WO2022116411A1 - 一种人体功能性关节旋转中心检测与定位分析方法 - Google Patents

一种人体功能性关节旋转中心检测与定位分析方法 Download PDF

Info

Publication number
WO2022116411A1
WO2022116411A1 PCT/CN2021/080984 CN2021080984W WO2022116411A1 WO 2022116411 A1 WO2022116411 A1 WO 2022116411A1 CN 2021080984 W CN2021080984 W CN 2021080984W WO 2022116411 A1 WO2022116411 A1 WO 2022116411A1
Authority
WO
WIPO (PCT)
Prior art keywords
joint
coordinate system
fcr
human body
rotation
Prior art date
Application number
PCT/CN2021/080984
Other languages
English (en)
French (fr)
Inventor
冉令华
周子健
徐红旗
张欣
赵朝义
呼慧敏
赵鹤
Original Assignee
中国标准化研究院
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 中国标准化研究院 filed Critical 中国标准化研究院
Priority to US17/764,544 priority Critical patent/US11707209B2/en
Publication of WO2022116411A1 publication Critical patent/WO2022116411A1/zh

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1116—Determining posture transitions
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A61B5/1122—Determining geometric values, e.g. centre of rotation or angular range of movement of movement trajectories
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1121—Determining geometric values, e.g. centre of rotation or angular range of movement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
    • A61B5/1127—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique using markers
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4538—Evaluating a particular part of the muscoloskeletal system or a particular medical condition
    • A61B5/4576—Evaluating the shoulder

