100 Section - Online task difficulty adjustment based on neuro- and motor- feedback to enhance the engagement in human-robot interaction task

Tuesday, May 19, 2026

6:00 PM - 7:30 PM PT

Presenting Author/Autor expositor(s)

YL

Yifan Li, PhD

Postdoctoral Fellow
The Seventh Affiliated Hospital of Sun Yat-sen University
Shenzhen, Guangdong, China (People's Republic)

Corresponding Author/Autor a quien dirigir la corr(s)

DH

Dongfeng Huang, MD

Prof.
The Seventh Affiliated Hospital of Sun Yat-sen University
Shenzhen, Guangdong, China (People's Republic)

Objectives : Robot-assisted therapy is increasingly integrated into motor rehabilitation, highlighting the importance of human-robot interaction systems that enable personalized assistance. Enhancing active participation during post-stroke rehabilitation is essential for driving neuroplasticity and improving functional outcomes. Although adaptive feedback can optimize arousal to improve engagement, most approaches rely solely on motor or neural indicators, overlooking the integration of task-specific physical performance with neural adaptation. Therefore, this study proposes a neuro- and motor- feedback system to adaptively regulate the task difficulty levels, rather than relying on static parameter configurations.

Design: The neuro- and motor- feedback (NMF) system utilizes functional near infrared spectroscopy (fNIRS) and tracking error to continuously monitor real-time neural activity and motor performance during a visual-motor task, and realizes online adaptive regulation of task difficulty through fuzzy logic controller. A total of 10 healthy participants were recruited in the study. During the 5-day experimental period, all subjects performed the visual-motor tasks of fixed difficulty and adaptive difficulty each day and were assigned to the control group or the NMF group, respectively.

Results: Compared to the control group, the NMF group showed increased tracking errors, which suggested that the NMF system can provide subjects with challenging training tasks. The NMF group also showed heightened neural activity in the Prefrontal and the sensorimotor cortex, in both single-task trial and after 5 days of training. These findings suggest that the proposed adaptive modulation of task difficulty can indeed enhance cortical activation in PFC and SMC. Moreover, the NMF group exhibited significantly increased strength of brain functional connections between the PFC and sensorimotor areas after training compared to the control group.

Conclusion:

Our findings suggest that the proposed NMF system can enable online neural activity regulation in visual-motor tasks and achieve enhanced integration between cognitive and sensorimotor areas, with the potential to improve the rehabilitation training outcomes.