# An Image-Based Fall Detection System for the Elderly
## 5 Experiment
### Test Cases: Common Situation  
For the common situation, there are three tests. There are 23 cases in each test, including 9 non-fall cases and 14 fall cases. Case 1 to Case 4 in the non-fall cases are walking cases to verify that IFADS does not detect a fall while the tester is walking. Figure 6 shows the illustration of the walking cases. Case 1 and Case 2 both show that the tester walks across behind the chair, and the tester is far from the chair in Case 1 and near the chair in Case 2. Case 3 and Case 4 are both situations where the tester walks across in front of the chair, and the tester is far from the chair in Case 3 and near the chair in Case 4. On the other hand, Case 5 to Case 9 in the non-fall cases are sitting cases to verify that IFADS does not detect a fall while the tester is sitting with any rotation angle. Figure 7 shows the illustration of the sitting cases. Cases 5, 6, and 7 are the situations where the tester faces the chair, walks to the chair, sits, and then stands up and walks away. The difference between these cases is that the tester has his/her back to the chair, faces the camera, and turns his/her back to the camera while sitting in Cases 5, 6, and 7, respectively. Case 8 is the situation where the tester walks to the chair with his/her back to the camera, sits, and then stands up and walks away. Case 9 is the situation where the tester walks to the chair while facing the camera, sits, and then stands up and walks away. From Case 10 to Case 23, there are 14 fall cases. Figure 8 shows the illustration of the fall cases. From Case 10 to Case 16, the tester falls when he/she tries to sit on the chair, and from Case 17 to Case 23, the tester falls when he/she tries to stand up from the chair. The difference between these cases is that the rotation angle of the fall is different. Figure 9 shows the different rotation angles of the fall. The purpose of these fall cases is to verify that IFADS can detect falls with different rotation angles and different postures. Figure 6: An illustration of the walking cases. Figure 8: An illustration of the cases with a fall. Figure 9: Different rotation angles of falls. For the experiment, first, we mark the chair purple. As Table 2 shows, we mark the testers in different colors to distinguish between the different postures of the testers. Figure 10 shows the remaining results of the common situation. Since the tester usually walks across (in front of or behind) the chair instead of sitting on the chair when he/she finds that there is a chair, from Case 1 to Case 4 in Figure 10, we test when the tester walks across (in front of or behind) the chair and does not sit down from a different perspective. In addition, the tester walks a different distance from the tester to the chair and takes a different route. As the tester's height does not change significantly within 1.5 s, IFADS does not detect a fall. From Case 5 to Case 9, we test when the tester walks, sits on the chair, stands up from the chair, and leaves with a different rotation angle of sitting. Since the top of the tester remains higher than the top of the chair, IFADS does not detect a fall. From Case 5 to Case 8, IFADS accurately recognizes the posture of the tester as sitting. IFADS recognizes the posture of the tester as in progress in Case 9, because the tester does not sit at the center of the chair's faceplate. However, if an elderly person sits at the end of a chair, he/she may slide out from the chair easily. Then, we test when the tester falls off the chair while sitting with a different rotation angle of the fall from Case 10 to Case 16, and test when the tester falls off the chair while standing up from the chair in other cases. IFADS detects the fall accurately in these cases. In Cases 10, 21, 22, and 23, IFADS cannot detect the tester, because the falling tester's human features disappear from the frame, but IFADS can still detect the fall because of the state tracking.