Work

EEG Detection and Prediction of Freezing of Gait in Parkinson's Disease Based on Spatiotemporal Coherent Modes

Year: 2024

Type: article

Abstract: OBJECTIVE: Freezing of gait (FOG) in Parkinson's disease has a complex neurological mechanism. Compared with other modalities, electroencephalogram (EEG) can reflect FOG-related brain activity of both motor and non-motor symptoms. However, EEG-based FOG prediction methods often extract time, spatial, frequency, time-frequency, or phase information separately, which fragments the coupling among these heterogeneous features and cannot completely characterize the brain dynamics when FOG occurs. METHODS: In this study, dynamic spatiotemporal coherent modes of EEG were studied and used for FOG detection and prediction. A dynamic mode decomposition (DMD) method was first applied to extract the spatiotemporal coherent modes. Dynamic changes of the spatiotemporal modes, in both amplitude and phase of motor-related frequency bands, were evaluated with analytic common spatial patterns (ACSP) to extract the essential differences among normal, freezing, and transitional gaits. RESULTS: The proposed method was verified in practical clinical data. Results showed that, in the detection task, the DMD-ACSP achieved an accuracy of 86.4 $\pm$ 3.6% and a sensitivity of 83.5 $\pm$ 4.3%. In the prediction task, 86.5 $\pm$ 3.2% accuracy and 86.7 $\pm$ 7.8% sensitivity were achieved. CONCLUSION: Comparative studies showed that the DMD-ACSP method significantly improves FOG detection and prediction performance. Moreover, the DMD-ACSP reveals the spatial patterns of dynamic brain functional connectivity, which best discriminate the different gaits. SIGNIFICANCE: The spatiotemporal coherent modes may provide a useful indication for personalized intervention and transcranial magnetic stimulation neuromodulation in medical practices.

Source: IEEE Journal of Biomedical and Health Informatics

DOI: 10.1109/jbhi.2024.3496074

Authors: Jun Li, Yuzhu Guo

Institutions: Jilin University, Beihang University

Language: English

Topic: Balance, Gait, and Falls Prevention

Subfield: Physical Therapy, Sports Therapy and Rehabilitation

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,495