Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques
Background/Objectives: The aim of this study was to analyze the nonlinear dynamics of handgrip strength (HGS) in young adults, focusing on hand dominance, by employing the Poincaré plot method to assess short- and long-term variability utilizing dynamometry and video motion capture during sustained...
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2024-11-01
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| Series: | Journal of Functional Morphology and Kinesiology |
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| author | Constantin Ciucurel Elena Ioana Iconaru |
| author_facet | Constantin Ciucurel Elena Ioana Iconaru |
| author_sort | Constantin Ciucurel |
| collection | DOAJ |
| description | Background/Objectives: The aim of this study was to analyze the nonlinear dynamics of handgrip strength (HGS) in young adults, focusing on hand dominance, by employing the Poincaré plot method to assess short- and long-term variability utilizing dynamometry and video motion capture during sustained isometric contractions. Methods: A cross-sectional exploratory study was conducted on 30 healthy subjects (mean age 21.6 ± 1.3 years, 13 males and 17 females), measuring HGS for both the dominant hand (DH) and nondominant hand (NDH) using a Saehan hydraulic dynamometer during 25-s sustained isometric contractions. A GoPro HERO11 Black camera recorded the dynamometer’s needle movements, and the video data were analyzed using Kinovea software. Angular values were converted to force using a calibration-based formula, and the Poincaré plot computed variability indices (short-term variability—SD<sub>1</sub>, long-term variability—SD<sub>2</sub>, ratio SD<sub>1</sub>/SD<sub>2</sub>, and area of the fitting ellipse) for each hand in relation to HGS and angular velocity (AV). Data analysis included descriptive and inferential statistics. Results: We demonstrated a strong correlation between mechanical and video measurements (<i>p</i> ≤ 0.001), confirming the reliability of the video method. The findings highlight the importance of nonlinear analysis in understanding neuromuscular function and fatigue, revealing significant correlations among HGS, AV, Poincaré indices, and fatigue levels in both hands (<i>p</i> ≤ 0.001). Increased maximum HGS and AV correlated with higher nonlinear variability in force production. Conclusions: This study confirms the reliability of the proposed video-based HGS assessment and demonstrates the effectiveness of Poincaré plot analysis for capturing nonlinear variability in HGS. |
| format | Article |
| id | doaj-art-1b5c3d38428b42f3a09b2770617efaea |
| institution | DOAJ |
| issn | 2411-5142 |
| language | English |
| publishDate | 2024-11-01 |
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| series | Journal of Functional Morphology and Kinesiology |
| spelling | doaj-art-1b5c3d38428b42f3a09b2770617efaea2025-08-20T02:55:35ZengMDPI AGJournal of Functional Morphology and Kinesiology2411-51422024-11-019423410.3390/jfmk9040234Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing TechniquesConstantin Ciucurel0Elena Ioana Iconaru1Department of Medical Assistance and Physical Therapy, University Center of Pitesti, National University of Science and Technology Politehnica Bucharest, 110040 Pitesti, RomaniaDepartment of Medical Assistance and Physical Therapy, University Center of Pitesti, National University of Science and Technology Politehnica Bucharest, 110040 Pitesti, RomaniaBackground/Objectives: The aim of this study was to analyze the nonlinear dynamics of handgrip strength (HGS) in young adults, focusing on hand dominance, by employing the Poincaré plot method to assess short- and long-term variability utilizing dynamometry and video motion capture during sustained isometric contractions. Methods: A cross-sectional exploratory study was conducted on 30 healthy subjects (mean age 21.6 ± 1.3 years, 13 males and 17 females), measuring HGS for both the dominant hand (DH) and nondominant hand (NDH) using a Saehan hydraulic dynamometer during 25-s sustained isometric contractions. A GoPro HERO11 Black camera recorded the dynamometer’s needle movements, and the video data were analyzed using Kinovea software. Angular values were converted to force using a calibration-based formula, and the Poincaré plot computed variability indices (short-term variability—SD<sub>1</sub>, long-term variability—SD<sub>2</sub>, ratio SD<sub>1</sub>/SD<sub>2</sub>, and area of the fitting ellipse) for each hand in relation to HGS and angular velocity (AV). Data analysis included descriptive and inferential statistics. Results: We demonstrated a strong correlation between mechanical and video measurements (<i>p</i> ≤ 0.001), confirming the reliability of the video method. The findings highlight the importance of nonlinear analysis in understanding neuromuscular function and fatigue, revealing significant correlations among HGS, AV, Poincaré indices, and fatigue levels in both hands (<i>p</i> ≤ 0.001). Increased maximum HGS and AV correlated with higher nonlinear variability in force production. Conclusions: This study confirms the reliability of the proposed video-based HGS assessment and demonstrates the effectiveness of Poincaré plot analysis for capturing nonlinear variability in HGS.https://www.mdpi.com/2411-5142/9/4/234hand grip strengthnonlinear dynamicsPoincaré plottime seriesmotion capture techniques |
| spellingShingle | Constantin Ciucurel Elena Ioana Iconaru Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques Journal of Functional Morphology and Kinesiology hand grip strength nonlinear dynamics Poincaré plot time series motion capture techniques |
| title | Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques |
| title_full | Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques |
| title_fullStr | Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques |
| title_full_unstemmed | Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques |
| title_short | Nonlinear Dynamics Analysis of Handgrip Strength Using the Poincaré Plot Method Through Video Processing Techniques |
| title_sort | nonlinear dynamics analysis of handgrip strength using the poincare plot method through video processing techniques |
| topic | hand grip strength nonlinear dynamics Poincaré plot time series motion capture techniques |
| url | https://www.mdpi.com/2411-5142/9/4/234 |
| work_keys_str_mv | AT constantinciucurel nonlineardynamicsanalysisofhandgripstrengthusingthepoincareplotmethodthroughvideoprocessingtechniques AT elenaioanaiconaru nonlineardynamicsanalysisofhandgripstrengthusingthepoincareplotmethodthroughvideoprocessingtechniques |