JPH11296651A - Automation method for behavior observation of experimental animal - Google Patents

Abstract

PROBLEM TO BE SOLVED: To automate the behavior observation of an experimental animal, to shorten required time and to provide data with objectivity. SOLUTION: The behavior of a rat 7 inside an open field 6 is photographed by a video camera 1 and the behavior of the rat 7 is classified into six behavior items by an observer who observes the behavior of the rat 7 in photographed VTR images. Image parameters composed of seven items are extracted by image processing digital images for which the VTR images are fetched to a computer 5, the image parameters for the respective behavior items judged by the observer are compared and algorithm for judging the behavior of the rat 7 is prepared.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to an automatic method for observing the behavior of an experimental animal, which is effective for evaluating the efficacy of a drug.

[0002]

2. Description of the Related Art In conventional behavioral observation of experimental animals, observation results are obtained based on the subjectivity of the observer. Therefore, observation by the same observer is repeated twice to obtain accurate results. Observation results sometimes did not match even for the same person. In addition, in order to improve the objectivity of the observation result by a plurality of observers, the observation is performed after providing a training period in advance in order to match the criteria, but the observation result may still not match.

[0003]

As described above, in the conventional behavior observation method, the time required for observation is long, and the observation results sometimes do not match. Had to be considered.
SUMMARY OF THE INVENTION The present invention has been made to solve the above-mentioned drawbacks of the conventional behavior observation method, and aims to shorten the behavior observation time and provide data with objectivity.

[0004]

The behavior of an experimental animal in an open field is photographed by a video camera for a predetermined time and recorded as a VTR image, and the behavior of the experimental animal in the VTR image is observed to be included in a plurality of behavior items. In addition to the classification, the computer inputs the VTR image as a digital image and performs digital image processing to extract image parameters used for determining the behavior of the experimental animal. Next, the values of the image parameters for each action item determined by the observer are compared, an algorithm for action determination is created and stored in a computer, and the image of the experimental animal to be observed is obtained from the video camera. Observation results can be automatically obtained by acquiring the image parameters into a computer, applying an action determination algorithm stored in the computer to obtain image parameters.

[0005]

Embodiments of the present invention will be described with reference to the drawings. FIG. 1 is an explanatory diagram showing a configuration of a behavior observation system for experimental animals according to the present invention. In FIG.
The observation target rat 7 is placed in a square (115 × 115 cm) open field 6, and the behavior of the rat 7 is photographed by the video camera 1 provided above the open field 6, and the photographed VTR image is recorded on the video tape recorder 2.
It is configured to be input to a behavior observation system including an image input / output device 3, a video monitor 4, and a computer 5 and to be subjected to image processing.

In this embodiment, the rat 7 is left in the open field 6 for 10 minutes, photographed by the video camera 1, and an observer observes the behavior using the VTR image. The behavior of rat 7 that occurs is categorized. Classified action items are L
ocomotion (moving activity), Grooming (grooming), Stre
ching (elongation), Sniffing (sniffing), Rearing (hind leg standing)
And Immobility (immobility), which are determined by the time sample method every second, and one action occurs in one second. The action items are appropriately changed depending on the type of the experimental animal to be observed.

[0007] The above-mentioned VTR image is input as a digital image to a pyramid vision system (PVS) manufactured by SENSAR, and image processing including image difference method, binarization method, elliptic approximation, and centroid extraction is performed to set image parameters. Extracted and used for action determination. Image parameter is 7
It consists of items, the breakdown of which is as follows. (1) Area: The area of the rat captured on the image. (2) Long axis length: Long axis length of the ellipse when the rat is approximated by an ellipse. (3) Movement of the center of gravity: Movement of the rat's center of gravity. (4) Straightness : The number of processed images in which the rat's center of gravity goes straight. (5) Rotation: The size of the angle at which the long axis of the rat is rotated. (6) Total difference: The total change in brightness between two consecutive frames (7) Partial difference: The amount of change in the luminance value near both ends of the long axis when the rat is approximated by an ellipse

The pyramid vision system (P
FIG. 3 shows a flowchart of the image processing by VS).
In FIG. 3, the flow of processing time for each frame in the VTR image is displayed in the vertical axis direction, and each frame is displayed in the horizontal axis direction in order from the left. In the first frame, first, the target image is fetched (S101), the background image is fetched (S100), and the difference processing between the target image and the background image (S102) is performed to remove noise (S103). It is created (S104). Similarly, the second
Of the target image in the frame (S20)
1), the background image is captured (S100), the difference processing between the target image and the background image (S202), the noise removal (S100)
203), a background erased image is created (S204). First
Background erased image (S
104 and S204) is performed (S105),
The total difference amount measurement (S106) is performed, and further the partial difference amount measurement (S107) is performed.

Next, the area of the target image is measured (S108) from the background erased image (S104) in the first frame, and the ellipse approximation (S109) and the center of gravity (S11) are performed.
Perform 0). Based on the ellipse approximation (S109), the long axis length measurement (S112) and the short axis length measurement (S113) of the target image are performed. Similarly, in the second frame, the area measurement (S20) is performed from the background erased image (S204).
8), ellipse approximation (S209), and centroid measurement (S210). Based on the center-of-gravity measurement of the first frame (S110) and the center-of-gravity measurement of the second frame (S210), the amount of movement of the center of gravity between frames (S111) is measured. Further, based on the ellipse approximation of the first frame (S109) and the ellipse approximation of the second frame (S209), the rotation between the frames is measured (S114) and the straightness is measured (S115). In the same manner, image processing is performed on the third and subsequent frames to determine seven image parameters used for action determination.

