Electromyography analysis by classification complexity estimation - A study of the complexity of myoelectric pattern recognition
| dc.contributor.author | Nilsson, Niclas | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för signaler och system | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Signals and Systems | en |
| dc.date.accessioned | 2019-07-03T14:24:02Z | |
| dc.date.available | 2019-07-03T14:24:02Z | |
| dc.date.issued | 2016 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/245722 | |
| dc.language.iso | eng | |
| dc.relation.ispartofseries | Ex - Institutionen för signaler och system, Chalmers tekniska högskola : EX078/2016 | |
| dc.setspec.uppsok | Technology | |
| dc.subject | Elektroteknik och elektronik | |
| dc.subject | Electrical Engineering, Electronic Engineering, Information Engineering | |
| dc.title | Electromyography analysis by classification complexity estimation - A study of the complexity of myoelectric pattern recognition | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Biomedical engineering (MPBME), MSc |
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