Nonlinear analysis of the effects of vision and postural threat on upright stance. Weinberg, S. E., Palmisano, S., Allison, R. S., & Cleworth, T. W. Gait and Posture, 122:123-129, 2025. ![Nonlinear analysis of the effects of vision and postural threat on upright stance [link]](https://bibbase.org/img/filetypes/link.svg "link")
-1 doi abstract bibtex Background: Humans maintain upright stance to interact with their surroundings. Linear analysis of these processes fails to address the nonstationary behaviour of the human body, whereas dynamical nonlinear approaches consider the underlying dynamics of postural sway. Here, behaviour during upright stance was examined using nonlinear methods to provide additional insight into the effects of postural threat (height above ground) and vision on postural control. Research question: Can nonlinear methods provide a more comprehensive identification and analysis of height- and vision-related changes in quiet standing? Methods: This study is a secondary analysis of a previously collected dataset [1]. Twenty young healthy adults performed a 60s quiet standing balance task under all combinations of: 1) two height conditions: standing at ground level (LOW) and standing 3.2 m above ground level (HIGH); and 2) two visual conditions: eyes open (EO) and eyes closed (EC). Recurrence quantification analyses (RQA) were performed on centre of pressure (COP) and centre of mass (COM) data to calculate Recurrence Rate (%REC), Determinism (%DET), Entropy (ENT), and Average Line Length (LINE). Results: For COP, %DET, ENT, and LINE showed significant effects of vision and height, with the values of each measure being lowest in the HIGH-EC condition. For COM, %DET, ENT, and LINE showed significant effects for vision, with the values of each being lower in the EC compared to EO condition; additionally, %DET was significantly smaller in the HIGH condition compared to LOW. Significance: RQA identified differences in sway dynamics across both vision and height conditions that linear methods failed to detect [1]. They represented greater randomness and adaptability in response to increased fear (HIGH) or decreased sensory information (EC). The novel effects observed with these RQA variables suggest nonlinear analyses provide a more robust tool for identifying the effects of postural threat and vision on upright stance.
@article{Weinberg:aa,
abstract = {Background: Humans maintain upright stance to interact with their surroundings. Linear analysis of these processes fails to address the nonstationary behaviour of the human body, whereas dynamical nonlinear approaches consider the underlying dynamics of postural sway. Here, behaviour during upright stance was examined using nonlinear methods to provide additional insight into the effects of postural threat (height above ground) and vision on postural control. Research question: Can nonlinear methods provide a more comprehensive identification and analysis of height- and vision-related changes in quiet standing? Methods: This study is a secondary analysis of a previously collected dataset [1]. Twenty young healthy adults performed a 60s quiet standing balance task under all combinations of: 1) two height conditions: standing at ground level (LOW) and standing 3.2 m above ground level (HIGH); and 2) two visual conditions: eyes open (EO) and eyes closed (EC). Recurrence quantification analyses (RQA) were performed on centre of pressure (COP) and centre of mass (COM) data to calculate Recurrence Rate (\%REC), Determinism (\%DET), Entropy (ENT), and Average Line Length (LINE). Results: For COP, \%DET, ENT, and LINE showed significant effects of vision and height, with the values of each measure being lowest in the HIGH-EC condition. For COM, \%DET, ENT, and LINE showed significant effects for vision, with the values of each being lower in the EC compared to EO condition; additionally, \%DET was significantly smaller in the HIGH condition compared to LOW. Significance: RQA identified differences in sway dynamics across both vision and height conditions that linear methods failed to detect [1]. They represented greater randomness and adaptability in response to increased fear (HIGH) or decreased sensory information (EC). The novel effects observed with these RQA variables suggest nonlinear analyses provide a more robust tool for identifying the effects of postural threat and vision on upright stance. },
author = {Sara E. Weinberg and Stephen Palmisano and Robert S. Allison and Taylor W. Cleworth},
date-added = {2025-07-22 20:21:56 -0400},
