Online motion recognition using an accelerometer in a mobile device
This paper introduces a new method to implement a motion recognition process using a mobile phone fitted with an accelerometer. The data collected from the accelerometer are interpreted by means of a statistical study and machine learning algorithms in order to obtain a classification function. Then...
| Authors: | , , , |
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| Format: | article |
| Publication Date: | 2011 |
| Country: | España |
| Institution: | Universitat Politècnica de Catalunya (UPC) |
| Repository: | UPCommons. Portal del coneixement obert de la UPC |
| Language: | English |
| OAI Identifier: | oai:upcommons.upc.edu:2117/13325 |
| Online Access: | https://hdl.handle.net/2117/13325 https://dx.doi.org/10.1016/j.eswa.2011.08.098 |
| Access Level: | Open access |
| Keyword: | Support vector machines Supervised learning (Machine learning) Learning classifier systems Reconeixement de formes (Informàtica) Acceleròmetres Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes |
| Summary: | This paper introduces a new method to implement a motion recognition process using a mobile phone fitted with an accelerometer. The data collected from the accelerometer are interpreted by means of a statistical study and machine learning algorithms in order to obtain a classification function. Then, that function is implemented in a mobile phone and online experiments are carried out. Experimental results show that this approach can be used to effectively recognize different human activities with a high-level accuracy. |
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