School of Health Sciences, University of Aveiro (ESSUA), Campus Universitário de Santiago, Edifício 30, Agras do Crasto - Campus Universitário de Santiago, 3810-193 Aveiro, Portugal.
Comput Biol Med. 2013 Dec;43(12):2205-13. doi: 10.1016/j.compbiomed.2013.10.010. Epub 2013 Oct 17.
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±6.9min). 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.
计算机屏幕视频（CSVs）和用户面部表情视频（FEVs）被推荐用于评估系统性能。然而，在临床研究领域，通常无法使用结合这两种方法的软件。Observer-XT 软件常用于临床研究以评估人类行为。因此，本研究报告了结合 CSV 和 FEV 来评估图形用户界面（GUI）的方法。八名物理治疗师在 GUI 中输入临床信息，同时收集 CSV 和 FEV。使用 Observer-XT-10.5 分析 FEV 中发现的一系列行为的频率和持续时间。同时，手动记录 CSV 中可用性问题的频率和持续时间。还将 CSV 和 FEV 的时间线进行匹配以验证组合。FEV 的分析结果表明，用户行为中观察到的最常见类别是与屏幕的眼神接触（ECS，32±9），而口头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。大多数问题是通过口头交流（45.8%）和 ECS（40.8%）报告的。“误报”和“漏报”没有引起可量化的反应，面部表情问题主要与用户在与界面交互时缺乏熟悉感（55.4%）有关。这些发现鼓励使用 Observer-XT-10.5 进行小型可用性测试，因为它通过结合方法可以识别出出现的问题群组。但是，为了验证系统的最终版本，应该使用专门的软件进行进一步验证。