Definitions

  • the invention relates to the technical field of human body detection and positioning, in particular to a method for detection and positioning analysis of the rotation center of a functional joint of a human body.
  • Sports posture analysis is a very important research direction in sports events, especially in the context of the Olympics of science and technology, the analysis of the sports posture of athletes can, on the one hand, screen out better athletes, and on the other hand, help athletes find out in time. Postural defects in sports help athletes to further improve training, especially for sports that require relatively high posture, such as ice and snow events.
  • the analysis of motion posture needs to be based on digital dummies.
  • Traditional digital dummies are constructed according to human body structure and anatomical knowledge, and their postures are single, so traditional digital dummies cannot meet the posture analysis during motion.
  • the functional joint rotation center of the human body must be detected and analyzed.
  • the existing detection methods for the human functional joint rotation center all aim to have higher detection accuracy.
  • the trajectory continuity to the functional joint rotation center is not good enough.
  • the current positioning analysis method for human functional joints is based on kinematic parameters. Although high-precision positioning analysis results can be achieved, the positioning process is complex and takes a long time.
  • the present invention provides a method for detecting and positioning the rotation center of a functional joint of the human body.
  • the continuity of the trajectory is very good; the positioning analysis method only needs to perform a brief three-dimensional scan of the human body to obtain the position of the rotation center of the joints of the whole body, so that the positioning analysis of the joint position can get rid of the complex kinematic analysis, and can be more Quickly estimate and locate joint positions.
  • a first aspect of the present invention provides a method for detecting the center of rotation of a functional joint of a human body, comprising:
  • Step 11 In a continuous motion, the functional joint rotation center FCR of the human body is abstracted as the center of a flexible ball that satisfies the constraints:
  • the distances between the three marked points M1, M2, and M3 on the FCR-related body segment are kept within the specified range, and the three marked points M1, M2, and M3 are points on the flexible spherical surface;
  • Step 12 At any moment in the test process, determine the position coordinates of the center of the ball (ie FCR) at this moment according to the position coordinates of M1, M2, and M3 on the FCR-related body segment, then in a continuous motion, according to M1, M2, and M3
  • the position information of M2 and M3 can determine the position information of the center of the ball (that is, the FCR), and then the movement trajectory of the FCR in the continuous motion can be obtained.
  • the human functional joint rotation center FCR specifically refers to at least one of shoulder joint FCR, elbow joint FCR, hip joint FCR and knee joint FCR.
  • the relevant body segment is the upper arm of the human body, that is, the marker points M1, M2, M3 are located on the upper arm of the human body; Points M1, M2, and M3 are located on the human forearm; for the hip joint FCR detection, the relevant body segment is the human thigh, that is, the marked points M1, M2, and M3 are located on the human thigh; for the knee joint FCR, the relevant body segment is the human calf, marked Points M1, M2, and M3 are located on the human lower leg.
  • step 12 includes:
  • Step 121 establish a local coordinate system;
  • the local coordinate system includes a chest coordinate system, a marker point coordinate system, and also includes at least one of an upper arm coordinate system, a forearm coordinate system, a thigh coordinate system, and a calf coordinate system;
  • Step 122 Convert the position coordinates of the marker points M1, M2, and M3 in the absolute coordinate system to the position coordinates in the chest coordinate system;
  • Step 123 Calculate the rotation matrix between the local coordinate systems and the position coordinates of the rotation center FCR of the functional joint of the human body in the local coordinate system;
  • Step 124 Convert the position coordinates of the human body functional joint rotation center FCR in the local coordinate system to the position coordinates in the chest coordinate system through the rotation matrix, and then convert them to the coordinates in the absolute coordinate system, and then obtain the human body functional joints The detection result of the center of rotation FCR.
  • the adopted local coordinate system includes chest coordinate system and upper arm coordinate system; for elbow joint FCR detection, the adopted local coordinate system includes chest coordinate system, upper arm coordinate system, and forearm coordinate system.
  • the local coordinate systems used include the chest coordinate system and the thigh coordinate system; for the FCR detection of the knee joint, the local coordinate systems used include the chest coordinate system, the thigh coordinate system, and the calf coordinate system.
  • step 12 For shoulder joint FCR detection, the specific process of step 12 is:
  • a second aspect of the present invention provides a method for positioning and analyzing the center of rotation of a functional joint of a human body, including:
  • Step 21 obtain the morphological parameters of the human body through 3D scanning
  • Step 22 According to the fitting relationship between the morphological parameters of the human body and the joints of the human body, perform positioning analysis on the joints of the human body;
  • Step 23 Compensate the analysis result of human joint positioning.
  • three-dimensional scanning is performed on the three postures of the natural standing posture, the upright posture and the sitting posture of the human body to obtain the morphological parameters of the human body.
  • determining the fitting relationship between the morphological parameters of the human body and the joints of the human body described in step 22 includes:
  • Step 221 Determine the joint position coordinates in the standing posture of the human body
  • Step 222 Perform principal component analysis on the human body morphological parameters to determine N major principal components of the human body morphological parameters;
  • Step 223 Fitting the N major principal components of the human body morphological parameters and the joint position coordinates in the standing posture of the human body determined in step 221, respectively, to obtain the fitting relationship:
  • FCRix, FCRiy and FCRiz represent the x, y and z-axis coordinates of the i-th joint, respectively, a ix1 , a ix2 , ..., a ixN , a iy1 , a iy2 , ..., a iyN , a iz1 , a iz2 , ..., a izN are fitting coefficients, PC1, PC2, ..., PCN are the N principal components of human morphological parameters.
  • step 221 the position coordinates of the shoulder joint, the elbow joint, the hip joint, and the knee joint are determined by using the method for detecting the rotation center of the functional joint of the human body.
  • step 221 for the joints at the end of the limbs and the joints of the human body, the position coordinates of the joints are represented by the coordinates of the bony landmark points.
  • the compensation for the human body joint positioning analysis result includes translation and rotation.
  • the translation includes: selecting a translation standard joint point; calculating the difference between the measured coordinate value of the standard joint point and the positioning coordinate value to determine the translation amount; Shift amount to pan.
  • the rotation includes: selecting a rotation standard joint point; calculating the rotation amount of the upper limb of the wrist joint after translation and the wrist joint before translation relative to the height axis passing through the rotation standard joint point; The joints on the translated upper limb are rotated according to the rotation amount of the upper limb.
  • the rotation further comprises: selecting a rotation standard joint point; calculating the rotation amount of the lower extremity of the ankle joint after translation and the ankle joint before translation relative to the height axis of the rotation standard joint point; The joints on the translated lower limb are rotated according to the rotation amount of the lower limb.
  • the human functional joint rotation center detection method of the present invention is based on the idea of a flexible ball, and is easy to operate within a certain error range. The most important thing is that the method performs very well in the continuity of the joint trajectory, and can obtain joints with very good continuity.
  • the movement trajectory of the rotation center; the positioning analysis method establishes a fitting relationship between the morphological parameters of the human body and the joint positions based on the detection method, so that the morphological parameters of the human body can be obtained by simply performing a brief three-dimensional scan of the human body
  • the position of the rotation center of the joints of the whole body makes the positioning analysis of the joint position get rid of the complex kinematic analysis.
  • the method for detecting and positioning the rotation center of the functional joints of the present invention can be used for the collection and analysis of the movement posture of the players in sports.
  • FIG. 1 is a schematic flowchart of a preferred embodiment of a method for detecting the rotation center of a functional joint of a human body according to the present invention.
  • FIG. 2 is a schematic flowchart of a preferred embodiment of the method for analyzing the rotation center of a human functional joint according to the present invention.
  • FIG. 3 is a schematic diagram of the three-dimensional scanning posture of the embodiment shown in FIG. 2 according to the method for positioning and analyzing the rotation center of a functional joint of the human body according to the present invention.
  • FIG. 4 is a schematic diagram of morphological parameters according to another embodiment of the method for analyzing the rotation center of a human functional joint according to the present invention.
  • FIG. 5 is a histogram of the contribution of the principal components of the morphological parameters of the embodiment shown in FIG. 4 according to the method for analyzing the rotation center of the human functional joint according to the present invention.
  • FIG. 6A is the result of the positioning analysis of subject No. 7 in the embodiment shown in FIG. 4 according to the method for positioning and analyzing the rotation center of the human functional joint according to the present invention before compensation.
  • FIG. 6B is the result of the positioning analysis of the subject No. 15 in the embodiment shown in FIG. 4 according to the method for positioning and analyzing the rotation center of the human functional joint according to the present invention before compensation.
  • FIG. 6C is a result of the positioning analysis of subject No. 2 in the embodiment shown in FIG. 4 according to the method for positioning and analyzing the rotation center of a human functional joint according to the present invention before compensation.
  • FIG. 7 is a result of the positioning analysis of subject No. 7 according to the embodiment shown in FIG. 4 according to the positioning analysis method of the human functional joint rotation center of the present invention after compensation.
  • FIG. 8 is a schematic diagram of the joint positioning analysis result corresponding to the average value of the morphological parameters of the embodiment shown in FIG. 4 according to the positioning analysis method of the human functional joint rotation center of the present invention.
  • 9A-9L are schematic diagrams showing the range and limit of each principal component influencing the joint positioning analysis result of the embodiment shown in FIG. 4 according to the method for analyzing the rotation center positioning of a human functional joint of the present invention.
  • Human functional joint rotation center detection refers to calculating the position of the joint functional rotation center according to the kinematic parameters of the human body in motion
  • the positioning analysis of the human functional joint rotation center refers to estimating the position of the joint functional rotation center according to the static human morphological parameters.
  • the FCR can be considered to be fixed in a short period of time, then the distance from the marked point on the FCR-related body paragraph to the FCR is fixed, so the FCR can be abstracted as the center of the sphere, and the marked point on the related body paragraph Abstract as a point on a sphere.
  • the FCR of the center of the sphere can be obtained. Location.
  • a method for detecting the rotation center of a functional joint of a human body includes:
  • Step 11 In a continuous motion, the functional joint rotation center FCR of the human body is abstracted as the center of a flexible ball that satisfies the constraints:
  • the distances between the three marked points M1, M2, and M3 on the FCR-related body segment are kept within the specified range, and the three marked points M1, M2, and M3 are points on the flexible spherical surface;
  • Step 12 At any moment in the test process, determine the position coordinates of the center of the ball (ie FCR) at this moment according to the position coordinates of M1, M2, and M3 on the FCR-related body segment, then in a continuous motion, according to M1, M2, and M3
  • the position information of M2 and M3 can determine the position information of the center of the ball (that is, the FCR), and then the movement trajectory of the FCR in the continuous motion can be obtained.
  • the human functional joint rotation center FCR specifically refers to at least one of the shoulder joint FCR, the elbow joint FCR, the hip joint FCR, and the knee joint FCR.
  • the relevant body segment is the upper arm of the human body, that is, the marker points M1, M2, and M3 are located on the upper arm of the human body;
  • the relevant body segment is the human forearm, that is, the marker points M1, M2, and M3 are located on the human body.
  • the relevant body segment is the human thigh, that is, the marked points M1, M2, M3 are located in the human thigh; for the knee joint FCR, the relevant body segment is the human calf, and the marked points M1, M2, M3 are located in the human body calf.
  • Step 12 includes:
  • Step 121 establish a local coordinate system;
  • the local coordinate system includes a chest coordinate system, a marker point coordinate system, and also includes at least one of an upper arm coordinate system, a forearm coordinate system, a thigh coordinate system, and a calf coordinate system;
  • Step 122 Convert the position coordinates of the marker points M1, M2, and M3 in the absolute coordinate system to the position coordinates in the chest coordinate system;
