G. Goodfellow, J. Neasham, Ivor Rendulic, D. Nad, N. Mišković
{"title":"DiverNet -一个用于实时潜水员可视化的惯性传感器网络","authors":"G. Goodfellow, J. Neasham, Ivor Rendulic, D. Nad, N. Mišković","doi":"10.1109/SAS.2015.7133640","DOIUrl":null,"url":null,"abstract":"This paper describes the DiverNet system that allows real time reconstruction of diver's posture and its visualization using a virtual 3D model. DiverNet is a network consisting of 17 inertial sensors mounted on diver's body, enabling calculation of orientation of each body part. Based on the obtained data, diver posture can be visualized. In addition to that, DiverNet allows integration of additional sensors for measuring physiological parameters such as breathing rate. This is the first time such technology is used in the underwater. Obtained data will be used to increase diver safety by monitoring the diver in real time, as well as developing tools for understanding diver behaviour and automatically recognizing possible signs of trouble. The paper focuses on technical description of the developed system, as well as the software used for data analysis and visualization.","PeriodicalId":384041,"journal":{"name":"2015 IEEE Sensors Applications Symposium (SAS)","volume":"90 21","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"DiverNet — A network of inertial sensors for real time diver visualization\",\"authors\":\"G. Goodfellow, J. Neasham, Ivor Rendulic, D. Nad, N. Mišković\",\"doi\":\"10.1109/SAS.2015.7133640\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the DiverNet system that allows real time reconstruction of diver's posture and its visualization using a virtual 3D model. DiverNet is a network consisting of 17 inertial sensors mounted on diver's body, enabling calculation of orientation of each body part. Based on the obtained data, diver posture can be visualized. In addition to that, DiverNet allows integration of additional sensors for measuring physiological parameters such as breathing rate. This is the first time such technology is used in the underwater. Obtained data will be used to increase diver safety by monitoring the diver in real time, as well as developing tools for understanding diver behaviour and automatically recognizing possible signs of trouble. The paper focuses on technical description of the developed system, as well as the software used for data analysis and visualization.\",\"PeriodicalId\":384041,\"journal\":{\"name\":\"2015 IEEE Sensors Applications Symposium (SAS)\",\"volume\":\"90 21\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 IEEE Sensors Applications Symposium (SAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAS.2015.7133640\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Sensors Applications Symposium (SAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAS.2015.7133640","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
DiverNet — A network of inertial sensors for real time diver visualization
This paper describes the DiverNet system that allows real time reconstruction of diver's posture and its visualization using a virtual 3D model. DiverNet is a network consisting of 17 inertial sensors mounted on diver's body, enabling calculation of orientation of each body part. Based on the obtained data, diver posture can be visualized. In addition to that, DiverNet allows integration of additional sensors for measuring physiological parameters such as breathing rate. This is the first time such technology is used in the underwater. Obtained data will be used to increase diver safety by monitoring the diver in real time, as well as developing tools for understanding diver behaviour and automatically recognizing possible signs of trouble. The paper focuses on technical description of the developed system, as well as the software used for data analysis and visualization.