A neurofuzzy inference system based on biomechanical features for the evaluation of the effects of physical training

G. Vannozzi, F. Pecoraro, P. Caserotti and A. Cappozzo

Computer Methods in Biomechanics and Biomedical Engineering, 2008, vol. 11, issue 1, 11-17

Abstract: The current study aimed to evaluate physical training effects. For this purpose, a classifier was implemented by taking into account biomechanical features selected from force-plate measurements and a neurofuzzy algorithm for data management and relevant decision-making. Measurements included two sets of sit-to-stand (STS) trials involving two homogeneous groups, experimental and control, of elders. They were carried out before and after a 12-week heavy resistance strength-training program undergone by the experimental group. Pre- and post-training differences were analysed, and percentages of membership to “trained” and “untrained” fuzzy sets calculated. The method was shown to be appropriate for detecting significant training-related changes. Detection accuracy was higher than 87%. Slightly weaker results were obtained using a neural approach, suggesting the need for a larger sample size. In conclusion, the use of a set of biomechanical features and of a neurofuzzy algorithm allowed to propose a global score for evaluating the effectiveness of a specific training program.

Date: 2008
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10255840701550915 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gcmbxx:v:11:y:2008:i:1:p:11-17

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/gcmb20

DOI: 10.1080/10255840701550915

Access Statistics for this article

Computer Methods in Biomechanics and Biomedical Engineering is currently edited by Director of Biomaterials John Middleton

More articles in Computer Methods in Biomechanics and Biomedical Engineering from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().