Based on the seven image parameters described above, the values of the image parameters for each of the six action items determined by the observer are compared, and an algorithm for action determination is created using the flowchart shown in FIG. . In FIG. 2, the straightness is examined first (S1). If the straightness value is larger than a predetermined value, it is determined to be Locomotion (moving activity). If the straightness is smaller than the predetermined value, the partial difference is examined. (S2) If the partial difference amount is larger than a predetermined value, the value of the major axis length is further examined (S3). If the major axis length is longer than the predetermined value, the action is determined to be Streching (elongation), and
If it is shorter, it is judged as "Rearing". Next, when the partial difference amount is smaller than the predetermined value, the total difference amount, the center-of-gravity shift amount, and the rotation property are examined (S4, S5, S5).
S6) If all the values are less than or less than the predetermined value, it is determined that the action is Immobility (immobility), and whether any of the total difference amount, the center of gravity movement amount, and the rotation property is larger than the predetermined value. Or, if it is large, consider the area further (S
7) If the area is larger than the predetermined value, the action is Sniffin
In addition to determining that the action is g (sniffing), if the action is smaller than the predetermined value, the action is determined to be grooming. The algorithm for action determination created by the above method is stored in a computer.

An image of the rat 7 to be observed is taken from the video camera 1 into the computer 5 to obtain image parameters of the image, and an action determination algorithm stored in advance in the computer is applied. Desired. If the experimental animal to be observed is not a rat, it is necessary to create a different algorithm for behavior determination, but it can be easily created by applying the image parameter and algorithm creation method described above. .

[0012]

As described above, according to the method for automatically observing the behavior of an experimental animal according to the present invention, the time required for observing the behavior of the experimental animal can be shortened, and the data can be objectively evaluated. It is particularly effective for such applications.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram showing a configuration of a behavior observation system for experimental animals according to the present invention.

FIG. 2 is an algorithm for determining an action according to the present invention.

FIG. 3 is a flowchart of image processing.

[Explanation of symbols]

 Reference Signs List 1 video camera 2 video tape recorder 3 image input / output device 4 video monitor 5 computer 6 open field 7 rat

 ──────────────────────────────────────────────────続 き Continued on the front page (72) Inventor Akira Shimizu 3-5-302-202 Takezono, Tsukuba City, Ibaraki Prefecture (72) Inventor Yasuhiro Yoshikawa 3-1-6 Shinmachi, Hoya City, Tokyo (72) Inventor Jun Makino Shiro 4-1 Inari-mae, Tsukuba City, Ibaraki Prefecture (72) Inventor Keiji Terao 5-718-1 Matsushiro, Tsukuba City, Ibaraki Prefecture (72) Inventor Nao Sankai 2-701-202, Azuma, Tsuzuba City, Ibaraki Prefecture (72) Inventor Koyama Takamasa 301 Christie Mejiro 3-20-4 Mejiro, Toshima-ku, Tokyo (72) Inventor Takeshi Hasegawa 1-9-9 Motohongo-cho, Hachioji-shi, Tokyo Chuo Denshi Co., Ltd.

Claims (2)

[Claims] 1. The behavior of an experimental animal in an open field is photographed by a video camera, and the behavior of the experimental animal is classified into a plurality of behavior items by an observer who observes the behavior of the experimental animal in the photographed VTR image. The VTR image is input to a computer as a digital image, and the digital image is subjected to image processing including an image difference method, a binarization method, an ellipse approximation, and a centroid extraction, to extract image parameters, and each image determined by an observer. Comparing the values of the image parameters for each action item, creating an algorithm that is a criterion for determining the behavior of the experimental animal, storing it in a computer, and capturing the image of the experimental animal to be observed from the video camera to the computer. Obtain the parameters and apply the stored behavior judgment algorithm to automatically observe Experimental automated method of animal behavior observation, characterized in that has be obtained. 2. An algorithm for determining an action using an image parameter, wherein when the straightness is greater than a predetermined value, the action is
Locomotion (moving activity) is determined, and if the straightness is smaller than a predetermined value, the amount of partial difference is examined.
If the partial difference amount is larger than the predetermined value, further examine the value of the long axis length, and if the long axis length is longer than the predetermined value, the action is Strech.
ing (elongation), and if it is short, it is determined to be Rearing (hind limb standing). Further, if the partial difference is smaller than a predetermined value, the total difference, the center-of-gravity shift, and the rotation are examined. If all the values are less than or less than a predetermined value, the action is determined to be Immobility, and any of the total difference amount, the center of gravity shift amount, and the rotation property is greater than a predetermined value or If it is large, consider the area further,
When the area is larger than a predetermined value, the action is determined to be sniffing (sniffing), and when the area is smaller than the predetermined value, the action is determined to be grooming (grooming). The automated method for observing behavior of an experimental animal according to claim 1.