date-modified = {2025-07-22 20:21:56 -0400},
doi = {10.1016/j.gaitpost.2025.07.002},
journal = {Gait and Posture},
keywords = {Optic flow & Self Motion (also Locomotion & Aviation)},
pages = {123-129},
title = {Nonlinear analysis of the effects of vision and postural threat on upright stance},
url-1 = {https://doi.org/10.1016/j.gaitpost.2025.07.002},
volume = {122},
year = {2025},
bdsk-url-1 = {https://doi.org/10.1016/j.gaitpost.2025.07.002}}
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Twenty young healthy adults performed a 60s quiet standing balance task under all combinations of: 1) two height conditions: standing at ground level (LOW) and standing 3.2 m above ground level (HIGH); and 2) two visual conditions: eyes open (EO) and eyes closed (EC). Recurrence quantification analyses (RQA) were performed on centre of pressure (COP) and centre of mass (COM) data to calculate Recurrence Rate (%REC), Determinism (%DET), Entropy (ENT), and Average Line Length (LINE). Results: For COP, %DET, ENT, and LINE showed significant effects of vision and height, with the values of each measure being lowest in the HIGH-EC condition. For COM, %DET, ENT, and LINE showed significant effects for vision, with the values of each being lower in the EC compared to EO condition; additionally, %DET was significantly smaller in the HIGH condition compared to LOW. Significance: RQA identified differences in sway dynamics across both vision and height conditions that linear methods failed to detect [1]. They represented greater randomness and adaptability in response to increased fear (HIGH) or decreased sensory information (EC). The novel effects observed with these RQA variables suggest nonlinear analyses provide a more robust tool for identifying the effects of postural threat and vision on upright stance. ","author":[{"firstnames":["Sara","E."],"propositions":[],"lastnames":["Weinberg"],"suffixes":[]},{"firstnames":["Stephen"],"propositions":[],"lastnames":["Palmisano"],"suffixes":[]},{"firstnames":["Robert","S."],"propositions":[],"lastnames":["Allison"],"suffixes":[]},{"firstnames":["Taylor","W."],"propositions":[],"lastnames":["Cleworth"],"suffixes":[]}],"date-added":"2025-07-22 20:21:56 -0400","date-modified":"2025-07-22 20:21:56 -0400","doi":"10.1016/j.gaitpost.2025.07.002","journal":"Gait and Posture","keywords":"Optic flow & Self Motion (also Locomotion & Aviation)","pages":"123-129","title":"Nonlinear analysis of the effects of vision and postural threat on upright stance","url-1":"https://doi.org/10.1016/j.gaitpost.2025.07.002","volume":"122","year":"2025","bdsk-url-1":"https://doi.org/10.1016/j.gaitpost.2025.07.002","bibtex":"@article{Weinberg:aa,\n\tabstract = {Background: Humans maintain upright stance to interact with their surroundings. Linear analysis of these processes fails to address the nonstationary behaviour of the human body, whereas dynamical nonlinear approaches consider the underlying dynamics of postural sway. Here, behaviour during upright stance was examined using nonlinear methods to provide additional insight into the effects of postural threat (height above ground) and vision on postural control. Research question: Can nonlinear methods provide a more comprehensive identification and analysis of height- and vision-related changes in quiet standing? Methods: This study is a secondary analysis of a previously collected dataset [1]. Twenty young healthy adults performed a 60s quiet standing balance task under all combinations of: 1) two height conditions: standing at ground level (LOW) and standing 3.2 m above ground level (HIGH); and 2) two visual conditions: eyes open (EO) and eyes closed (EC). Recurrence quantification analyses (RQA) were performed on centre of pressure (COP) and centre of mass (COM) data to calculate Recurrence Rate (\\%REC), Determinism (\\%DET), Entropy (ENT), and Average Line Length (LINE). Results: For COP, \\%DET, ENT, and LINE showed significant effects of vision and height, with the values of each measure being lowest in the HIGH-EC condition. For COM, \\%DET, ENT, and LINE showed significant effects for vision, with the values of each being lower in the EC compared to EO condition; additionally, \\%DET was significantly smaller in the HIGH condition compared to LOW. Significance: RQA identified differences in sway dynamics across both vision and height conditions that linear methods failed to detect [1]. They represented greater randomness and adaptability in response to increased fear (HIGH) or decreased sensory information (EC). 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