Journal of Movement Disorders

Original Article

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

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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.

Citations

Citations to this article as recorded by

Immediate Effects of a Jewett Brace on Posture and Dynamic Balance in Parkinson’s Disease-Associated Camptocormia: A Case Report
Chisato Nakamoto, Kyota Bando, Yohei Mukai, Yuji Takahashi, Kazuhiko Seki, Takatoshi Hara
Cureus.2026;[Epub] CrossRef
How are we representing the trunk? A narrative review on marker sets for kinematics analysis of neurological conditions.
María B. Sánchez, Alberto Javier Fidalgo-Herrera, Bruno Mazuquin
Clinical Biomechanics.2026; 137: 106843. CrossRef

Brief communication

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

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289 Download
12 Web of Science
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Abstract PDF Supplementary 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

A novel multimodal AI framework for early diagnosis of idiopathic Parkinson’s disease
Efe Yılmaz Taşyürek, Şaban Murat Altun, Ata Emir Uncu, Sefa Tunca, Sevinç İlhan Omurca, Meltem Kurt Pehlivanoğlu, Aybala Neslihan Alagöz, Oğulcan Kalkan
Medical & Biological Engineering & Computing.2026; 64(5): 1689. CrossRef
Validating Single-Camera Pose Estimation Against Multi-Camera Motion Capture for Accessible Biomechanical Assessment
Aniket Pratapneni, Ryan Halvorson, Pavlos Silvestros, Nicholas Harris, Jeannie F. Bailey
IEEE Access.2026; 14: 66264. CrossRef
Research Progress of Camptocormia in Parkinson Disease
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Clinical Spine Surgery.2025; 38(2): 39. CrossRef
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HoYoung Jeon, Jung Hwan Shin, Ri Yu, Min Kyung Kang, Seungmin Lee, Seoyeon Kim, Bora Jin, Kyung Ah Woo, Han-Joon Kim, Beomseok Jeon
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Journal of Neurology.2025;[Epub] CrossRef
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Sensors.2025; 25(20): 6373. CrossRef
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Three‐Dimensional Mesh Recovery from Common 2‐Dimensional Pictures for Automated Assessment of Body Posture in Camptocormia
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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
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