{"title":"帕金森病螺旋分析的Android应用程序","authors":"D. Surangsrirat, C. Thanawattano","doi":"10.1109/SECON.2012.6196943","DOIUrl":null,"url":null,"abstract":"The paper presents an application for spiral analysis in Parkinson's Disease (PD). PD is one of the most common degenerative disorders of the central nervous system that affects elderly. Four cardinal symptoms of the disease are tremor, rigidity, slowness of movement, and postural instability. The current diagnosis is based on clinical observation which relies on skills and experiences of a trained specialist. Thus, an additional method is desirable to help in the diagnosis process and possibly improve the detection of early PD as well as the measurement of disease severity. Many studies have reported that the spiral analysis may be useful in the diagnosis of motor dysfunction in PD patient. We therefore implement a mobile, safe, easy to use, inexpensive, and online application for detection of movement disorders with a comprehensive test analysis according to the indices from Archimedean and octagon spirals tracing tasks. We introduce the octagon tracing task along with the conventional Archimedean spiral task because a shape tracing task with clear sequential components may increase a likelihood of detecting tremors and other cardinal features of PD. A widely used Android mobile operating system, the fastest markets share growth among smartphone platforms, is chosen as our development platform. We also show that the preliminary results of selected indices in the application could potentially be used to distinguish between PD patient and healthy control.","PeriodicalId":187091,"journal":{"name":"2012 Proceedings of IEEE Southeastcon","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"Android application for spiral analysis in Parkinson's Disease\",\"authors\":\"D. Surangsrirat, C. Thanawattano\",\"doi\":\"10.1109/SECON.2012.6196943\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper presents an application for spiral analysis in Parkinson's Disease (PD). PD is one of the most common degenerative disorders of the central nervous system that affects elderly. Four cardinal symptoms of the disease are tremor, rigidity, slowness of movement, and postural instability. The current diagnosis is based on clinical observation which relies on skills and experiences of a trained specialist. Thus, an additional method is desirable to help in the diagnosis process and possibly improve the detection of early PD as well as the measurement of disease severity. Many studies have reported that the spiral analysis may be useful in the diagnosis of motor dysfunction in PD patient. We therefore implement a mobile, safe, easy to use, inexpensive, and online application for detection of movement disorders with a comprehensive test analysis according to the indices from Archimedean and octagon spirals tracing tasks. We introduce the octagon tracing task along with the conventional Archimedean spiral task because a shape tracing task with clear sequential components may increase a likelihood of detecting tremors and other cardinal features of PD. A widely used Android mobile operating system, the fastest markets share growth among smartphone platforms, is chosen as our development platform. We also show that the preliminary results of selected indices in the application could potentially be used to distinguish between PD patient and healthy control.\",\"PeriodicalId\":187091,\"journal\":{\"name\":\"2012 Proceedings of IEEE Southeastcon\",\"volume\":\"93 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Proceedings of IEEE Southeastcon\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.2012.6196943\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Proceedings of IEEE Southeastcon","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2012.6196943","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Android application for spiral analysis in Parkinson's Disease
The paper presents an application for spiral analysis in Parkinson's Disease (PD). PD is one of the most common degenerative disorders of the central nervous system that affects elderly. Four cardinal symptoms of the disease are tremor, rigidity, slowness of movement, and postural instability. The current diagnosis is based on clinical observation which relies on skills and experiences of a trained specialist. Thus, an additional method is desirable to help in the diagnosis process and possibly improve the detection of early PD as well as the measurement of disease severity. Many studies have reported that the spiral analysis may be useful in the diagnosis of motor dysfunction in PD patient. We therefore implement a mobile, safe, easy to use, inexpensive, and online application for detection of movement disorders with a comprehensive test analysis according to the indices from Archimedean and octagon spirals tracing tasks. We introduce the octagon tracing task along with the conventional Archimedean spiral task because a shape tracing task with clear sequential components may increase a likelihood of detecting tremors and other cardinal features of PD. A widely used Android mobile operating system, the fastest markets share growth among smartphone platforms, is chosen as our development platform. We also show that the preliminary results of selected indices in the application could potentially be used to distinguish between PD patient and healthy control.