Association Between Turn Impairments and Cognitive Function in Parkinson Disease
Shanhu Xu1,2, Linlin Kong1, Xiaoli Liu2
1Department of Neurology Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China.
Aging Medicine (Milton (N.S.W))
|September 2, 2025
Summary
Turn performance, including step count and angular velocity, can help identify cognitive impairment in Parkinson disease (PD) patients. These metrics, especially during 360° turns, show potential for distinguishing cognitive decline from normal cognition in PD.
Area of Science:
- Neurology
- Movement Disorders
- Cognitive Neuroscience
Background:
- Parkinson disease (PD) is a neurodegenerative disorder affecting motor function.
- Cognitive impairment (CI) is a common non-motor symptom in PD, impacting daily life.
- Objective assessment of cognitive status in PD is crucial for management.
Purpose of the Study:
- To investigate the association between turn parameters and cognitive status in Parkinson disease (PD) patients.
- To determine the efficacy of turn performance metrics in differentiating PD-related cognitive impairment (CI) from normal cognition (NC).
Main Methods:
- 168 PD patients (102 NC, 66 CI) underwent 180° and 360° turn trials using the MATRIX wearable system.
- Turn parameters evaluated: turn duration, step count, mean angular velocity (MAV), and peak angular velocity (PAV).
- Cognitive function assessed using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA).
Main Results:
- PD patients with CI exhibited longer turn durations and higher step counts compared to those with NC.
- PD-CI group showed lower MAV and PAV during both 180° and 360° turns.
- Step counts and MAV during 360° turns effectively distinguished PD-CI from PD-NC (AUCs 0.781 and 0.789).
Conclusions:
- Turn performance metrics are significantly associated with cognitive status in PD.
- 360° turn analysis using wearable systems can aid in assessing cognitive impairment in PD patients.
- Routine clinic assessment of 360° turn characteristics may improve understanding of CI in PD.
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