Study on Optimization of Eye Control Interactive Interface in ALS Patients Based on Cognitive Load Theory

HE Yubin; CHEN Yang

doi:10.19554/j.cnki.1001-3563.2025.18.011

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (18) : 117-126. DOI: 10.19554/j.cnki.1001-3563.2025.18.011

Industrial Design

Study on Optimization of Eye Control Interactive Interface in ALS Patients Based on Cognitive Load Theory

HE Yubin, CHEN Yang^*

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Abstract

The work aims to reduce cognitive load for ALS patients and propose a set of design principles of eye- controlled interaction interfaces suitable for ALS patients. Initially, experiments were conducted using existing eye-control interaction interfaces available in the market, focusing on three phases: free browsing tests, task tests, and subjective evaluation tests. These experiments identified problems with the current interfaces, leading to the development of corresponding design principles. Then, the design principles were applied to optimize the original interface, and compare the cognitive load of the interface before and after optimization by eye movement data (such as blink rate, blink time, total fixation number, pupil diameter, hot zone map, AOI fixation rate), performance data (task completion time and task completion rate) and subjective cognitive load (NASA-TLX scale). The eye movement data and performance data of the optimized interface were both superior to those of the original interface, and the subjective cognitive load was also less than that of the original interface. The results show that the proposed design principle of eye-controlled interfaces for ALS patients is feasible and the comprehensive analysis method of subjective and objective cognitive load is suitable for the optimization analysis of eye-controlled interfaces in ALS patients.

Key words

eye-controlled interaction / cognitive load / amyotrophic lateral sclerosis (ALS) / interface design / caring experience

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HE Yubin, CHEN Yang. Study on Optimization of Eye Control Interactive Interface in ALS Patients Based on Cognitive Load Theory[J]. Packaging Engineering. 2025, 46(18): 117-126 https://doi.org/10.19554/j.cnki.1001-3563.2025.18.011

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