Investigating how cognitive and motor functions interact in people with multiple sclerosis (PwMS) is key to identifying disease-related alterations, yet technical challenges have long hindered this research. We introduce an innovative framework for dual-task (DT) assessment in PwMS, integrating wearable electroencephalography (EEG) and inertial measurement unit (IMU) sensors. The study involved 11 PwMS (6 males, 5 females; mean age: 58.5 ± 12.5 years), who performed the timed up and go (TUG) test under two conditions: a motor task as single-task (ST) and a motor-cognitive DT. A custom-made bracelet including an IMU and a wearable EEG device allowed the recording of motion data and brain activity during the tasks. The former was used for automatic trial segmentation through a hybrid convolutional neural network and a long-shortterm-memory model. This allowed the extraction of the EEG epoch during the task. Finally, the power spectral density in θ (4-8 Hz) and α (8-12 Hz) frequency bands was analyzed to extract mental workload. The proposed segmentation method achieved accurate estimations when compared to manual video-based labeling, with a very strong correlation R2=0.993 and mean-absolute-error of 0.383 s and 0.294 s for the ST and DT conditions, respectively. The EEG results showed increased mental workload during the DT condition (Wilcoxon signed-rank test p-value = 0.02). The planned inclusion of new participants will help to confirm the robustness of cortical activity patterns during DT performances in PwMS.Clinical relevance - The proposed experimental protocol represents a significant step forward to the understanding of neural correlates of cognitive-motor interaction, allowing the recording of cortical activity during walking. These findings could contribute to a better understanding of the association between DT performance and risk of falls in PwMS and help design specific and personalized rehabilitation interventions.

Wearable EEG-IMU based Framework for Investigating Neural Correlates of Motor-Cognitive Interaction in Multiple Sclerosis

Straudi S.;
2025

Abstract

Investigating how cognitive and motor functions interact in people with multiple sclerosis (PwMS) is key to identifying disease-related alterations, yet technical challenges have long hindered this research. We introduce an innovative framework for dual-task (DT) assessment in PwMS, integrating wearable electroencephalography (EEG) and inertial measurement unit (IMU) sensors. The study involved 11 PwMS (6 males, 5 females; mean age: 58.5 ± 12.5 years), who performed the timed up and go (TUG) test under two conditions: a motor task as single-task (ST) and a motor-cognitive DT. A custom-made bracelet including an IMU and a wearable EEG device allowed the recording of motion data and brain activity during the tasks. The former was used for automatic trial segmentation through a hybrid convolutional neural network and a long-shortterm-memory model. This allowed the extraction of the EEG epoch during the task. Finally, the power spectral density in θ (4-8 Hz) and α (8-12 Hz) frequency bands was analyzed to extract mental workload. The proposed segmentation method achieved accurate estimations when compared to manual video-based labeling, with a very strong correlation R2=0.993 and mean-absolute-error of 0.383 s and 0.294 s for the ST and DT conditions, respectively. The EEG results showed increased mental workload during the DT condition (Wilcoxon signed-rank test p-value = 0.02). The planned inclusion of new participants will help to confirm the robustness of cortical activity patterns during DT performances in PwMS.Clinical relevance - The proposed experimental protocol represents a significant step forward to the understanding of neural correlates of cognitive-motor interaction, allowing the recording of cortical activity during walking. These findings could contribute to a better understanding of the association between DT performance and risk of falls in PwMS and help design specific and personalized rehabilitation interventions.
2025
979-8-3315-8618-8
979-8-3315-8619-5
Cognitive interaction; Cortical activity; Dual-task conditions; Dual-task performance; Dual-tasks; Inertial measurements units; Mental workload; Multiple sclerosis; Neural correlate; Unit-based; cognition; devices; electroencephalography; female; human; male; middle aged; multiple sclerosis; pathophysiology; physiology; wearable electronic device
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11392/2624654
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