{"title":"借鉴健康踝关节示范改进康复机器人轨迹再生","authors":"Yunkai Wang, Qingsong Ai, Ling Ai, Quan Liu, Jiwei Hu, Zude Zhou","doi":"10.1145/3440840.3440852","DOIUrl":null,"url":null,"abstract":"The prevalence of ankle injuries in daily life has prompted the widespread application of rehabilitation robots. One of the important factors affecting robot-assisted ankle rehabilitation is the training trajectory which is usually regenerated from ankle movements. The traditional trajectory regeneration method is not suitable for the clinically recommended periodic ankle movements. In this paper, an improved robot trajectory regeneration method based on the individual characteristics is proposed to provide training reference trajectory for rehabilitation robots. This method extracts sample characteristics from the demonstration of the healthy ankle and reconstructs the sample space. Based on Learning from Demonstration (LfD) technology, the reference trajectory is regenerated for the rehabilitation of the injured ankle. The analysis of statistics and the regeneration of spatial features are performed to prove that this proposed method can regenerate the rehabilitation reference trajectory by learning from the healthy ankle demonstration.","PeriodicalId":273859,"journal":{"name":"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improved Rehabilitation Robot Trajectory Regeneration by Learning from the Healthy Ankle Demonstration\",\"authors\":\"Yunkai Wang, Qingsong Ai, Ling Ai, Quan Liu, Jiwei Hu, Zude Zhou\",\"doi\":\"10.1145/3440840.3440852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The prevalence of ankle injuries in daily life has prompted the widespread application of rehabilitation robots. One of the important factors affecting robot-assisted ankle rehabilitation is the training trajectory which is usually regenerated from ankle movements. The traditional trajectory regeneration method is not suitable for the clinically recommended periodic ankle movements. In this paper, an improved robot trajectory regeneration method based on the individual characteristics is proposed to provide training reference trajectory for rehabilitation robots. This method extracts sample characteristics from the demonstration of the healthy ankle and reconstructs the sample space. Based on Learning from Demonstration (LfD) technology, the reference trajectory is regenerated for the rehabilitation of the injured ankle. The analysis of statistics and the regeneration of spatial features are performed to prove that this proposed method can regenerate the rehabilitation reference trajectory by learning from the healthy ankle demonstration.\",\"PeriodicalId\":273859,\"journal\":{\"name\":\"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3440840.3440852\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 3rd International Conference on Computational Intelligence and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3440840.3440852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
日常生活中踝关节损伤的普遍存在,促使了康复机器人的广泛应用。影响机器人辅助踝关节康复的重要因素之一是训练轨迹,而训练轨迹通常是由踝关节运动生成的。传统的轨迹再生方法不适合临床推荐的周期性踝关节运动。本文提出了一种改进的基于个体特征的机器人轨迹再生方法,为康复机器人提供训练参考轨迹。该方法从健康踝关节的演示中提取样本特征,重构样本空间。基于LfD (Learning from Demonstration)技术,再生踝关节损伤康复的参考轨迹。通过统计分析和空间特征的再生,证明了该方法可以通过学习健康踝关节的示范来再生康复参考轨迹。
Improved Rehabilitation Robot Trajectory Regeneration by Learning from the Healthy Ankle Demonstration
The prevalence of ankle injuries in daily life has prompted the widespread application of rehabilitation robots. One of the important factors affecting robot-assisted ankle rehabilitation is the training trajectory which is usually regenerated from ankle movements. The traditional trajectory regeneration method is not suitable for the clinically recommended periodic ankle movements. In this paper, an improved robot trajectory regeneration method based on the individual characteristics is proposed to provide training reference trajectory for rehabilitation robots. This method extracts sample characteristics from the demonstration of the healthy ankle and reconstructs the sample space. Based on Learning from Demonstration (LfD) technology, the reference trajectory is regenerated for the rehabilitation of the injured ankle. The analysis of statistics and the regeneration of spatial features are performed to prove that this proposed method can regenerate the rehabilitation reference trajectory by learning from the healthy ankle demonstration.