400 Section - Latent Dimensions of Quiet-Standing Postural Control across Neurological Disorders

Wednesday, May 20, 2026

6:00 PM - 7:30 PM PT

Presenting Author/Autor expositor(s)

KT

Kenta Takeda, PhD

Assistant Professor
Japan Healthcare University
Sapporo, Hokkaido, Japan

Co-Author/Coautor(s)

SF

Shintaro Fujii, PhD

Physical Therapist
Nishiyamato Rehabilitation Hospital
Kitakatsuragi-gun, Nara, Japan
KS

Kosuke Sakano, BS

Physical Therapist
Hokkaido Neurological Hospital
Sapporo, Hokkaido, Japan
KT

Kohei Tanaka, BS

Physical Therapist
Shizuoka Rehabilitation Hospital
Shizuoka-shi, Shizuoka, Japan

Corresponding Author/Autor a quien dirigir la corr(s)

NK

Noritaka Kawashima, PhD

Section Chief
Research Institute of National Rehabilitation Center for Persons with Disabilities
Tokorozawa, Saitama, Japan

Objectives : Postural instability during quiet standing is commonly evaluated using center of pressure (CoP) trajectories, yet the fundamental structure of postural impairment remains insufficiently defined. Although disease-specific abnormalities have been reported, postural control reflects not only pathology-driven deficits but also compensatory strategies that may transcend diagnostic boundaries. This study aimed to identify core dimensions of postural control and determine whether individuals with different neurological conditions share common impairment phenotypes, using exploratory factor analysis (EFA) combined with non-hierarchical clustering applied to multidimensional balance data.

Design: Participants included individuals with stroke (CVA, n=111), Parkinson’s disease (PD, n=72), spinocerebellar degeneration (SCD, n=86), healthy young adults (n=71), and healthy older adults (n=47). During a 30-s quiet-standing, CoP trajectories, full-body kinematics, and lower-leg electromyography were recorded. Forty variables capturing CoP spatiotemporal and frequency-domain indices, joint angles and angular velocities, and muscle activation were extracted. EFA was conducted on all variables, and the resulting factor scores were used for non-hierarchical clustering to identify postural control phenotypes.

Results: Six factors emerged, representing sway magnitude, sway complexity, static posture, mediolateral frequency components, anteroposterior mid-frequency components, and high-frequency components. Cluster analysis using these factor scores yielded eight distinct postural control subtypes. While certain clusters predominantly included healthy individuals or those with marked impairments, participants with the same diagnosis were distributed across multiple clusters, indicating substantial within-diagnosis heterogeneity. Importantly, several clusters contained comparable proportions of individuals from different conditions, suggesting the existence of cross-diagnostic postural phenotypes.

Conclusion: By integrating EFA and clustering, this study delineated the multidimensional structure underlying quiet-standing control and demonstrated that postural instability cannot be fully explained by diagnostic category alone. These cross-diagnostic phenotypes have the potential to inform individualized assessment and rehabilitation strategies that target fundamental postural control mechanisms rather than disease labels.