  • Step 123 Calculate the rotation matrix between the local coordinate systems and the position coordinates of the rotation center FCR of the functional joint of the human body in the local coordinate system;
  • Step 124 Convert the position coordinates of the human body functional joint rotation center FCR in the local coordinate system to the position coordinates in the chest coordinate system through the rotation matrix, and then convert them to the coordinates in the absolute coordinate system, and then obtain the human body functional joints The detection result of the center of rotation FCR.
  • the adopted local coordinate system includes chest coordinate system and upper arm coordinate system; for elbow joint FCR detection, the adopted local coordinate system includes chest coordinate system, upper arm coordinate system, and forearm coordinate system;
  • the local coordinate systems used include the chest coordinate system and the thigh coordinate system;
  • the local coordinate systems used include the chest coordinate system, the thigh coordinate system, and the calf coordinate system.
  • step 12 is described in detail, and other elbow joint FCR, hip joint FCR and knee joint FCR detection step 12 may refer to shoulder joint FCR detection.
  • step 12 For shoulder joint FCR detection, the specific process of step 12 is:
  • the three-axis direction of the chest coordinate system is the same as the direction of the absolute coordinate system, and the position of the origin coincides with the position of the upper chest point.
  • the purpose of establishing the chest coordinate system is to offset the influence of the upper arm translation caused by the torso displacement during human walking. In the chest coordinate system, the motion trajectory of the upper arm of the human body is dominated by rotation.
  • the origin is at the shoulder point
  • the initial three-axis direction is the same as that of the absolute coordinate system.
  • the rotation amount of the coordinate system before and after dt can be calculated according to the three vectors that point to the three marked points of the upper arm from the shoulder peak as the starting point, that is, the rotation matrix. According to the rotation matrix at each moment, the three-axis direction of the upper arm coordinate system can be iteratively calculated.
  • the coordinate system of the marked point in view of the fact that the axial direction of the upper arm coordinate system is not used in the actual detection process, only pays attention to the three vector rotations in the upper arm coordinate system.
  • the hip joint FCR detection process is similar to the shoulder joint FCR detection process.
  • the elbow joint FCR detection process is slightly different from the shoulder joint FCR detection process. Because the elbow joint connects the upper arm and the forearm, in the absolute coordinate system or the chest coordinate system, the elbow joint is mainly affected by the motion of the upper arm, so the calculation of the functional rotation center of the elbow joint cannot be directly from the chest coordinate system like the functional rotation center of the shoulder joint.
  • To convert to the forearm coordinate system it is necessary to convert from the chest coordinate system to the upper arm coordinate system first, offset the effect of the upper arm rotation, and then calculate the functional rotation center of the elbow joint according to the relationship between the forearm coordinate system and the upper arm coordinate system.
  • the specific method is: after calculating the rotation matrix from the chest coordinate system to the upper arm coordinate system, rotate the forearm coordinate system by the same amount according to the rotation matrix, and then perform the calculation according to the upper arm coordinate system and the rotated forearm coordinate system.
  • the knee joint FCR detection process is similar to the elbow joint FCR detection process.
  • a method for positioning and analyzing the rotation center of a human functional joint includes:
  • Step 21 obtain the morphological parameters of the human body through 3D scanning
  • Step 22 According to the fitting relationship between the morphological parameters of the human body and the joints of the human body, perform positioning analysis on the joints of the human body;
  • Step 23 Compensate the analysis result of human joint positioning.
  • three-dimensional 3D stance is performed on the three postures of the human body's natural standing posture (the leftmost posture in the figure), the upright posture (the middle posture in the figure) and the sitting posture (the rightmost posture in the figure). Scanning to obtain morphological parameters of the human body.
  • the natural standing posture the feet of the human body are open to the width of the shoulders, and the hands are open at the same time. Because the torso of the human body is not close to the arms in this posture, and the legs do not interfere with each other, so the general circumference parameters and width parameters are measured in this attitude.
  • the upright posture the arms of the human body are close to the torso, the legs are close together, and the heels of the feet are close to each other.
  • the human bones are straight upward, which is very suitable for measuring height parameters.
  • the thigh of the human body in the sitting position is parallel to the ground, the right arm is stretched forward horizontally, the upper arm of the left hand is vertically downward, and the forearm is horizontally forward.
  • step 22 the process of determining the fitting relationship between the morphological parameters of the human body and the joints of the human body includes:
  • Step 221 Determine the joint position coordinates in the standing posture of the human body
  • Step 222 Perform principal component analysis on the human body morphological parameters to determine N major principal components of the human body morphological parameters;
  • Step 223 Fitting the N major principal components of the human body morphological parameters and the joint position coordinates in the standing posture of the human body determined in step 221, respectively, to obtain the fitting relationship:
  • FCRix, FCRiy and FCRiz represent the x, y and z-axis coordinates of the i-th joint, respectively, a ix1 , a ix2 , ..., a ixN , a iy1 , a iy2 , ..., a iyN , a iz1 , a iz2 , ..., a izN are fitting coefficients, PC1, PC2, ..., PCN are the N principal components of human morphological parameters.
  • step 221 the position coordinates of the shoulder joint, the elbow joint, the hip joint, and the knee joint are determined using the method for detecting the rotation center of the human functional joint described in Embodiment 1.
  • the position coordinates of other joints can be determined according to the needs of positioning analysis, such as the joints at the end of some limbs and the joints of the human torso, and then the posture of the entire human body can be analyzed and estimated.
  • the position coordinates of the joints are represented by the coordinates of the bony landmarks.
  • step 23 the compensation for the analysis results of the human joint positioning includes translation and rotation.
  • the translation includes: selecting a translation standard joint point; calculating the difference between the measured coordinate value of the standard joint point and the positioning coordinate value to determine the translation amount; and translating all the positioned joints according to the translation amount.
  • the rotation includes: selecting a rotation standard joint point; calculating the rotation amount of the upper limb of the wrist joint after translation and the wrist joint before translation relative to the height axis passing through the rotation standard joint point; The upper limb rotation amount is rotated.
  • the rotation also includes: selecting a rotation standard joint point; calculating the rotation amount of the lower limb between the ankle joint after translation and the ankle joint before translation relative to the height axis passing through the rotation standard joint point; Rotate according to the described lower extremity rotation.
  • the position coordinates of 22 joints in the standing posture of the human body are determined.
  • the 22 joints include shoulder joints, elbow joints, hip joints, and knee joints, and the position coordinates of these four joints are calculated and obtained by using the functional joint rotation center detection method.
  • the position coordinates of other joints are replaced by the coordinates of bony landmarks.
  • the first type of joints includes hands and feet.
  • the hand joints are replaced by the midpoints of the two and five fingers on the midline of the length of the hand, and the joints of the feet are replaced by the midpoints of the one or four toes on the midline of the foot length.
  • the second type of joints are mainly on the head and trunk.
  • the points used to replace the joints on the head include the glabella point and the midpoint of the tragus point, the neck has the cervical point, and the points used to replace the joints on the trunk are the thoracic vertebral point, The center of the left and right anterior superior iliac spine points and the left and right posterior superior iliac spine points, and the midpoint of the line connecting the left and right greater trochanters.
  • These joints correspond to the forehead (end of the head), head-neck joint, neck-thoracic joint, thoracic-abdominal joint, abdominal-pelvic joint, and pelvic center.
  • the rotation angle of the wrist joint and ankle joint is small in the process of gait measurement, so the midpoint of the radial styloid process and the ulnar styloid process and the midpoint of the medial and lateral malleolus are used instead.
  • a total of 66 coordinate values are obtained.
  • Each coordinate value is linearly fitted with the principal components of the morphological parameters, and the fitting relationship between the morphological parameters of the human body and the position coordinates of the human body joints is obtained.
  • the human body joint positioning analysis can be performed according to the morphological parameters, which is used to estimate the joint rotation center.
  • 6A-6C are schematic diagrams showing the positioning of the joints of subject No. 7, subject No. 15, and subject No. 2, and comparing the positioning results with the joint positions calculated according to kinematic parameters.
  • the localization analysis results of all 22 joints are translated.
  • Select the translation standard joint points in this embodiment, the neck point, the abdominal-pelvic joint point (the geometric center of the anterior superior iliac spine point and the posterior superior iliac spine point), the thoracic spine point, the wrist joint point and the ankle joint point are selected A total of seven points are used as translation standard joint points; the difference between the measured coordinate value of the standard joint point and the positioning coordinate value is calculated to determine the translation amount, and the translation amount can be determined according to the least squares method; Translate by the translation amount.
  • the joint points on the translated upper limb and the joint points on the lower limb are rotated respectively.
  • Select the rotation standard joint point In this embodiment, the thoracic vertebra point after translation is selected as the rotation standard joint point; The rotation amount of the upper limb; rotate the joint on the upper limb after translation according to the rotation amount of the upper limb; calculate the rotation amount of the lower limb between the ankle joint after translation and the ankle joint before translation relative to the height axis of the rotation standard joint point; The joints on the translated lower limb are rotated according to the rotation amount of the lower limb.
  • Figure 7 shows the positioning analysis results of subject No. 7 after translation and rotation compensation. It can be found that after translation and rotation, the joint positions estimated according to the morphological parameters and the joint positions calculated according to the kinematic parameters have a high degree of coincidence. Although there is still an error, the error is within an acceptable range.
  • This proves the effectiveness and accuracy of the method for positioning and analyzing the rotation center of a human functional joint provided by the present invention, and the method for positioning and analyzing the rotation center of a human functional joint of the present invention can realize the human body morphology obtained only from a brief three-dimensional scan.
  • the parameter estimates the position of the rotation center of the joint, so that the positioning analysis of the joint position can get rid of the complex kinematic analysis, and the estimated speed of the joint position can reach a higher value.
  • Figure 8 is a schematic diagram showing the results of joint localization analysis corresponding to the average value of morphological parameters.
  • 9A-9L are schematic diagrams showing the range and limit of the principal component affecting the joint positioning analysis result with each principal component as a single variable in turn.
  • the first principal component represents the width and circumference of the upper body, and the subjects with larger first principal components have wider and thicker upper bodies;
  • the second principal component represents the height of the human body;
  • the third principal component is not very representative of the human body, but according to the factor load factor in Table 3 greater than 0.4, that is, the wall spacing and the full head length, it is inferred that this principal component represents the forward leaning angle of the human body when standing, and the third principal component is larger The standing posture of the group of people is more inclined to be forward;
  • the fourth principal component represents the distance between the knees of the human body, and the only item whose factor load coefficient is greater than 0.4 is the medial malleolus height.
  • the medial malleolus height is related to the rotation of the foot and then affects the knees;
  • the fifth principal component represents In the ratio of limbs to body, subjects with a large fifth principal component have longer arms;
  • the sixth principal component represents the ratio of lower limbs to height of the human body. Simply put, subjects with a large sixth principal component have a higher hip than Humans of the same or similar height.
  • the principal component analysis is not performed on the morphological parameters of the human body, but the fitting relationship is directly established, so that although the amount of data calculation will be relatively large , but the estimation accuracy will be higher.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Biomedical Technology (AREA)
  • Medical Informatics (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Veterinary Medicine (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Dentistry (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Physiology (AREA)
  • Geometry (AREA)
  • Physical Education & Sports Medicine (AREA)
  • Orthopedic Medicine & Surgery (AREA)
  • Rheumatology (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

