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Usability testing of a respiratory interface using computer screen and facial expressions videos

机译:使用计算机屏幕和面部表情视频对呼吸界面进行可用性测试

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Computer screen videos (CSVs) and users' facial expressions videos (FEVs) are recommended to evaluate systems performance. However, software combining both methods is often non-accessible in clinical research fields. The Observer-XT software is commonly used for clinical research to assess human behaviours. Thus, this study reports on the combination of CSVs and FEVs, to evaluate a graphical user interface (GUI).Eight physiotherapists entered clinical information in the GUI while CSVs and FEVs were collected. The frequency and duration of a list of behaviours found in FEVs were analysed using the Observer-XT-10.5. Simultaneously, the frequency and duration of usability problems of CSVs were manually registered. CSVs and FEVs timelines were also matched to verify combinations.The analysis of FEVs revealed that the category most frequently observed in users behaviour was the eye contact with the screen (ECS, 32±9) whilst verbal communication achieved the highest duration (14.8±6.9. min). Regarding the CSVs, 64 problems, related with the interface (73%) and the user (27%), were found. In total, 135 usability problems were identified by combining both methods. The majority were reported through verbal communication (45.8%) and ECS (40.8%). "False alarms" and "misses" did not cause quantifiable reactions and the facial expressions problems were mainly related with the lack of familiarity (55.4%) felt by users when interacting with the interface.These findings encourage the use of Observer-XT-10.5 to conduct small usability sessions, as it identifies emergent groups of problems by combining methods. However, to validate final versions of systems further validation should be conducted using specialized software.
机译:建议使用计算机屏幕视频(CSV)和用户面部表情视频(FEV)来评估系统性能。但是,结合这两种方法的软件在临床研究领域通常是不可访问的。 Observer-XT软件通常用于临床研究,以评估人类行为。因此,本研究报告了CSV和FEV的组合,以评估图形用户界面(GUI)。八位理疗师在收集CSV和FEV的同时在GUI中输入了临床信息。使用Observer-XT-10.5分析了在FEV中发现的一系列行为的频率和持续时间。同时,手动记录了CSV的可用性问题的频率和持续时间。 CSV和FEV时间轴也匹配以验证组合.FEV的分析显示,用户行为中最常观察到的类别是与屏幕的目光接触(ECS,32±9),而言语交流的持续时间最长(14.8±6.9)分钟)。关于CSV,发现与界面(73%)和用户(27%)相关的64个问题。通过结合两种方法,总共确定了135个可用性问题。多数通过口头交流(45.8%)和ECS(40.8%)报告。 “虚假警报”和“遗漏”没有引起可量化的反应,面部表情问题主要与用户与界面进行交互时感到不熟悉(55.4%)有关。这些发现鼓励使用Observer-XT-10.5进行小型可用性会议,因为它可以通过组合方法识别出现的问题组。但是,要验证系统的最终版本,应使用专用软件进行进一步验证。

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