Estimation of continuous elbow joint movement based on human physiological structure.
Objective: Human intention recognition technology plays a vital role in the application of robotic exoskeletons and powered exoskeletons. However, the precise estimation of the continuous motion of each joint represents a major challenge. In the current study, we present a method for estimating cont...
| Publicado en: | BioMedical Engineering OnLine Vol. 18; no. 1 |
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| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
BioMed Central
3/20/2019
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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=135440072&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 135440072 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1475925X 1CGX jtl: BioMedical Engineering OnLine issn: 1475925X maglogo: N pubinfo: dt: 3/20/2019 vid: 18 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 135440072 135440072 NLM30894195 10.1186/s12938-019-0653-2 NLM30894195 135440072 ppct: 1 formats: tig: atl: Estimation of continuous elbow joint movement based on human physiological structure. aug: au: Li, Kexiang Zhang, Jianhua Liu, Xuan Zhang, Minglu affil: School of Mechanical Engineering, Hebei University of Technology, 300130, Tianjin, China sug: subj: Movement Elbow Joint Physiology Models, Biological Muscles Physiology Electromyography Tendons Physiology Female Kinematics Sensitivity and Specificity Weight-Bearing Male Adult Adult: 19-44 years Female Male ab: Objective: Human intention recognition technology plays a vital role in the application of robotic exoskeletons and powered exoskeletons. However, the precise estimation of the continuous motion of each joint represents a major challenge. In the current study, we present a method for estimating continuous elbow joint movement.Methods: We developed a novel approach for estimating the elbow joint angle based on human physiological structure. We used surface electromyography signals to analyze the biomechanical properties of the muscle and combined it with physiological structure to achieve a model for estimating continuous motion. And a genetic algorithm was used to optimize unknown parameters.Results: We performed extensive trials to verify the generalizability and effectiveness of this method. The trial types included elbow joint motion with single cycle trials, typical cycle trials, gradually increasing amplitude trials, and random movement trials for handheld loads of 1.25 and 2.5 kg. The results revealed that the average root-mean-square errors ranged from 0.12 to 0.26 rad, reflecting an appropriate level of estimation accuracy.Conclusion: Establishing a reasonable physiological model and applying an efficient optimization algorithm enabled more accurate estimation of the joint angle. The proposed method provides a theoretical foundation for robotic exoskeletons and powered exoskeletons to understand the intentions of human continuous motion. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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