一种人体功能性关节旋转中心检测与定位分析方法，人体功能性关节旋转中心检测方法包括：步骤11：在一段连续运动中，将人体功能性关节旋转中心FCR抽象为一个柔性球的球心；步骤12：测试过程中的任一时刻，根据标记点M1、M2、M3的位置坐标确定此时刻的球心即FCR位置坐标，进而得到此连续运动中FCR的运动轨迹。定位分析方法基于三维扫描采集的形态学参数对关节位置进行定位分析。检测方法基于柔性球思想，在一定的误差范围内运算简便，且在关节轨迹的连续性上表现非常出色；定位分析方法仅需对人体进行短暂的三维扫描即可得到全身关节的旋转中心的位置，使得关节位置的定位分析摆脱了复杂的运动学分析，定位更快速。

Description

一种人体功能性关节旋转中心检测与定位分析方法 技术领域
本发明涉及人体检测与定位技术领域，具体涉及一种人体功能性关节旋转中心检测与定位分析方法。
背景技术
运动姿态分析是体育运动项目中非常重要的一项研究方向，特别是在科技奥运的背景下，对于运动员的运动姿态进行分析一方面可以筛选出更优质的运动员，另一方面可以帮助运动员及时发现运动中的姿态缺陷，帮助运动员进行进一步的提升训练，特别是对于对运动姿态要求比较高的运动项目，如冰雪项目。
对运动姿态进行分析需要基于数字假人，传统的数字假人根据人体结构和解剖学知识构建，其姿态是单一的，因此传统的数字假人无法满足运动过程中的姿态分析。要分析运动员的运动姿态，必须检测出人体的功能性关节旋转中心并对其进行定位分析，但是现有的对人体功能性关节旋转中心的检测方法均以具有更高检测精度为目标，但是检测到的功能性关节旋转中心的轨迹连续性不够好。当前对于人体功能性关节的定位分析方法是基于运动学参数实现的，虽然可以实现精度较高的定位分析结果，但是定位过程复杂，需要的时间长。
发明内容
为解决以上技术问题，本发明提供了一种人体功能性关节旋转中心检测与定位分析方法，所述检测方法基于柔性球思想，在一定的误差范围内运算简便，最重要的是该方法在关节轨迹的连续性上表现非常出色；所述定位分析方法仅需对人体进行短暂的三维扫描即可得到全身关节的旋转中心的位置，使得关节位置的定位分析摆脱了复杂的运动学分析，可以更快速的对关节位置进行估计定位。
本发明的第一方面提供一种人体功能性关节旋转中心检测方法，包括：
步骤11：在一段连续运动中，将人体功能性关节旋转中心FCR抽象为一个柔性球的球心，所述柔性球满足约束条件：
A、FCR相关身体段落上的三个标记点M1、M2、M3之间的距离保持规定的范围内，且三个标记点M1、M2、M3为柔性球球面上的点；
B、球心FCR与球上点M1、M2、M3的距离(即球的半径)在设定的范围内而非确切的值；
C、FCR的运动轨迹是连续的；
步骤12：测试过程中的任一时刻，根据FCR相关身体段落上的M1、M2、M3的位置坐标确定该时刻的球心(即FCR)位置坐标，则在一段连续的运动中，根据M1、M2、M3的位置信息可以确定球心(即FCR)的位置信息，进而得到该连续运动中FCR的运动轨迹。
优选的是，所述人体功能性关节旋转中心FCR特指肩关节FCR、肘关节FCR、胯关节FCR和膝关节FCR中的至少一种。
上述任一方案优选的是，针对肩关节FCR检测，相关的身体段落为人体上臂，即标记点M1、M2、M3位于人体上臂；针对肘关节FCR检测，相关的身体段落为人体前臂，即标记点M1、M2、M3位于人体前臂；针对胯关节FCR检测，相关的身体段落为人体大腿，即标记点M1、M2、M3位于人体大腿；针对膝关节FCR，相关的身体段落为人体小腿，标记点M1、M2、M3位于人体小腿。
上述任一方案优选的是，步骤12包括：
步骤121：建立局部坐标系；所述局部坐标系包括胸部坐标系，标记点坐标系，还包括上臂坐标系、前臂坐标系、大腿坐标系、小腿坐标系中的至少一种；
步骤122：将标记点M1、M2、M3在绝对坐标系中的位置坐标转换为在胸部坐标系中的位置坐标；
步骤123：计算局部坐标系之间的旋转矩阵以及在局部坐标系中的人体功能性关节旋转中心FCR的位置坐标；
步骤124：将人体功能性关节旋转中心FCR在局部坐标系中的位置坐标通过旋转矩阵转换为在胸部坐标系中的位置坐标，再转换为在绝对坐标系中的坐标，进而得到人体功能性关节旋转中心FCR的检测结果。
上述任一方案优选的是，针对肩关节FCR检测，采用的局部坐标系包括胸部坐标系、上臂坐标系；针对肘关节FCR检测，采用的局部坐标系包括胸部坐标系、上臂坐标系、前臂坐标系；针对胯关节FCR检测，采用的局部坐标系包括胸部坐标系、大腿坐标系；针对膝关节FCR检测，采用的局部坐标系包括胸部坐标系、大腿坐标系、小腿坐标系。
上述任一方案优选的是，针对肩关节FCR检测，步骤12的具体流程为：
(1)在定位运动中，将标记点M1、M2、M3在绝对坐标系中的位置坐标转换为在胸部坐标系中的位置坐标；
(2)在胸部坐标系中，肩关节FCR的坐标是固定的，因此在胸部坐标系中的标记点集的中心
Figure PCTCN2021080984-appb-000001
到肩关节FCRP Jt和P Jt+dt的距离关系表示为：
Figure PCTCN2021080984-appb-000002
Figure PCTCN2021080984-appb-000003
其中，
Figure PCTCN2021080984-appb-000004
是上臂的旋转矩阵，
Figure PCTCN2021080984-appb-000005
为上臂标记坐标系中从原点到肩关节FCR的常数向量，P Jt是肩关节FCR在t时刻在胸部坐标系中的坐标，P Jt+dt是肩关节FCR在t+dt时刻在胸部坐标系中的坐标，dt的取值范围为小于等于1秒；
(3)联合式①和式②，得到线性方程：
Figure PCTCN2021080984-appb-000006
其中
Figure PCTCN2021080984-appb-000007
捕捉时刻0到时刻T的定位运动中，对式③进行积分为：
Figure PCTCN2021080984-appb-000008
其中
Figure PCTCN2021080984-appb-000009
Figure PCTCN2021080984-appb-000010
r 1xt表示t时刻标记点M1在上臂坐标系中的X轴坐标值，其他符号的含义依此类推，n＝3；
(4)根据式④，由最小二乘法确定
Figure PCTCN2021080984-appb-000011
(5)将
Figure PCTCN2021080984-appb-000012
通过旋转矩阵转换为在胸部坐标系中的位置坐标，再转换为在绝对坐标系中的坐标，进而得到肩关节FCR的检测结果。
本发明的第二方面提供一种人体功能性关节旋转中心定位分析方法，包括：
步骤21：通过三维扫描获得人体的形态学参数；
步骤22：根据人体形态学参数与人体关节之间的拟合关系，对人体关节进行定位分析；
步骤23：对人体关节定位分析结果进行补偿。
优选的是，对人体自然站立姿态、立正姿态和坐姿三种姿态进行三维扫描，获得人体的形态学参数。
上述任一方案优选的是，确定步骤22中所述的人体形态学参数与人体关节之间的拟合关系包括：
步骤221：确定人体站立姿态下的关节位置坐标；
步骤222：对人体形态学参数进行主成分分析，确定人体形态学参数N大主成分；
步骤223：对人体形态学参数的N大主成分与步骤221中确定的人体站立姿态下的关节位置坐标分别进行拟合，得到拟合关系：
Figure PCTCN2021080984-appb-000013
其中，FCRix、FCRiy和FCRiz分别表示第i个关节的x、y和z轴坐标，a ix1、a ix2、…、a ixN、a iy1、a iy2、…、a iyN、a iz1、a iz2、…、a izN为拟合系数，PC1、PC2、…、PCN为人体形态学参数的N个主成分。
上述任一方案优选的是，步骤221中，对于肩关节、肘关节、胯关节、膝关节的位置坐标采用所述人体功能性关节旋转中心检测方法确定。
上述任一方案优选的是，步骤221中，对于肢体末端关节以及人体躯干关节，用骨性标志点的坐标表示关节的位置坐标。
上述任一方案优选的是，步骤23中对人体关节定位分析结果进行补偿包括平移和旋转。
上述任一方案优选的是，所述平移包括：选定平移标准关节点；计算标准关节点的测量坐标值与定位坐标值之间的差值确定平移量；对所有定位的关节按照所述的平移量进行平移。
上述任一方案优选的是，所述旋转包括：选定旋转标准关节点；计算平移后的手腕关节与平移前的手腕关节相对于过所述旋转标准关节点的高度轴的上肢旋转量；对平移后的上肢上的关节按照所述上肢旋转量进行旋转。
上述任一方案优选的是，所述旋转还包括：选定旋转标准关节点；计算平移后的脚踝关节与平移前的脚踝关节相对于过所述旋转标准关节点的高度轴的下肢旋转量；对平移后的下肢上的关 节按照所述下肢旋转量进行旋转。
本发明的人体功能性关节旋转中心检测方法基于柔性球思想，在一定的误差范围内运算简便，最重要的是该方法在关节轨迹的连续性上表现非常出色，可以获得连续性非常好的关节旋转中心运动轨迹；所述定位分析方法基于所述检测方法，建立了人体形态学参数与关节位置之间的拟合关系，使得仅需对人体进行短暂的三维扫描获得人体形态学参数即可得到全身关节的旋转中心的位置，使得关节位置的定位分析摆脱了复杂的运动学分析，虽然相对于基于运动学参数计算关节位置损失了一些计算精度，但是可以更快速的对关节位置进行估计定位。本发明的人体功能性关节旋转中心检测与定位分析方法可以用于体育运动中选手的运动姿态的采集与分析。
附图说明
图1为按照本发明的人体功能性关节旋转中心检测方法的一优选实施例的流程示意图。
图2为按照本发明的人体功能性关节旋转中心定位分析方法的一优选实施例的流程示意图。
