JP4595104B2 - Objective severity assessment method for movement disorders - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention is a method for evaluating the severity of a disease whose main symptom is movement disorder such as Parkinson's disease or Huntington's disease, or how much medical practice such as drug administration, surgery or rehabilitation has affected the improvement of movement disorder. Therefore, the present invention relates to a data collection method and an evaluation method for the severity of movement disorders.
[0002]
[Prior art]
Conventionally, the method for evaluating the severity of movement disorder is a subjective evaluation method based on the observation of the therapist, or a scale evaluation method using Unified Parkinson's Disseating Rating Scale, Unified Huntington's Disseating Scale, etc. It was the center. Each of these methods is an evaluation method based on the subjectivity that the therapist performs based on visual information, and is an evaluation method with low objectivity that does not depend on physical measurement data.
[0003]
[Problems to be solved by the invention]
As described above, the conventional methods for assessing the severity of movement disorders require careful examination in terms of objectivity. The present invention has been made in order to eliminate the disadvantages of the conventional evaluation method, and to make the data objective, so that anyone can see the same data in the same way. The objective is to enable an objective assessment of severity based on data.
[0004]
[Means for Solving the Problems]
In order to solve the above-mentioned problems, the invention of claim 1 uses a material having low reflectivity with respect to visible light and infrared light such as cloth as a background, and one of a front surface, a ceiling, and two side surfaces. In the movement disorder test box, which is characterized by being open, exercise to open and close the palm using the part of the body as the evaluation target part by the evaluation target, and to unrotate the upper arm Test exercises such as exercise, quick touch of the target with the tip of the index finger, posture to keep the hand quiet, movement to raise and lower the lower limbs, etc. are performed using a video camera from the front of the movement disorder test box The captured moving image is converted into a digital value and input to a computer, and a frame between adjacent frames or a fixed interval for each frame of the digital moving image is input. The difference processing between frames separated by the number of frames is performed, and the luminance difference values of all detected pixels or blocks are summed for each processing, or the total number of pixels or blocks having a difference value of a certain value or more is 1 This is obtained as the pseudo momentum (pseudo momentum) of the evaluation target part at the time of measurement, and the obtained pseudo momentum data is subjected to orthogonal transformation such as Fourier transform and wavelet transform to obtain the spectrum of the frequency. Objective severity assessment of movement disorders characterized by judging the severity of movement disorders based on deviations in peak positions and differences in intensity at the maximum peak compared to model spectra based on healthy person data obtained by the method of Is the method.
[0005]
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the present invention will be described with reference to the drawings.
FIG. 1 is an explanatory diagram showing the system configuration of a movement disorder test and evaluation according to the present invention. In FIG. 1, a part (evaluation target part) 8 of a subject's body is characterized by a background 71 using a material that is non-reflective or low-reflective with respect to visible light or infrared light. Put in the movement disorder test box 7, for example, exercise to open and close the palm, exercise to unrotate the upper arm, exercise to touch the target quickly with the tip of the index finger, posture to keep the hand quiet, exercise to raise and lower the leg Such a test exercise is performed, and this is photographed by the video camera 1 and input to an analysis system including a digital video recorder 2, an image input device 3, a video monitor 4, a computer 5, and a monitor 6 for image processing and data. It is configured to be processed.
[0006]
In this embodiment, first, the test target part 8 is caused to perform the test movement for 15 seconds inside the movement disorder test box 7, and this state is photographed by the video camera 1 and recorded by the digital video tape recorder 2. . In addition, before the evaluation target region 8 is put into the movement disorder test box 7, a background 71 in a state where there is no evaluation target person is previously photographed by the video camera 1 and recorded by the digital video tape recorder 2. deep.
[0007]
The digital video image recorded by the above method is slowly reproduced by the digital video tape recorder 2 and input to the computer 5 through the image input device 3 to perform digital image processing and subsequent data processing. FIG. 2 is a flowchart showing the flow of image processing and subsequent data processing performed by the computer. The input data is first subjected to background difference P1 or frame difference P2 for calculating the difference from the background image in the absence of the evaluation target person, and the tip position detection is performed for the data on which the background difference P1 has been performed. P11 and barycentric position detection P12 are performed. The data detected by these are arranged in a two-dimensional space, and a motion trajectory is drawn P13. Next, for the data on which the frame difference P2 has been performed, the pseudo momentum calculation P21 is performed by summing the difference amounts in all the pixel portions obtained in one frame difference calculation, and this is further displayed on the time axis. A Fourier transform P22 is performed on the arranged data, and a spectrum is drawn P23.
