Iterative optimization of robot surgery system interface design from the perspective of cognitive mechanisms

doi:10.11996/JG.j.2095-302X.2025020469

Abstract

Abstract:

This study aims to enhance the cognitive experience of doctors using surgical robots during the diagnostic and treatment process, and to complete the iterative optimization of the interface design of the robot surgery system to ensure the efficiency and safety of the treatment. First, the interaction interface of the liver cancer ablation surgery robot was selected as the research object, and the natural language processing technology (NLP) based on the BERT (bidirectional encoder representation from transformers) model was used to extract key words from the user’s spoken report and select and classify cognitive related vocabulary. User needs were summarized and refined through the affinity diagram method. The expert’s weight assignment for each demand item were calculated using an innovative combination of the ICE (impact confidence ease) three-dimensional scoring model and the ideal point vector projection method. The key needs were selected based on the development cost and reference to the cognitive mechanism principles and FAST (function analysis system technique) model. User requirements were analyzed and transformed into design layers through a combination of cognitive mechanism principles and FAST model. The schemes before and after iteration were subjected to usability testing, collecting objective and subjective evaluation data to verify the rationality of the design. Then, the cognitive characteristics were taken as the entry point, and the design iteration and optimization of the liver cancer ablation surgery robot interface were completed through a combination of qualitative and quantitative analysis. Finally, the usability test demonstrated that the post-iteration design can significantly reduce the operation time and the frequency of ineffective operations, while achieving higher user experience scores. Introducing cognitive theory as a guide in the interface design of robot surgery systems, and combining the BERT natural language processing model with the ICE-ideal point vector projection demand analysis method, this approach enhanced the usability of the original interface, optimized the cognitive experience of the operation process, and provide guidance and reference in theory and practice for the interface design of robot surgery systems.

Key words: interface design, surgical robot, cognitive mechanism, user demand, design iteration

CLC Number:

LI Saisai, SUN Bowen, LI Dijia, PAN Wenjuan. Iterative optimization of robot surgery system interface design from the perspective of cognitive mechanisms[J]. Journal of Graphics, 2025, 46(2): 469-478.

Figures/Tables 26

References 18

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分类	关键词
注意	持续专注、分心、警觉异样、信息凸显、干扰
感知	平静感、紧张感、视觉反馈、听觉提示、差异化
记忆	记忆量、逻辑性、识别性、分类识记、记忆一致

分类	关键词
注意	持续专注、分心、警觉异样、信息凸显、干扰
感知	平静感、紧张感、视觉反馈、听觉提示、差异化
记忆	记忆量、逻辑性、识别性、分类识记、记忆一致

编号	需求描述	编号	需求描述
A1	保持持续专注	A5	信息分类识记
A2	警觉异样信息	A6	记忆逻辑连贯
A3	情感语义感知	A7	分割记忆任务
A4	多重通道感知	A8	符号识别性高

编号	需求描述	编号	需求描述
A1	保持持续专注	A5	信息分类识记
A2	警觉异样信息	A6	记忆逻辑连贯
A3	情感语义感知	A7	分割记忆任务
A4	多重通道感知	A8	符号识别性高

需求	权重	优先级
A₁	0.253	1
A₂	0.124	4
A₃	0.145	3
A₄	0.032	8
A₅	0.172	2
A₆	0.098	6
A₇	0.112	5
A₈	0.064	7