motor-imagery-performance-through-embodied-digital-twins-virtual

Motor Imagery Performance Through Embodied Digital Twins in a Virtual Reality-Enabled Brain-Computer Interface Environment

This study introduces an innovative framework for neurological rehabilitation by integrating brain-computer interfaces (BCI) and virtual reality (VR) ...

Vellore Institute of Technology

Reaction time is an important measure of sensorimotor performance and coordination and has been shown to improve with training. Various training methods have been employed in the past to improve reaction time. Tactile imagery (TI) is a method of mentally simulating a tactile sensation and has been used in brain-computer interface applications. However, it is yet unknown whether TI can have a learning effect and improve reaction time.

The Effect of Tactile Imagery Training on Reaction Time in Healthy Participants.

: The purpose of this study was to investigate the cortical activity and digit classification performance during tactile imagery (TI) of a vibratory stimulus at the index, middle, and thumb digits within the left hand in healthy individuals. Furthermore, the cortical activities and classification performance of the compound TI were compared with similar compound motor imagery (MI) with the same digits as TI in the same subjects.  Twelve healthy right-handed adults with no history of upper limb injury, musculoskeletal condition, or neurological disorder participated in the study. The study evaluated the event-related desynchronization (ERD) response and brain-computer interface (BCI) classification performance on discriminating between the digits in the left-hand during the imagery of vibrotactile stimuli to either the index, middle, or thumb finger pads for TI and while performing a motor activity with the same digits for MI. A supervised machine learning technique was applied to discriminate between the digits within the same given limb for both imagery conditions.  Both TI and MI exhibited similar patterns of ERD in the alpha and beta bands at the index, middle, and thumb digits within the left hand. While TI had significantly lower ERD for all three digits in both bands, the classification performance of TI-based BCI (77.74 ± 6.98%) was found to be similar to the MI-based BCI (78.36 ± 5.38%).  The results of this study suggest that compound tactile imagery can be a viable alternative to MI for BCI classification. The study contributes to the growing body of evidence supporting the use of TI in BCI applications, and future research can build on this work to explore the potential of TI-based BCI for motor rehabilitation and the control of external devices.

Evaluation of EEG Oscillatory Patterns and Classification of Compound Limb Tactile Imagery.

The aim of the present study is to evaluate the effect of vibrotactile stimulation prior to repeated complex motor imagery of finger movements using the non-dominant hand on motor imagery (MI) performance.

Enhanced motor imagery of digits within the same hand via vibrotactile stimulation.

This study aimed to assess the usability of a virtual reality-assisted sensorimotor activation (VRSMA) apparatus for individual digit rehabilitation. The study had two main objectives: Firstly, to collect preliminary data on the expectations and preferences of patients with carpal tunnel syndrome (CTS) regarding virtual reality (VR) and an apparatus-assisted therapy for their affected digits. Secondly, to evaluate the usability of the VRSMA apparatus that was developed.

Article	Year
The Effect of Tactile Imagery Training on Reaction Time in Healthy Participants. Brain sciences\| PubMed ID: 36831864	2023
Evaluation of EEG Oscillatory Patterns and Classification of Compound Limb Tactile Imagery. Brain sciences\| PubMed ID: 37190621	2023
Enhanced motor imagery of digits within the same hand via vibrotactile stimulation. Frontiers in neuroscience\| PubMed ID: 37360173	2023
Feasibility and usability of a virtual-reality-based sensorimotor activation apparatus for carpal tunnel syndrome patients. PloS one\| PubMed ID: 37819927	2023

Vadivelan Ramu

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