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Original Article
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Gait Instability and Compensatory Mechanisms in Parkinson’s Disease Patients With Camptocormia: An Exploratory Study
Hideyuki Urakami, Yasutaka Nikaido, Yuta Okuda, Yutaka Kikuchi, Ryuichi Saura, Yohei Okada
J Mov Disord. 2025;18(2):127-137.   Published online December 27, 2024
DOI: https://doi.org/10.14802/jmd.24226
  • 1,663 View
  • 218 Download
AbstractAbstract PDFSupplementary Material
Objective
Camptocormia contributes to vertical gait instability and, at times, may also lead to forward instability in experimental settings in Parkinson’s disease (PD) patients. However, these aspects, along with compensatory mechanisms, remain largely unexplored. This study comprehensively investigated gait instability and compensatory strategies in PD patients with camptocormia (PD+CC).
Methods
Ten PD+CC patients, 30 without camptocormia (PD-CC), and 27 healthy controls (HCs) participated. Self-paced gait tasks were analyzed using three-dimensional motion capture systems to assess gait stability as well as spatiotemporal and kinematic parameters. Unique cases with pronounced forward gait stability or instability were first identified, followed by group comparisons. Correlation analysis was performed to examine associations between trunk flexion angles (lower/upper) and gait parameters. The significance level was set at 0.05.
Results
Excluding one unique case, the PD+CC group presented a significantly lower vertical center of mass (COM) position (p=0.019) increased mediolateral COM velocity (p=0.004) and step width (p=0.013), compared to the PD-CC group. Both PD groups presented greater anterior‒posterior margins of stability than did the HCs (p<0.001). Significant correlations were found between lower/upper trunk flexion angles and a lower vertical COM position (r=-0.690/-0.332), as well as increased mediolateral COM velocity (r=0.374/0.446) and step width (r=0.580/0.474).
Conclusion
Most PD+CC patients presented vertical gait instability, increased fall risk, and adopted compensatory strategies involving greater lateral COM shift and a wider base of support, with these trends intensifying as trunk flexion angles increased. These findings may guide targeted interventions for gait instability in PD+CC patients.
Brief communication
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Automatic Measurement of Postural Abnormalities With a Pose Estimation Algorithm in Parkinson’s Disease
Jung Hwan Shin, Kyung Ah Woo, Chan Young Lee, Seung Ho Jeon, Han-Joon Kim, Beomseok Jeon
J Mov Disord. 2022;15(2):140-145.   Published online January 19, 2022
DOI: https://doi.org/10.14802/jmd.21129
  • 4,508 View
  • 277 Download
  • 7 Web of Science
  • 6 Crossref
AbstractAbstract PDFSupplementary Material
Objective
This study aims to develop an automated and objective tool to evaluate postural abnormalities in Parkinson’s disease (PD) patients.
Methods
We applied a deep learning-based pose-estimation algorithm to lateral photos of prospectively enrolled PD patients (n = 28). We automatically measured the anterior flexion angle (AFA) and dropped head angle (DHA), which were validated with conventional manual labeling methods.
Results
The automatically measured DHA and AFA were in excellent agreement with manual labeling methods (intraclass correlation coefficient > 0.95) with mean bias equal to or less than 3 degrees.
Conclusion
The deep learning-based pose-estimation algorithm objectively measured postural abnormalities in PD patients.

Citations

Citations to this article as recorded by  
  • Research Progress of Camptocormia in Parkinson Disease
    Yilin Lu, Xiang Zhang, Junyu Li, Weishi Li, Miao Yu
    Clinical Spine Surgery.2025; 38(2): 39.     CrossRef
  • Spatiotemporal Gait Parameters During Turning and Imbalance in Parkinson’s Disease: Video-Based Analysis From a Single Camera
    HoYoung Jeon, Jung Hwan Shin, Ri Yu, Min Kyung Kang, Seungmin Lee, Seoyeon Kim, Bora Jin, Kyung Ah Woo, Han-Joon Kim, Beomseok Jeon
    Journal of Movement Disorders.2025; 18(1): 87.     CrossRef
  • Botulinum Toxin for Axial Postural Abnormalities in Parkinson’s Disease: A Systematic Review
    Marialuisa Gandolfi, Carlo Alberto Artusi, Gabriele Imbalzano, Serena Camozzi, Mauro Crestani, Leonardo Lopiano, Michele Tinazzi, Christian Geroin
    Toxins.2024; 16(5): 228.     CrossRef
  • Three‐Dimensional Mesh Recovery from Common 2‐Dimensional Pictures for Automated Assessment of Body Posture in Camptocormia
    Robin Wolke, Olga Gavriliuc, Oliver Granert, Günther Deuschl, Nils G. Margraf
    Movement Disorders Clinical Practice.2023; 10(3): 472.     CrossRef
  • Assessment of Axial Postural Abnormalities in Parkinsonism: Automatic Picture Analysis Software
    Carlo Alberto Artusi, Christian Geroin, Gabriele Imbalzano, Serena Camozzi, Stefano Aldegheri, Leonardo Lopiano, Michele Tinazzi, Nicola Bombieri
    Movement Disorders Clinical Practice.2023; 10(4): 636.     CrossRef
  • Camera- and Viewpoint-Agnostic Evaluation of Axial Postural Abnormalities in People with Parkinson’s Disease through Augmented Human Pose Estimation
    Stefano Aldegheri, Carlo Alberto Artusi, Serena Camozzi, Roberto Di Marco, Christian Geroin, Gabriele Imbalzano, Leonardo Lopiano, Michele Tinazzi, Nicola Bombieri
    Sensors.2023; 23(6): 3193.     CrossRef

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