Technical Validation of a Multimodal Cognitive-Haptic Sudoku Platform Under Simulated Tremor Conditions

Area of Science:

• Neuroscience
• Rehabilitation Engineering
• Human-Computer Interaction

Background:

• Neurological disorders like Parkinson's and Alzheimer's present complex motor and cognitive challenges.
• Integrated rehabilitation strategies are crucial for addressing these overlapping impairments.
• Simulated tremor conditions can mimic motor deficits seen in neurological diseases.

Purpose of the Study:

• To technically validate a dual-modality rehabilitation platform integrating haptic motor interaction and cognitive tasks.
• To assess the platform's performance under simulated tremor conditions in healthy adults.
• To evaluate the usability of the platform in older adults.

Main Methods:

• Developed a real-time tremor-filtering pipeline using discrete wavelet denoising, Kalman smoothing, and wavelet packet decomposition.
• Conducted preclinical evaluation with healthy adults performing a cognitive-haptic task under no tremor, simulated tremor without filtering, and simulated tremor with filtering.
• Assessed usability with older participants using the System Usability Scale (SUS).

Main Results:

• The platform demonstrated low end-to-end latency (41.4 ± 1.4 ms).
• Tremor filtering significantly improved task performance compared to unfiltered tremor, though not fully restoring baseline.
• High usability was reported (overall mean SUS = 81.4 ± 6.2).

Conclusions:

• The dual-modality platform is technically feasible for rehabilitation applications.
• The tremor-filtering algorithm offers a promising first-step compensation strategy for motor impairments.
• Further patient studies are warranted to assess clinical effectiveness in neurodegenerative disease populations.