The adaptation of GDL motion recognition system to sport and rehabilitation techniques analysis.
The main novelty of this paper is presenting the adaptation of Gesture Description Language (GDL) methodology to sport and rehabilitation data analysis and classification. In this paper we showed that Lua language can be successfully used for adaptation of the GDL classifier to those tasks. The newl...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 6; pp. 1 - 10 |
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| Autores principales: | , |
| Formato: | computer program pictorial tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925356&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925356 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jun2016 vid: 40 iid: 6 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925356 115925356 115925356 10.1007/s10916-016-0493-6 115925356 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: The adaptation of GDL motion recognition system to sport and rehabilitation techniques analysis. aug: au: Hachaj, Tomasz Ogiela, Marek affil: Institute of Computer Science and Computer Methods, Pedagogical University of Krakow, 2 Podchorazych Ave 30-084 Krakow Poland sug: subj: Kinematics Motion Analysis Systems Sports Medicine Rehabilitation Programming Languages Time Series Funding Source Time Factors ab: The main novelty of this paper is presenting the adaptation of Gesture Description Language (GDL) methodology to sport and rehabilitation data analysis and classification. In this paper we showed that Lua language can be successfully used for adaptation of the GDL classifier to those tasks. The newly applied scripting language allows easily extension and integration of classifier with other software technologies and applications. The obtained execution speed allows using the methodology in the real-time motion capture data processing where capturing frequency differs from 100 Hz to even 500 Hz depending on number of features or classes to be calculated and recognized. Due to this fact the proposed methodology can be used to the high-end motion capture system. We anticipate that using novel, efficient and effective method will highly help both sport trainers and physiotherapist in they practice. The proposed approach can be directly applied to motion capture data kinematics analysis (evaluation of motion without regard to the forces that cause that motion). The ability to apply pattern recognition methods for GDL description can be utilized in virtual reality environment and used for sport training or rehabilitation treatment. pubtype: Academic Journal doctype: computer program pictorial tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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