| Summary: | 碩士 === 長庚大學 === 醫療機電工程研究所 === 98 === Preventing Falling down is an important issue for the aging society; therefore, the fall detection is crucial for the healthcare system. Fall signal is generally collected from a 3-axis accelerometer which is placed on the human’s chest, and the collected signal is further analyzed to develop the fall detection algorithms. Nevertheless, it is not easy to collect realistic fall signals because the experiments of falls may cause serious injuries. Therefore, most of collected fall signals are conservative and cannot completely represent the situations of actual falls. That means the volunteer may perform a slow fall when collecting the fall signal. Especially, it is hardly to collect the fall signals from high risk fall situations such as falls from stairs. Biped humanoid robot researches are fast increasing in recent years, because the torso structures of the biped humanoid robots is similar to the human beings. This thesis proposes a biped humanoid robot based fall scenario simulation system. The proposed fall scenario simulation system constructs the gait pattern libraries for the different fall scenarios which are similar to the falls of human beings. A 3-axis accelerometer is also placed on the chest of the biped humanoid robot to measure the fall signals. In order to verify the proposed approach, a motion capture system is employed in this study to measure the fall motions. At the same time, the fall motions collected from the motion capture system and the fall signals collected from the 3-axis accelerometer are synchronously recorded to verify the signal correlations between the biped humanoid robot and the human beings. Experiment results shows that the signal correlations between the biped humanoid robot and the human beings for typical forward, side and backward falls. Based on this correlation performance, the high risk fall signals such as falls from stairs and slip falls are collected from the biped humanoid robots only. Therefore, the proposed biped humanoid robot based fall scenario simulation system may effectively collect the fall signals for the further fall detection algorithm studies.
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