图3为按照本发明的人体功能性关节旋转中心定位分析方法的如图2所示实施例的三维扫描姿态示意图。
图4为按照本发明的人体功能性关节旋转中心定位分析方法的另一实施例的形态学参数示意图。
图5为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的形态学参数主成分贡献柱状图。
图6A为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的7号受试者进行补偿前的定位分析结果。
图6B为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的15号受试者进行补偿前的定位分析结果。
图6C为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的2号受试者进行补偿前的定位分析结果。
图7为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的7号受试者进行补偿后的定位分析结果。
图8为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的形态学参数平均值对应的关节定位分析结果示意图。
图9A-9L为按照本发明的人体功能性关节旋转中心定位分析方法的如图4所示实施例的各个主成分影响关节定位分析结果的范围及极限示意图。
具体实施方式
为了更好地理解本发明，下面结合具体实施例对本发明作详细说明。
为了更好的对本发明进行详细说明，首先对本发明中涉及到的一些概念进行简单介绍。
人体功能性关节旋转中心检测指根据运动中人体的运动学参数计算关节功能性旋转中心的位置；
人体功能性关节旋转中心定位分析指根据静态的人体形态学参数估计关节功能性旋转中心的位置。
实施例1
根据运动中人体的运动学参数计算关节功能性旋转中心FCR的位置需要在理想条件下具有两个前提：躯干运动可以忽略；皮肤变形可以忽略。
忽略躯干运动，在短时间内可以认为FCR是固定不动的，那么FCR相关身体段落上的标记点到FCR的距离是固定的，因此可以将FCR抽象为球心，相关身体段落上的标记点抽象为球面上的点。通过检测人体运动中附着在相关身体段落上的至少三个标记点的位置，并将短时间内的变化后的标记点的位置视为新的球面上的点，即可求出球心FCR的位置。
FCR相关身体段落上的标记点到FCR的距离固定的性质采用公式表示为：
Figure PCTCN2021080984-appb-000014
其中，
Figure PCTCN2021080984-appb-000015
被定义为时间t时刻在测量坐标系里的FCR坐标，R nt＝(r nxt,r nyt,r nzt) T则代表时间t时刻在测量坐标系里的第n个标记点(一般共三个)的位置。经过非常短的时间dt后，FCR位置的变化可以忽略，
Figure PCTCN2021080984-appb-000016
与
Figure PCTCN2021080984-appb-000017
是非常接近的，因此可以计算出瞬态FCR的位置。
实际进行人体功能性关节旋转中心检测的过程中，当存在皮肤变形时，严格的球心未必存在，即使可以计算出瞬态FCR，计算误差也可能比较大，因此提出一种基于柔性球思想的人体功能性关节旋转中心检测方法，用于减少皮肤变形对FCR检测的影响。
如图1所示，一种人体功能性关节旋转中心检测方法，包括：
步骤11：在一段连续运动中，将人体功能性关节旋转中心FCR抽象为一个柔性球的球心，所述柔性球满足约束条件：
A、FCR相关身体段落上的三个标记点M1、M2、M3之间的距离保持规定的范围内，且三个标记点M1、M2、M3为柔性球球面上的点；
B、球心FCR与球上点M1、M2、M3的距离(即球的半径)在设定的范围内而非确切的值；
C、FCR的运动轨迹是连续的。
步骤12：测试过程中的任一时刻，根据FCR相关身体段落上的M1、M2、M3的位置坐标确定该时刻的球心(即FCR)位置坐标，则在一段连续的运动中，根据M1、M2、M3的位置信息可以确定球心(即FCR)的位置信息，进而得到该连续运动中FCR的运动轨迹。
在本实施例中，所述人体功能性关节旋转中心FCR特指肩关节FCR、肘关节FCR、胯关节FCR和膝关节FCR中的至少一种。针对肩关节FCR检测，相关的身体段落为人体上臂，即标记点M1、M2、M3位于人体上臂；针对肘关节FCR检测，相关的身体段落为人体前臂，即标记点M1、M2、M3位于人体前臂；针对胯关节FCR检测，相关的身体段落为人体大腿，即标记点M1、M2、M3位于人体大腿；针对膝关节FCR，相关的身体段落为人体小腿，标记点M1、M2、M3位于人体小腿。
步骤12包括：
步骤121：建立局部坐标系；所述局部坐标系包括胸部坐标系，标记点坐标系，还包括上臂坐标系、前臂坐标系、大腿坐标系、小腿坐标系中的至少一种；
步骤122：将标记点M1、M2、M3在绝对坐标系中的位置坐标转换为在胸部坐标系中的位置坐标；
步骤123：计算局部坐标系之间的旋转矩阵以及在局部坐标系中的人体功能性关节旋转中心FCR的位置坐标；
步骤124：将人体功能性关节旋转中心FCR在局部坐标系中的位置坐标通过旋转矩阵转换为在胸部坐标系中的位置坐标，再转换为在绝对坐标系中的坐标，进而得到人体功能性关节旋转中心FCR的检测结果。
在本实施例中，针对肩关节FCR检测，采用的局部坐标系包括胸部坐标系、上臂坐标系；针对肘关节FCR检测，采用的局部坐标系包括胸部坐标系、上臂坐标系、前臂坐标系；针对胯关节FCR检测，采用的局部坐标系包括胸部坐标系、大腿坐标系；针对膝关节FCR检测，采用的局部坐标系包括胸部坐标系、大腿坐标系、小腿坐标系。
在本实施例中，以肩关节FCR检测为例，对步骤12进行详细说明，其他肘关节FCR、胯关节FCR和膝关节FCR检测步骤12参照肩关节FCR检测即可。
针对肩关节FCR检测，步骤12的具体流程为：
(1)在定位运动中，将标记点M1、M2、M3在绝对坐标系中的位置坐标转换为在胸部坐标系中的位置坐标；
(2)在胸部坐标系中，肩关节FCR的坐标是固定的，因此在胸部坐标系中的标记点集的中心
Figure PCTCN2021080984-appb-000018
到肩关节FCRP Jt和P Jt+dt的距离关系表示为：
Figure PCTCN2021080984-appb-000019
Figure PCTCN2021080984-appb-000020
其中，
Figure PCTCN2021080984-appb-000021
是上臂的旋转矩阵，
Figure PCTCN2021080984-appb-000022
为上臂标记坐标系中从原点到肩关节FCR的常数向量，P Jt是肩关节FCR在t时刻在胸部坐标系中的坐标，P Jt+dt是肩关节FCR在t+dt时刻在胸部坐标系中的坐标，dt的取值范围为小于等于1秒；
(3)联合式①和式②，得到线性方程：
Figure PCTCN2021080984-appb-000023
其中
Figure PCTCN2021080984-appb-000024
捕捉时刻0到时刻T的定位运动中，对式③进行积分为：
Figure PCTCN2021080984-appb-000025
其中
Figure PCTCN2021080984-appb-000026
Figure PCTCN2021080984-appb-000027
r 1xt表示t时刻标记点M1在上臂坐标系中的X轴坐标值，其他符号的含义依此类推，n＝3；
(4)根据式④，由最小二乘法确定
Figure PCTCN2021080984-appb-000028
(5)将
Figure PCTCN2021080984-appb-000029
通过旋转矩阵转换为在胸部坐标系中的位置坐标，再转换为在绝对坐标系中的坐 标，进而得到肩关节FCR的检测结果。
所述胸部坐标系，其三轴方向与绝对坐标系方向相同，原点位置与胸上点位置重合，建立胸部坐标系目的是抵消人体行走过程中躯干位移带动上臂平移的影响。在胸部坐标系下，人体上臂运动轨迹以旋转为主。
上所述臂坐标系，原点在肩峰点处，初始三轴方向与绝对坐标系相同。根据以肩峰点为起点分别指向上臂三标记点的三条向量可以求出dt前后坐标系旋转量，即旋转矩阵。依据每个时刻的旋转矩阵，可以迭代计算上臂坐标系三轴方向。
所述标记点坐标系，鉴于实际检测过程中没有用到上臂坐标系轴向，只关注了所述上臂坐标系中三条向量旋转量，因此定义标记点坐标系为原点在肩峰点，以三条向量方向为轴向的非标准坐标系。
胯关节FCR检测过程与肩关节FCR检测过程相类似。
肘关节FCR检测过程与肩关节FCR检测过程略有不同。因为肘关节连接上臂与前臂，在绝对坐标系下或胸部坐标系下，肘关节主要受上臂运动影响，因此肘关节功能性旋转中心的计算不能像肩关节功能性旋转中心那样从胸部坐标系直接转换到前臂坐标系，而是需要从胸部坐标系先转换到上臂坐标系，抵消上臂旋转影响后再根据前臂坐标系与上臂坐标系的关系计算肘关节功能性旋转中心。具体做法为：计算出胸部坐标系到上臂坐标系的旋转矩阵后，令前臂坐标系根据所述旋转矩阵旋转相同量，在此基础上再根据上臂坐标系与旋转后前臂坐标系进行计算。
膝关节FCR检测过程与肘关节FCR检测过程相类似。
实施例2
如图2所示，一种人体功能性关节旋转中心定位分析方法，包括：
步骤21：通过三维扫描获得人体的形态学参数；
步骤22：根据人体形态学参数与人体关节之间的拟合关系，对人体关节进行定位分析；
步骤23：对人体关节定位分析结果进行补偿。
