Wegner Stephan, Lohmeyer Quentin, Wahlen Dimitri, Neumann Sandra, Groebli Jean-Claude, Meboldt Mirko
Product Development Group Zurich, Institute of Design, Materials and Fabrication, Department of Mechanical and Process Engineering, Swiss Federal Institute of Technology in Zurich, Zürich, Switzerland.
Peripal AG, Zürich, Switzerland.
JMIR Hum Factors. 2020 Jun 3;7(2):e15581. doi: 10.2196/15581.
In order to give a wide range of people the opportunity to ensure and support home care, one approach is to develop medical devices that are as user-friendly as possible. This allows nonexperts to use medical devices that were originally too complicated to use. For a user-centric development of such medical devices, it is essential to understand which user interface design best supports patients, caregivers, and health care professionals.
Using the benefits of mobile eye tracking, this work aims to gain a deeper understanding of the challenges of user cognition. As a consequence, its goal is to identify the obstacles to the usability of the features of two different designs of a single medical device user interface. The medical device is a patient assistance device for home use in peritoneal dialysis therapy.
A total of 16 participants, with a subset of seniors (8/16, mean age 73.7 years) and young adults (8/16, mean age 25.0 years), were recruited and participated in this study. The handling cycle consisted of seven main tasks. Data analysis started with the analysis of task effectiveness for searching for error-related tasks. Subsequently, the in-depth gaze data analysis focused on these identified critical tasks. In order to understand the challenges of user cognition in critical tasks, gaze data were analyzed with respect to individual user interface features of the medical device system. Therefore, it focused on the two dimensions of dwell time and fixation duration of the gaze.
In total, 97% of the handling steps for design 1 and 96% for design 2 were performed correctly, with the main challenges being task 1 insert, task 2 connect, and task 6 disconnect for both designs. In order to understand the two analyzed dimensions of the physiological measurements simultaneously, the authors propose a new graphical representation. It distinguishes four different patterns to compare the eye movements associated with the two designs. The patterns identified for the critical tasks are consistent with the results of the task performance.
This study showed that mobile eye tracking provides insights into information processing in intensive handling tasks related to individual user interface features. The evaluation of each feature of the user interface promises an optimal design by combining the best found features. In this way, manufacturers are able to develop products that can be used by untrained people without prior knowledge. This would allow home care to be provided not only by highly qualified nurses and caregivers, but also by patients themselves, partners, children, or neighbors.
为了让更多人有机会确保和支持家庭护理，一种方法是开发尽可能用户友好的医疗设备。这使得非专业人员能够使用原本过于复杂而无法操作的医疗设备。对于以用户为中心开发此类医疗设备而言，了解哪种用户界面设计最能支持患者、护理人员和医疗保健专业人员至关重要。
利用移动眼动追踪的优势，这项工作旨在更深入地了解用户认知方面的挑战。因此，其目标是识别单一医疗设备用户界面两种不同设计的功能在可用性方面的障碍。该医疗设备是一种用于腹膜透析治疗家庭使用的患者辅助设备。
总共招募了16名参与者，其中包括一部分老年人（8/16，平均年龄73.7岁）和年轻人（8/16，平均年龄25.0岁），他们参与了本研究。操作流程包括七个主要任务。数据分析首先从分析与错误相关任务的搜索任务有效性开始。随后，深入的注视数据分析聚焦于这些确定的关键任务。为了理解关键任务中用户认知的挑战，针对医疗设备系统的各个用户界面特征对注视数据进行了分析。因此，它聚焦于注视的停留时间和注视持续时间这两个维度。
设计1的97%的操作步骤和设计2的96%的操作步骤执行正确，两种设计的主要挑战都是任务1插入、任务2连接和任务6断开。为了同时理解生理测量的两个分析维度，作者提出了一种新的图形表示法。它区分了四种不同模式来比较与两种设计相关的眼动。为关键任务识别出的模式与任务执行结果一致。
本研究表明，移动眼动追踪为深入了解与各个用户界面特征相关的密集操作任务中的信息处理提供了见解。通过结合找到的最佳特征对用户界面的每个特征进行评估有望实现优化设计。通过这种方式，制造商能够开发出未经培训且无先验知识的人也能使用的产品。这将使家庭护理不仅能够由高素质的护士和护理人员提供，也能由患者自己、伴侣、子女或邻居提供。