[0008]
The image processing performed by the computer 5 will be described as follows.
(1) Background difference P1: A luminance value difference for each pixel or each block between the background image input in advance and each frame of the image related to the motion of the evaluation target part is performed.
(2) Frame difference P2: A luminance value difference is calculated for each pixel or block between two consecutive frames of an image related to the motion of the evaluation target site or between frames at a fixed time interval.
(3) Tip position detection P11: Among the evaluation target parts in the image detected by the background difference, the tip part in the movement direction is detected and expressed in two dimensions of x and y.
(4) Barycentric position detection P12: The positions of all pixels or blocks representing the evaluation target part in the image detected by the background difference are expressed in two dimensions of x and y, and the average of these is obtained.
(5) Pseudo-momentum calculation P21: A value obtained by adding the luminance difference values of all pixels or blocks detected by the frame difference for each process, or the total number of pixels or blocks having a difference value equal to or greater than a certain value at the time of measurement The pseudo momentum at.
[0009]
FIG. 3 is an explanatory diagram of the trajectory data analysis. In the severity diagnosis based on the motion trajectory data D1 of the evaluation target part, the deviation area D3 from the model curve D2 created using a considerable number of healthy subjects is calculated, and the severity increases as the area size increases. And evaluate.
[0010]
FIG. 4 is an explanatory diagram of spectrum data analysis. Severity diagnosis based on the spectrum D10 obtained by Fourier transform from the pseudo momentum of the evaluation target site is performed with a peak position deviation D30 from the model spectrum D20 created using a considerable number of healthy subjects, and a difference in intensity D40 at the maximum peak. Each of these is determined, and the greater the size, the higher the severity.
[0011]
[Other Embodiments]
In the embodiment shown in FIG. 1 and FIG. 2, a general embodiment on the assumption that visible light is used is shown, but an infrared camera may be used as the video camera shown in FIG. In this case, the P1 background difference process described in FIG. 2 can be omitted.
[0012]
【The invention's effect】
As described above, according to the present invention, since the degree of movement disorder can be expressed as physical data, it is possible to make the data objective and to perform objective severity evaluation using the data. It becomes possible.
[Brief description of the drawings]
FIG. 1 is an explanatory diagram showing a system configuration of a movement disorder test and evaluation according to the present invention. FIG. 2 is a flowchart showing a flow of image processing performed by a computer and subsequent data processing. FIG. [Fig. 4] Explanatory diagram about spectral data analysis [Explanation of symbols]
DESCRIPTION OF SYMBOLS 1 Video camera 2 Digital video recorder 3 Image input device 4 Video monitor 5 Computer 6 Monitor 7 Movement disorder test box 8 Part of the body of the person to be evaluated (target part to be evaluated)
71 Background P1 Using Low Reflective Material Background Difference P2 Frame Difference P11 Tip Position Detection P12 Center of Gravity Position Detection P13 Motion Trajectory P21 Pseudo Momentum Calculation P22 Fourier Transform P23 Spectrum Drawing D1 Trajectory Data D2 Model Curve D3 Deviation Area D10 Spectrum Data D20 model power spectrum D30 peak position deviation D40 intensity difference

Claims (1)

  In a movement disorder test box characterized by using a material that is low-reflective with respect to visible light or infrared light such as cloth as a background, and having one of the front and ceiling and the two side surfaces open, The subject to be evaluated uses a part of the body as the part to be evaluated, exercises to open and close the palm, exercise to unrotate the upper arm, exercise to touch the target quickly with the tip of the index finger, and quietly hold the hand A test motion such as a posture to be placed and a motion of raising and lowering a lower limb is performed, and the state of the test motion is photographed from the front of the movement disorder test box using a video camera, and the photographed moving image is converted into a digital value to be a computer , And perform differential processing between adjacent frames for each frame of this digital moving image or between frames separated by a fixed number of frames. The value of the sum of the luminance difference values of all the pixels or blocks for each process, or the total number of pixels or blocks having a difference value equal to or greater than a certain value, (Momentum) is obtained, and the obtained pseudo-momentum data is subjected to orthogonal transform such as Fourier transform and wavelet transform to obtain the frequency spectrum, which is compared with the model spectrum obtained from the normal data obtained in the same way in advance. An objective severity evaluation method for movement disorders, characterized in that the severity of movement disorders is determined based on a shift in peak position and a difference in strength at a maximum peak.

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