如图3所示，步骤21中，对人体自然站立姿态(图中最左侧的姿态)、立正姿态(图中中间的姿态)和坐姿(图中最右侧的姿态)三种姿态进行三维扫描，获得人体的形态学参数。其中自然站立姿态下人体双脚打开与肩同宽，同时双手打开，因为这种姿态下人体的躯干不与双臂紧挨，双腿也不相互干扰，所以一般的围度参数与宽度参数是在这种姿态下测量的。立正姿态下人体双臂紧贴躯干，双腿并拢，双脚脚跟贴紧，这类姿态下人体骨骼笔直向上非常适合测量高度参数。通过调节升降椅的高矮，坐姿下的人体大腿与地面平行，右手手臂水平向前伸直，左手上臂垂直向下，小臂水平向前。
步骤22中，所述的人体形态学参数与人体关节之间的拟合关系的确定过程包括：
步骤221：确定人体站立姿态下的关节位置坐标；
步骤222：对人体形态学参数进行主成分分析，确定人体形态学参数N大主成分；
步骤223：对人体形态学参数的N大主成分与步骤221中确定的人体站立姿态下的关节位置坐标分别进行拟合，得到拟合关系：
Figure PCTCN2021080984-appb-000030
其中，FCRix、FCRiy和FCRiz分别表示第i个关节的x、y和z轴坐标，a ix1、a ix2、…、a ixN、a iy1、a iy2、…、a iyN、a iz1、a iz2、…、a izN为拟合系数，PC1、PC2、…、PCN为人体形态学参数的N个主成分。
步骤221中，对于肩关节、肘关节、胯关节、膝关节的位置坐标采用实施例1中所述人体功能性关节旋转中心检测方法确定。可以根据进行定位分析的需要确定其他关节的位置坐标，如确定一些肢体末端的关节以及人体躯干的关节，进而可以对整个人体的姿态进行分析预估。对于肢体末端关节以及人体躯干关节，用骨性标志点的坐标表示关节的位置坐标。
步骤23中对人体关节定位分析结果进行补偿包括平移和旋转。
所述平移包括：选定平移标准关节点；计算标准关节点的测量坐标值与定位坐标值之间的差值确定平移量；对所有定位的关节按照所述的平移量进行平移。
所述旋转包括：选定旋转标准关节点；计算平移后的手腕关节与平移前的手腕关节相对于过所述旋转标准关节点的高度轴的上肢旋转量；对平移后的上肢上的关节按照所述上肢旋转量进行旋转。所述旋转还包括：选定旋转标准关节点；计算平移后的脚踝关节与平移前的脚踝关节相对于过所述旋转标准关节点的高度轴的下肢旋转量；对平移后的下肢上的关节按照所述下肢旋转量进行旋转。
实施例3
为了对所述人体功能性关节旋转中心定位分析方法的有效性及准确性进行验证，进行了实验。
实验过程中，通过三维扫描采集了30位男性受试者的形态学参数，每位受试者均采集了24个形态学参数，各个形态学参数的示意图如图4所示，30位受试者的形态学参数的具体情况如表1所示。
表1 30位男性受试者的形态学参数
Figure PCTCN2021080984-appb-000031
Figure PCTCN2021080984-appb-000032
对三维扫描获得的形态学参数进行主成分分析，在进行主成分分析之前，需要先计算KMO检验统计量与BartlettP值，以验证三维扫描采集的形态学参数是可以进行主成分分析的，经过计算KMO值为0.64，P值为0.000，表明采集的形态学参数可以进行主成分分析。经过主成分分析后，前10项形态学参数主成分贡献率如图5所示，前8项形态学参数主成分具体贡献率数值如表2所示。
表2 形态学参数主成分贡献率表(前8项)
Figure PCTCN2021080984-appb-000033
可以看出，前六项主成分的累积贡献率已超过百分之八十五，因此在本实施例中选定六项主成分。为找出因子与各形态学参数之间的对应关系，进行因子分析，使用最大方差旋转方法进行旋转。因子分析结果如表3所示。通过表3可以看出，各形态学参数对应的共同度值均高于0.4，说明各形态学参数和因子之间的关联性强，因子可以有效提取出形态学参数的大部分信息量。
表3 旋转后因子载荷系数表
Figure PCTCN2021080984-appb-000034
Figure PCTCN2021080984-appb-000035
分析因子和各形态学参数的对应关系情况。经过分析后认为因子载荷系数绝对值大于0.4时，说明形态学参数与因子之间存在对应关系。因此，根据因子与各形态学参数之间的关系等式，求出因子的值，即特征向量元素分别与受试者各项形态学参数求积的和，并找到各成分中因子载荷系数绝对值大于0.4的项，使两者作回归分析。对于统计学参数调整后R 2值过小的采用淘汰特征向量元素与对应形态学参数之积小于平均值的项的方法进行调整，分析结果如表4。
表4 形态学参数与其主成分回归分析表
Figure PCTCN2021080984-appb-000036
Figure PCTCN2021080984-appb-000037
在本实施例中，确定了人体站立姿态下的22个关节的位置坐标。所述22个关节包括肩关节、肘关节、胯关节、膝关节，这四个关节的位置坐标采用所述的功能性关节旋转中心检测方法计算获得。其他关节的位置坐标采用骨性标志点的坐标代替。
人体众多关节中有两类关节可以由骨性标志点代替，一类是肢体末端如手脚的关节，这类关 节运动信息缺乏但容易描述；另一类是人体躯干的关节，这类关节复杂但简单的运动(如行走)造成的躯干运动或变形较少，因此也可以用骨性标志点代替。第一类关节包括手与脚，手部关节由手长中线上的二五指中点代替，脚部关节由脚长中线上的一四趾中点代替。第二类关节主要在头部与躯干上，头部上用来代替关节的点有眉间点、耳屏点中点，颈部有颈点，躯干上用来代替关节的点有胸椎点、左右髂前上棘点和左右髂后上棘点的中心、左右大转子连线中点。这类关节分别对应前额(头部末端)、头-颈关节、颈-胸关节、胸-腹关节、腹-盆腔关节、盆腔中心。除此之外，手腕关节与脚踝关节在步态测量过程中旋转角度小，因此分别采用桡骨茎突与尺骨茎突中点与内外踝点中点代替。
确定了人体站立姿态下的22个关节的位置后，因为每个关节的位置采用三维坐标表示，因此共获得66个坐标值。对每一个坐标值分别和形态学参数主成分进行线性拟合，得到人体形态学参数与人体关节位置坐标之间的拟合关系。通过所述拟合关系即可根据形态学参数进行人体关节定位分析，用于估计关节旋转中心。
根据人体形态学参数与人体关节位置坐标之间的拟合关系，对关节进行定位分析。图6A-6C所示为对7号受试者、15号受试者、2号受试者的关节进行定位，并将定位结果与根据运动学参数计算的关节位置进行对比的示意图。
通过图6A-6C可以发现，根据人体形态学参数对关节进行定位与根据运动学参数计算的关节位置之间存在误差，因此对定位分析结果进行补偿。
首先，对所有22个关节的定位分析结果进行平移。选定平移标准关节点，在本实施例中，选定颈点、腹-盆关节点(髂前上棘点和髂后上棘点的几何中心)、胸椎点、手腕关节点以及脚踝关节点共七点作为平移标准关节点；计算标准关节点的测量坐标值与定位坐标值之间的差值确定平移量，所述平移量可以根据最小二乘法确定；对所有定位的关节按照计算的所述平移量进行平移。
然后，对平移后的上肢上的关节点和下肢上的关节点分别进行旋转。选择旋转标准关节点，在本实施例中，选定平移后的胸椎点作为旋转标准关节点；计算平移后的手腕关节与平移前的手腕关节相对于过所述旋转标准关节点的高度轴的上肢旋转量；对平移后的上肢上的关节按照所述上肢旋转量进行旋转；计算平移后的脚踝关节与平移前的脚踝关节相对于过所述旋转标准关节点的高度轴的下肢旋转量；对平移后的下肢上的关节按照所述下肢旋转量进行旋转。
图7所示为7号受试者进行平移和旋转补偿后的定位分析结果，可以发现经过平移和旋转之后，根据形态学参数估计的关节位置与根据运动学参数计算的关节位置重合度高，虽然依然存在误差，但是误差在可以接受的范围内。由此证明了本发明所提供的人体功能性关节旋转中心定位分析方法的有效性及准确性，本发明的人体功能性关节旋转中心定位分析方法可以实现仅仅根据短暂的三维扫描获得的人体形态学参数估计关节旋转中心的位置，使得关节位置的定位分析摆脱了复杂的运动学分析，让关节位置的估计速度达到一个更高的值。
实施例4
在本实施例中，对各个主成分对关节定位结果进行影响分析。
以30位受试者的形态学参数的主成分平均值为基础，在正负波动三倍方差的范围内，控制 单一主成分为变量，观察各个主成分对关节旋转中心的影响范围与极限。
图8所示为形态学参数平均值对应的关节定位分析结果示意图。
图9A-9L为依次以各个主成分为单一变量，主成分影响关节定位分析结果的范围及极限示意图。
通过图8以及图9A-9L可以看出，第一主成分代表上半身的宽度与围度，第一主成分较大的受试者其上半身更宽更厚；第二主成分代表人体的高矮；第三主成分对人体的代表性不强，但根据表3中因子载荷系数大于0.4的项，即墙间距与全头长推测该主成分代表人体站立时前倾角度，第三主成分较大的人群的站立姿态更倾向于向前；第四主成分代表人体膝盖间距，其因子载荷系数大于0.4的项只有内踝高，推测内踝高与脚部旋转有关进而影响到膝盖；第五主成分代表四肢与身体的比例，第五主成分大的受试者其手臂更长；第六主成分代表人体下肢与身高的比例，简单地说，第六主成分大的受试者们的胯高于相同或相近身高的人体。
实施例5
在本实施例中，建立人体形态学参数与人体关节位置之间的拟合关系的时候，不对人体形态学参数进行主成分分析，而是直接建立拟合关系，这样虽然数据计算量会比较大，但是估计精度会更高。
需要说明的是，以上实施例仅用于说明本发明的技术方案，而非对其限制；尽管前述实施例对本发明进行了详细的说明，本领域的技术人员应该理解：其可以对前述实施例记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换，而这些替换，并不使相应技术方案的本质脱离本发明技术方案的范围。

