Category: Parkinson's Disease (Other)
Objective: This study aims to analyze gait differences between individuals with Parkinson’s disease (PD) and healthy participants using the Timed Up-and-Go (TUG) test, exploring the feasibility of mixed reality (MR) devices for objective symptom assessment.
Background: Parkinson’s disease is associated with motor dysfunctions often evaluated subjectively. Traditional assessments, such as the TUG test, provide valuable information but may lack the precision required for objective measurement. MR technology, integrating sensors and machine learning, offers a more objective approach to gait analysis.
Method: The study involved 50 PD patients and 50 healthy individuals. Participants were assessed using clinical scales (MDS-UPDRS, Hoehn & Yahr) and the TUG test, with kinematic data collected via Microsoft HoloLens 2. The data was compared with a reference device, and temporal gait patterns were analyzed using Dynamic Time Warping (DTW), Hidden Markov Models (HMMs), and Fast Fourier Transform (FFT).
Results: Statistical analysis revealed significant gait differences between groups. The Random Forest classifier identified PD patients with 81% accuracy. Key differences included shorter step times, more steps during turning and sitting, and slower movement in PD patients. Turning and sitting times were longer, indicating postural instability. No significant differences were found in basic gait parameters like stride time, stride length, and cadence.
Conclusion: This study demonstrates the potential of MR technology combined with machine learning for improved PD assessment, providing a more precise approach than traditional methods. The integration of DTW, HMMs, and FFT could enhance clinical diagnosis and monitoring.
The project was funded by The National Centre for Research and Development, Poland under Lider Grant no: LIDER/6/0049/L-12/20/NCBIR/2021 and by the Ministry of Science and Higher Education (MNiSW) under the project no. MNiSW/2025/DPI/53, Support for Students in Enhancing Their Competencies and Skills.
To cite this abstract in AMA style:
M. Wójcik-Pędziwiatr, D. Hemmerling, J. Stępień, M. Yufan, M. Kaczmarska, W. Szecówka, A. Srinivasa, M. Rudzińska-Bar. Gait Analysis in Parkinson’s Disease with Mixed Reality [abstract]. Mov Disord. 2025; 40 (suppl 1). https://www.mdsabstracts.org/abstract/gait-analysis-in-parkinsons-disease-with-mixed-reality/. Accessed November 20, 2025.« Back to 2025 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/gait-analysis-in-parkinsons-disease-with-mixed-reality/