E. Martín-González, Rodrigo de Luis García, J. P. Casaseca-de-la-Higuera, J. R. Leiza, J. Andrés-de-Llano, C. Alberola-López
{"title":"Mapping Raw Acceleration Data on ActiGraph Counts: A Machine Learning Approach","authors":"E. Martín-González, Rodrigo de Luis García, J. P. Casaseca-de-la-Higuera, J. R. Leiza, J. Andrés-de-Llano, C. Alberola-López","doi":"10.1145/3284179.3284260","DOIUrl":null,"url":null,"abstract":"A method for mapping actimetry data between two platforms has been carried out; one platform is the CE and FDA approved ActiGraph wGT3X-BT, valid in clinical diagnosis, and the second one is Microsoft Band 2 Smartband, available for the general public. The method consists of a regression performed using machine learning technique, specifically, different configurations of neural networks have been tested. Access to the data has been achieved by means of an in-house mobile application.","PeriodicalId":370465,"journal":{"name":"Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3284179.3284260","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A method for mapping actimetry data between two platforms has been carried out; one platform is the CE and FDA approved ActiGraph wGT3X-BT, valid in clinical diagnosis, and the second one is Microsoft Band 2 Smartband, available for the general public. The method consists of a regression performed using machine learning technique, specifically, different configurations of neural networks have been tested. Access to the data has been achieved by means of an in-house mobile application.
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