Claims (10)

  1. 一种人体功能性关节旋转中心检测方法，其特征在于：包括：
    步骤11：在一段连续运动中，将人体功能性关节旋转中心FCR抽象为一个柔性球的球心，所述柔性球满足约束条件：
    A、FCR相关身体段落上的三个标记点M1、M2、M3之间的距离保持规定的范围内，且三个标记点M1、M2、M3为柔性球球面上的点；
    B、球心FCR与球上点M1、M2、M3的距离(即球的半径)在设定的范围内而非确切的值；
    C、FCR的运动轨迹是连续的；
    步骤12：测试过程中的任一时刻，根据FCR相关身体段落上的M1、M2、M3的位置坐标确定该时刻的球心(即FCR)位置坐标，则在一段连续的运动中，根据M1、M2、M3的位置信息可以确定球心(即FCR)的位置信息，进而得到该连续运动中FCR的运动轨迹。
  2. 如权利要求1所述的人体功能性关节旋转中心检测方法，其特征在于：所述人体功能性关节旋转中心FCR特指肩关节FCR、肘关节FCR、胯关节FCR和膝关节FCR中的至少一种。
  3. 如权利要求2所述的人体功能性关节旋转中心检测方法，其特征在于：针对肩关节FCR检测，相关的身体段落为人体上臂，即标记点M1、M2、M3位于人体上臂；针对肘关节FCR检测，相关的身体段落为人体前臂，即标记点M1、M2、M3位于人体前臂；针对胯关节FCR检测，相关的身体段落为人体大腿，即标记点M1、M2、M3位于人体大腿；针对膝关节FCR，相关的身体段落为人体小腿，标记点M1、M2、M3位于人体小腿。
  4. 如权利要求3所述的人体功能性关节旋转中心检测方法，其特征在于：步骤12包括：
    步骤121：建立局部坐标系；所述局部坐标系包括胸部坐标系，标记点坐标系，还包括上臂坐标系、前臂坐标系、大腿坐标系、小腿坐标系中的至少一种；
    步骤122：将标记点M1、M2、M3在绝对坐标系中的位置坐标转换为在胸部坐标系中的位置坐标；
    步骤123：计算局部坐标系之间的旋转矩阵以及在局部坐标系中的人体功能性关节旋转中心FCR的位置坐标；
    步骤124：将人体功能性关节旋转中心FCR在局部坐标系中的位置坐标通过旋转矩阵转换为在胸部坐标系中的位置坐标，再转换为在绝对坐标系中的坐标，进而得到人体功能性关节旋转中心FCR的检测结果。
  5. 如权利要求4所述的人体功能性关节旋转中心检测方法，其特征在于：针对肩关节FCR检测，采用的局部坐标系包括胸部坐标系、上臂坐标系；针对肘关节FCR检测，采用的局部坐标系包括胸部坐标系、上臂坐标系、前臂坐标系；针对胯关节FCR检测，采用的局部坐标系包括胸部坐标系、大腿坐标系；针对膝关节FCR检测，采用的局部坐标系包括胸部坐标系、大腿坐标系、小腿坐标系。
  6. 如权利要求5所述的人体功能性关节旋转中心检测方法，其特征在于：针对肩关节FCR检测，步骤12的具体流程为：
    (1)在定位运动中，将标记点M1、M2、M3在绝对坐标系中的位置坐标转换为在胸部坐标系中的位置坐标；
    (2)在胸部坐标系中，肩关节FCR的坐标是固定的，因此在胸部坐标系中的标记点集的中心
    Figure PCTCN2021080984-appb-100001
    到肩关节FCRP Jt和P Jt+dt的距离关系表示为：
    Figure PCTCN2021080984-appb-100002
    Figure PCTCN2021080984-appb-100003
    其中，
    Figure PCTCN2021080984-appb-100004
    是上臂的旋转矩阵，
    Figure PCTCN2021080984-appb-100005
    为上臂标记坐标系中从原点到肩关节FCR的常数向量，P Jt是肩关节FCR在t时刻在胸部坐标系中的坐标，P Jt+dt是肩关节FCR在t+dt时刻在胸部坐标系中的坐标，dt的取值范围为小于等于1秒；
    (3)联合式①和式②，得到线性方程：
    Figure PCTCN2021080984-appb-100006
    其中
    Figure PCTCN2021080984-appb-100007
    捕捉时刻0到时刻T的定位运动中，对式③进行积分为：
    Figure PCTCN2021080984-appb-100008
    其中
    Figure PCTCN2021080984-appb-100009
    Figure PCTCN2021080984-appb-100010
    r 1xt表示t时刻标记点M1在上臂坐标系中的X轴坐标值，其他符号的含义依此类推，n＝3；
    (4)根据式④，由最小二乘法确定
    Figure PCTCN2021080984-appb-100011
    (5)将
    Figure PCTCN2021080984-appb-100012
    通过旋转矩阵转换为在胸部坐标系中的位置坐标，再转换为在绝对坐标系中的坐标，进而得到肩关节FCR的检测结果。
  7. 一种人体功能性关节旋转中心定位分析方法，其特征在于：包括：
    步骤21：通过三维扫描获得人体的形态学参数；
    步骤22：根据人体形态学参数与人体关节之间的拟合关系，对人体关节进行定位分析；
    步骤23：对人体关节定位分析结果进行补偿。
    确定步骤22中所述的人体形态学参数与人体关节之间的拟合关系包括：
    步骤221：确定人体站立姿态下的关节位置坐标；
    步骤222：对人体形态学参数进行主成分分析，确定人体形态学参数N大主成分；
    步骤223：对人体形态学参数的N大主成分与步骤221中确定的人体站立姿态下的关节位置坐标分别进行拟合，得到拟合关系：
    Figure PCTCN2021080984-appb-100013
    其中，FCRix、FCRiy和FCRiz分别表示第i个关节的x、y和z轴坐标，a ix1、a ix2、…、a ixN、a iy1、a iy2、…、a iyN、a iz1、a iz2、…、a izN为拟合系数，PC1、PC2、…、PCN为人体形态学参数的N个主成分。
    步骤221中，对于肩关节、肘关节、胯关节、膝关节的位置坐标采用如权利要求1-6任一项 所述的人体功能性关节旋转中心检测方法确定。
  8. 如权利要求7所述的人体功能性关节旋转中心定位分析方法，其特征在于：步骤221中，对于肢体末端关节以及人体躯干关节，用骨性标志点的坐标表示关节的位置坐标。
  9. 如权利要求7所述的人体功能性关节旋转中心定位分析方法，其特征在于：步骤23中对人体关节定位分析结果进行补偿包括平移和旋转，所述平移包括：选定平移标准关节点；计算标准关节点的测量坐标值与定位坐标值之间的差值确定平移量；对所有定位的关节按照所述的平移量进行平移。
  10. 如权利要求9所述的人体功能性关节旋转中心定位分析方法，其特征在于：所述旋转包括：选定旋转标准关节点；计算平移后的手腕关节与平移前的手腕关节相对于过所述旋转标准关节点的高度轴的上肢旋转量；对平移后的上肢上的关节按照所述上肢旋转量进行旋转；所述旋转还包括：选定旋转标准关节点；计算平移后的脚踝关节与平移前的脚踝关节相对于过所述旋转标准关节点的高度轴的下肢旋转量；对平移后的下肢上的关节按照所述下肢旋转量进行旋转。
PCT/CN2021/080984 2020-12-02 2021-03-16 一种人体功能性关节旋转中心检测与定位分析方法 WO2022116411A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US17/764,544 US11707209B2 (en) 2020-12-02 2021-03-16 Detecting method and positioning analysis method of human functional joint rotation center

