, and specialists such as doctors can also infer the state of inflammation to some extent based on the angle.

[0054] Furthermore, if detection signals are obtained from a predetermined number or more of the multiple AE sensors 12 that are installed, the source location of the inflammation corresponding to the detection signal is output, and the detection signals from fewer than the predetermined number of sensors are output as the number of detections. This makes it possible to distinguish between major inflammation and other minor inflammations depending on the number of reacting sensors, thereby assisting physicians in diagnosing inflammation.

[0055] Furthermore, when outputting the location of inflammation, it outputs inflammation on the inside of the knee and inflammation on the outside of the knee in different ways. This allows for quick and easy identification of the approximate location of inflammation, for example, during a medical examination.

[0056] Furthermore, the AE sensor 12 identifies whether the inflammation corresponding to the detected signal is in the cartilage, meniscus, or bone, depending on the frequency of the detected signal, making it easier to determine a diagnostic strategy based on the state of inflammation. [Explanation of Symbols]

[0057] 1. Knee joint inflammation detection device 11 Target Persons 12 (12a~12f) AE sensor 13 Goniometer 14 Preamplifier 15 Goniometer Amplifier 16 Arithmetic unit 31 Input section 32 Signal Information Storage Unit 33 Inflammation location calculation unit 34 Output Control Unit

Claims

1. A sensor that detects elastic waves generated from the knee joint during movement of the knee joint as an ultrasonic detection signal, An inflammation location identification means that identifies the presence or absence of inflammation in the knee joint of the person being examined and the location of said inflammation, based on the aforementioned detection signal, The system includes an output control means that outputs the presence and location of inflammation for each angle of the knee joint during knee flexion and extension movements, During the examination, multiple anterior sensors are positioned to surround the joint between the femur and tibia when viewed from the front of the knee of the person being examined, and multiple posterior sensors are positioned on the lateral posterior and / or medial posterior of the knee of the person being examined, and these sensors are attached to the person being examined. A knee joint inflammation detection device characterized by outputting the location of inflammation corresponding to a detection signal when a detection signal is obtained from a predetermined number or more of the multiple sensors attached, and outputting the detection signal from fewer than the predetermined number of sensors as the number of detections.

2. A sensor that detects elastic waves generated from the knee joint during movement of the knee joint as an ultrasonic detection signal, An inflammation location identification means that identifies the presence or absence of inflammation in the knee joint of the person being examined and the location of said inflammation, based on the aforementioned detection signal, The system includes an output control means that outputs the presence and location of inflammation for each angle of the knee joint during knee flexion and extension movements, During the examination, multiple anterior sensors are positioned to surround the joint between the femur and tibia when viewed from the front of the knee of the person being examined, and multiple posterior sensors are positioned on the lateral posterior and / or medial posterior of the knee of the person being examined, and these sensors are attached to the person being examined. A knee joint inflammation detection device characterized in that, when outputting the location of the inflammation, it outputs inflammation on the inside of the knee and inflammation on the outside of the knee in different ways.

3. A sensor that detects elastic waves generated from the knee joint during movement of the knee joint as an ultrasonic detection signal, An inflammation location identification means that identifies the presence or absence of inflammation in the knee joint of the person being examined and the location of said inflammation, based on the aforementioned detection signal, The system includes a means for identifying whether the inflammation corresponding to the detection signal is cartilage, meniscus, or bone inflammation, according to the frequency of the detection signal detected by the sensor. A knee joint inflammation detection device characterized in that, during the examination, multiple anterior sensors are positioned to surround the joint between the femur and tibia when viewed from the front of the knee of the person being examined, and multiple posterior sensors are positioned on the lateral posterior and / or medial posterior of the knee of the person being examined, and these are attached to the person being examined.

4. Inflammation location identification means that detects elastic waves generated from the knee joint during movement of the knee joint as ultrasonic detection signals, and during examination, multiple anterior sensors arranged to surround the patella when viewed from the front of the knee of the person being examined, and multiple posterior sensors arranged on the lateral posterior and / or medial posterior of the knee of the person being examined, based on the detection signals from each sensor attached to the person being examined, to identify whether or not there is inflammation in the knee joint of the person being examined and the location of the inflammation. A computer is used as an output control means to output the presence and location of inflammation for each angle of the knee joint during knee flexion and extension movements. A knee joint inflammation detection program characterized by outputting the location of inflammation corresponding to a predetermined number of detection signals obtained from multiple attached sensors, and outputting the number of detection signals from fewer than the predetermined number of sensors as the number of detections.

5. An inflammation location identification means detects elastic waves generated from the knee joint during movement of the knee joint as ultrasonic detection signals, and during examination, multiple anterior sensors arranged around the patella when viewed from the front of the knee of the person being examined, and multiple posterior sensors arranged on the lateral posterior and / or medial posterior of the knee of the person being examined, based on the detection signals from each sensor attached to the person being examined, to identify whether or not there is inflammation in the knee joint of the person being examined and the location of such inflammation. A computer is used as an output control means to output the presence and location of inflammation for each angle of the knee joint during knee flexion and extension movements. A knee joint inflammation detection program characterized by outputting the location of inflammation on the inside of the knee and inflammation on the outside of the knee in different ways.

6. Inflammation location identification means that detects elastic waves generated from the knee joint during movement of the knee joint as ultrasonic detection signals, and during examination, a plurality of anterior sensors arranged so as to surround the patella when viewed from the front of the knee of the person being examined, and a plurality of posterior sensors arranged on the lateral posterior and / or medial posterior of the knee of the person being examined, based on the detection signals from each sensor attached to the person being examined, to identify whether or not there is inflammation in the knee joint of the person being examined and the location of the inflammation. A knee joint inflammation detection program characterized by using a computer as a means of identifying whether the inflammation corresponding to a detection signal is cartilage, meniscus, or bone inflammation, according to the frequency of the detection signal detected by each sensor.

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