{"title":"In-home Activity and Micro-motion Logging Using Mobile Robot with Kinect","authors":"Keita Nakahara, H. Yamaguchi, T. Higashino","doi":"10.1145/3004010.3004027","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a method for logging micro-motion of in-home daily activity based on the skeleton recognition of the elderly in their daily life. We believe that in near future, many types of mobile robots will be spread to general household, and our idea is to let such a home robot be equipped with a 3D-depth camera such as Microsoft Kinect to enable tracking and observation of the elderly people at any location, any time, from any angle at home. There are lots of furniture and other items at home, which often make hard to set fixed-point observation, but robots are flexible to move to the best position to acquire the motion logging. The collected micro-motion data can be used for early detection of mild cognitive impairment (MCI) or depression, both of which often affect the physical body ability. Our robot moves in the vicinity of the elderly and performs a joint detection from 3D depth information. Through the experiment in the real home, we could recognize the in-home activities and micro-motions with high accuracy.","PeriodicalId":406787,"journal":{"name":"Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Adjunct Proceedings of the 13th International Conference on Mobile and Ubiquitous Systems: Computing Networking and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3004010.3004027","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
In this paper, we propose a method for logging micro-motion of in-home daily activity based on the skeleton recognition of the elderly in their daily life. We believe that in near future, many types of mobile robots will be spread to general household, and our idea is to let such a home robot be equipped with a 3D-depth camera such as Microsoft Kinect to enable tracking and observation of the elderly people at any location, any time, from any angle at home. There are lots of furniture and other items at home, which often make hard to set fixed-point observation, but robots are flexible to move to the best position to acquire the motion logging. The collected micro-motion data can be used for early detection of mild cognitive impairment (MCI) or depression, both of which often affect the physical body ability. Our robot moves in the vicinity of the elderly and performs a joint detection from 3D depth information. Through the experiment in the real home, we could recognize the in-home activities and micro-motions with high accuracy.