aspg-25-4368-1791493208 20261008210008 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Cognitive Human-Computer Interaction JCHCI 2771-1471 2771-1463 2026 11 1 Khaled Sh. Gaber Computer Science and Intelligent Systems Research Center, Blacksburg 24060, Virginia, USA Mahmoud Elshabrawy Mohamed Computer Science and Intelligent Systems Research Center, Blacksburg 24060, Virginia, USA Wireless human-computer interaction increasingly depends on distributed sensing, yet adaptive computer interfaces are still commonly modelled from isolated evidence streams. This paper presents an interaction-centric wireless multimodal fusion model for recognizing cognitive state during computer-based task execution. The model integrates wearable physiology, ocular behaviour, compact neurophysiological summaries, and direct interaction evidence obtained from the task interface, then adjusts each sensing channel through a reliability term that reflects wireless degradation. The experimental workflow follows a public stress-resilience human-computer interaction protocol involving synchronized task phases and computer interaction logs. The analysis shows that interaction variables such as task error, response latency, and click activity are among the strongest indicators of cognitive state and complement physiological information in a meaningful way. The results support the design of adaptive computer interfaces that respond not only to what the user is doing on the screen, but also to how reliably the supporting wireless sensing infrastructure is functioning. 2026 14 19 4368 https://creativecommons.org/licenses/by/4.0/ 10.54216/JCHCI.110103 https://www.americaspg.com/journal/25/article/4368 https://www.americaspg.com/storage/articles/manuscripts/01KTM9FMHQW84G2NY9A1FDWVK2.pdf