التفاصيل البيبلوغرافية
| العنوان: |
Validity of Neural Networks to Determine Body Position on the Bicycle. |
| المؤلفون: |
Bini RR; La Trobe University., Serrancoli G; Universitat Politècnica de Catalunya., Santiago PRP; University of São Paulo., Pinto A; Institute of Computing, State University of Compinas., Moura F; State University of Londrina. |
| المصدر: |
Research quarterly for exercise and sport [Res Q Exerc Sport] 2023 Dec; Vol. 94 (4), pp. 905-912. Date of Electronic Publication: 2022 May 16. |
| نوع المنشور: |
Journal Article |
| اللغة: |
English |
| بيانات الدورية: |
Publisher: American Alliance For Health, Physical Education, Recreation, And Dance Country of Publication: United States NLM ID: 8006373 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2168-3824 (Electronic) Linking ISSN: 02701367 NLM ISO Abbreviation: Res Q Exerc Sport Subsets: MEDLINE |
| أسماء مطبوعة: |
Original Publication: Washington DC : American Alliance For Health, Physical Education, Recreation, And Dance |
| مواضيع طبية MeSH: |
Bicycling* , Lower Extremity*, Humans ; Knee Joint ; Knee ; Neural Networks, Computer ; Biomechanical Phenomena |
| مستخلص: |
Purpose: With the increased access to neural networks trained to estimate body segments from images and videos, this study assessed the validity of some of these networks in enabling the assessment of body position on the bicycle. Methods: Fourteen cyclists pedaled stationarily in one session on their own bicycles while video was recorded from their sagittal plane. Reflective markers attached to key bony landmarks were used to manually digitize joint angles at two positions of the crank (3 o'clock and 6 o'clock) extracted from the videos (Reference method). These angles were compared to measurements taken from videos generated by two deep learning-based approaches designed to automatically estimate human joints (Microsoft Research Asia-MSRA and OpenPose). Results: Mean bias for OpenPose ranged between 0.03° and 1.81°, while the MSRA method presented errors between 2.29° and 12.15°. Correlation coefficients were stronger for OpenPose than for the MSRA method in relation to the Reference method for the torso ( r = 0.94 vs. 0.92), hip ( r = 0.69 vs. 0.60), knee ( r = 0.80 vs. 0.71), and ankle ( r = 0.23 vs. 0.20). Conclusion: OpenPose presented better accuracy than the MSRA method in determining body position on the bicycle, but both methods seem comparable in assessing implications from changes in bicycle configuration. |
| فهرسة مساهمة: |
Keywords: Biomechanics; kinesiology; quantitative study; technology |
| تواريخ الأحداث: |
Date Created: 20220516 Date Completed: 20231206 Latest Revision: 20231206 |
| رمز التحديث: |
20231206 |
| DOI: |
10.1080/02701367.2022.2070103 |
| PMID: |
35575754 |
| قاعدة البيانات: |
MEDLINE |
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