Stroke rehabilitation critically relies on two pillars: precise functional assessment to dynamically track recovery and evidence-based interventions to restore independence. Traditional assessment tools—including clinical scales and the International Classification of Functioning, Disability and Health (ICF) framework—provide essential benchmarks but face limitations in sensitivity and standardization, driving ongoing efforts to refine them for diverse clinical needs. Similarly, while single-modality therapies (e.g., neuromodulation techniques like tDCS/FES or traditional approaches like Tai Chi) demonstrate efficacy, their integration into multimodal strategies remains inadequately explored. This Research Topic addresses the urgent need to bridge these gaps, leveraging technological innovations to optimize functional assessment and redefine rehabilitation paradigms.

This Research Topic aims to catalyze advances in stroke rehabilitation by tackling two interconnected challenges. First, revolutionizing functional assessment: we seek to overcome limitations of traditional tools through AI-driven integration of multimodal data (e.g., ICF-coded records, sensor metrics, clinical scores) to enable objective recovery trajectory prediction, automated pattern analysis, and personalized stratification. Second, decoding multimodal intervention synergy: we will critically evaluate whether combining therapies (e.g., Western neuromodulation + traditional physical therapies) yields synergistic (1+1>2), additive (1+1=2), or diminishing returns (1+1<2) for functional outcomes, exploring key questions such as: Does pairing tDCS with Tai Chi enhance motor recovery synergistically? Does sequenced delivery (e.g., acupuncture before FES) outperform concurrent application? How do neuroplasticity mechanisms underpin these interactions? By leveraging AI advances, we seek to advance intelligent functional assessment in stroke rehabilitation while promoting research on multimodal therapy integration to enhance treatment effectiveness.

To advance functional assessment and therapeutic interventions in stroke rehabilitation, this Research Topic welcomes contributions addressing, but not limited to, the following themes:

A. Functional Assessment:

• Novel/refined clinical scale development & validation
• ICF framework implementation & adaptation

Special Interest:

• AI/ML-driven innovations (e.g., recovery prediction models; neural network-based modeling of ICF data; sensor-based motion analytics).

B. Therapeutic Interventions:

• Efficacy & mechanisms of single-modality therapies

Special Interest:

• Multimodal integration (e.g., Brain + Limb targeted, Western + traditional therapies)
• Temporal optimization: Sequencing vs. concurrent protocols
• Neurophysiological biomarkers of treatment response

Are you interested in contributing a manuscript to this Research Topic?

Stroke Rehabilitation: Advances in Functional Assessment and Therapeutic Interventions