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202011391786.6A CN112545498B (zh) 2020-12-02 2020-12-02 一种人体功能性关节旋转中心检测与定位分析方法
CN202011391786.6 2020-12-02

Publications (1)

Publication Number Publication Date
WO2022116411A1 true WO2022116411A1 (zh) 2022-06-09

Family

ID=75047092

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/080984 WO2022116411A1 (zh) 2020-12-02 2021-03-16 一种人体功能性关节旋转中心检测与定位分析方法

Country Status (3)

Country Link
US (1) US11707209B2 (zh)
CN (1) CN112545498B (zh)
WO (1) WO2022116411A1 (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114469079B (zh) * 2022-01-29 2022-09-06 北京中科深智科技有限公司 一种利用LightHouse的身体关节测量方法
CN114565978B (zh) * 2022-04-28 2022-07-26 深圳市第二人民医院(深圳市转化医学研究院) 基于动作捕捉点云的关节旋转中心优化方法及设备

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1748642A (zh) * 2005-10-13 2006-03-22 上海交通大学 非侵入式人体手臂关节的测量方法
CN1969748A (zh) * 2006-11-29 2007-05-30 华中科技大学 一种基于单目视频的计算机辅助步态分析方法
JP4332669B2 (ja) * 2004-03-01 2009-09-16 独立行政法人科学技術振興機構 関節中心計測装置
CN102486816A (zh) * 2010-12-02 2012-06-06 三星电子株式会社 计算人体形状参数的装置和方法
JP2014117409A (ja) * 2012-12-14 2014-06-30 Kawasaki Heavy Ind Ltd 身体関節位置の計測方法および装置
CN107806837A (zh) * 2017-10-29 2018-03-16 北京工业大学 一种非侵入式腕关节轴线运动模型测量方法
CN108324282A (zh) * 2018-01-31 2018-07-27 北京工业大学 一种人体肩部盂肱关节旋转中心运动信息检测系统
CN110974241A (zh) * 2019-12-18 2020-04-10 上海理工大学 一种基于视觉的柔性外骨骼手指关节的运动轨迹测量装置

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH04294986A (ja) * 1991-03-22 1992-10-19 Sanyo Electric Co Ltd ロボットアームの長さ測定方法およびこれを用いた水平多関節ロボットの座標値補正方法
ATE409006T1 (de) * 2002-05-21 2008-10-15 Plus Orthopedics Ag Anordnung zur ermittlung funktionsbestimmender geometrischer grössen eines gelenkes eines wirbeltiers
CN108030496B (zh) * 2017-12-02 2021-03-16 北京工业大学 一种人体上肢肩部盂肱关节旋转中心与上臂抬升角耦合关系测量方法
CN109272488B (zh) * 2018-08-16 2021-08-20 深圳大学 一种人体髋关节的运动受力变化评估方法及装置
US11216074B2 (en) * 2020-03-13 2022-01-04 OnTracMD, LLC Motion classification user library

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4332669B2 (ja) * 2004-03-01 2009-09-16 独立行政法人科学技術振興機構 関節中心計測装置
CN1748642A (zh) * 2005-10-13 2006-03-22 上海交通大学 非侵入式人体手臂关节的测量方法
CN1969748A (zh) * 2006-11-29 2007-05-30 华中科技大学 一种基于单目视频的计算机辅助步态分析方法
CN102486816A (zh) * 2010-12-02 2012-06-06 三星电子株式会社 计算人体形状参数的装置和方法
JP2014117409A (ja) * 2012-12-14 2014-06-30 Kawasaki Heavy Ind Ltd 身体関節位置の計測方法および装置
CN107806837A (zh) * 2017-10-29 2018-03-16 北京工业大学 一种非侵入式腕关节轴线运动模型测量方法
CN108324282A (zh) * 2018-01-31 2018-07-27 北京工业大学 一种人体肩部盂肱关节旋转中心运动信息检测系统
CN110974241A (zh) * 2019-12-18 2020-04-10 上海理工大学 一种基于视觉的柔性外骨骼手指关节的运动轨迹测量装置

Also Published As

Publication number Publication date
CN112545498A (zh) 2021-03-26
CN112545498B (zh) 2021-11-19
US20220400981A1 (en) 2022-12-22
US11707209B2 (en) 2023-07-25

Similar Documents

Publication Publication Date Title
Manal et al. Comparison of surface mounted markers and attachment methods in estimating tibial rotations during walking: an in vivo study
Stagni et al. Quantification of soft tissue artefact in motion analysis by combining 3D fluoroscopy and stereophotogrammetry: a study on two subjects
Matsuki et al. In vivo 3-dimensional analysis of scapular kinematics: comparison of dominant and nondominant shoulders
Rettig et al. A new kinematic model of the upper extremity based on functional joint parameter determination for shoulder and elbow
Clément et al. Soft tissue artifact compensation in knee kinematics by multi-body optimization: Performance of subject-specific knee joint models
Stief et al. Reliability and accuracy in three-dimensional gait analysis: a comparison of two lower body protocols
WO2022116411A1 (zh) 一种人体功能性关节旋转中心检测与定位分析方法
Camomilla et al. An optimized protocol for hip joint centre determination using the functional method
Scheys et al. Calculating gait kinematics using MR-based kinematic models
WO2015162158A1 (en) Human motion tracking
Nair et al. A method to calculate the centre of the ankle joint: A comparison with the Vicon® Plug-in-Gait model
Kuo et al. Influence of soft tissue artifacts on the calculated kinematics and kinetics of total knee replacements during sit-to-stand
Barré et al. Soft tissue artifact distribution on lower limbs during treadmill gait: influence of skin markers' location on cluster design
Murakami et al. In vivo kinematics of healthy male knees during squat and golf swing using image-matching techniques
Groen et al. Sensitivity of the OLGA and VCM models to erroneous marker placement: Effects on 3D-gait kinematics
Cereatti et al. Hip joint centre location: an ex vivo study
Boser et al. Cluster-based upper body marker models for three-dimensional kinematic analysis: Comparison with an anatomical model and reliability analysis
Buczek et al. Implications of using hierarchical and six degree-of-freedom models for normal gait analyses
Adolphe et al. Center of Mass of Human's Body Segments.
Pedro et al. Concurrent validity of an inertial measurement system in tennis forehand drive
D'Isidoro et al. Effects of the soft tissue artefact on the hip joint kinematics during unrestricted activities of daily living
Hebert et al. A method of measuring three-dimensional scapular attitudes using the optotrak probing system
CN112617816B (zh) 一种基于运动学参数定位功能性肘关节旋转中心方法
WO2022110573A1 (zh) 基于刚性上臂模型的功能性肩关节旋转中心定位方法
Bakke et al. Shape-model scaled gait models can neglect segment markers without consequential change to inverse kinematics results

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21899455

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21899455

Country of ref document: EP

Kind code of ref document: A1