一种评估智能手机键盘设计的评估方法和工具包
Summary
所提出的协议集成了各种评估方法，并演示了一种评估智能手机键盘设计的方法。建议将英文字符匹配的对作为输入材料，并将两个键之间的过渡时间用作因变量。
Abstract
键盘输入在与广大用户群的人机交互中发挥了至关重要的作用，键盘设计一直是智能设备研究的基本对象之一。随着屏幕技术的发展，智能手机可以收集更精确的数据和指示器，以深入评估键盘设计。手机屏幕的放大导致了不尽如人意的输入体验和手指疼痛，特别是对于单手输入。输入效率和舒适性引起了研究人员和设计师的注意，并提出了带有尺寸可调按钮的曲面键盘，大致符合拇指的生理结构，以优化大屏幕智能手机上的单手使用。然而，它的实际影响仍然模糊不清。因此，该协议展示了一种通用的总结方法，通过自主开发的软件评估曲面QWERTY键盘设计在5英寸智能手机上的效果，该软件具有详细的变量，包括客观行为数据，主观反馈以及每个接触点的坐标数据。关于评估虚拟键盘的现有文献足够多;然而，其中只有少数几个系统地总结了评估方法和过程并进行了反思。因此，该协议填补了这一空白，并提出了一种系统评估键盘设计的过程和方法，以及用于分析和可视化的可用代码。它不需要额外或昂贵的设备，并且易于进行和操作。此外，该协议还有助于获得设计缺点的潜在原因，并启发设计的优化。总之，这种具有开源资源的协议不仅可以成为一种课堂演示实验，以激励新手开始学习，而且还有助于改善用户体验和输入法编辑器公司的收入。
Introduction
键盘输入是人机交互的主流方式1，2，随着智能手机的普及，键盘输入获得了数十亿用户。2019年，全球智能手机普及率已达41.5%3，而美国是普及率最高的国家，则高达79.1%4 。截至2020年第一季度，搜狗手机键盘日活跃用户约4.8亿5.截至2020年5月6日，谷歌Gboard的下载量已超过10亿次6。
不令人满意的键盘输入体验随着手机屏幕的放大而增加。虽然放大后的屏幕旨在改善观看体验，但它改变了智能手机的重力、尺寸和重量，导致用户反复改变握持姿势以到达偏远地区（例如，右撇子用户的按钮A和Q），从而导致输入效率低下。肌肉拉伸可能导致使用者患有肌肉骨骼疾病，手部疼痛和不同类型的疾病（例如，腕管综合征，拇指骨关节炎和拇指腱鞘炎7，8，9，10）。喜欢单手使用的用户条件更差11，12.
因此，键盘设计的评估和优化已成为心理学、技术和人体工程学研究的热点。输入法编辑器（IME）公司和研究人员不断提出可变键盘设计和概念，以优化输入体验和效率，包括布局更改和字符重新排序的键盘：Microsoft WordFlow Keyboard13，Gloryof Kings14中的功能按钮区域，IJQWERTY15和Quasi-QWERTY16。
现有的键盘设计评估方法因研究者而异，除了几个高度接受的指标外，提出了更准确的指标。然而，对于各种指标，没有提供一个总结和系统的协议来演示评估和分析键盘设计的过程。菲茨定律17及其扩展版FFitts定律18描述了人机交互，被广泛采用来评估键盘性能19，20，21，22。此外，提出了拇指的功能区域以改善键盘设计，并且它描述了一个弯曲的运动区域，以便拇指舒适地完成输入任务23。基于这些理论，包括每分钟单词数，单词错误率和主观反馈（感知可用性，感知性能，感知速度，主观工作量，感知的劳累和疼痛以及使用意图等）在内的指标被高度采用，在以前的研究中部分使用24，25，26，27，28，29 除了建模和模拟方法。此外，近年来还使用了每个按钮上接触点的拟合椭圆及其偏移量30，31来研究输入事件的准确性能。此外，还采用皮肤电反应、心率、肌电活动、手势和身体运动32、33、34、35等方式直接或间接评价用户的肌肉疲劳、舒适度和满意度。然而，这些不同的方法缺乏对所用指标的适当性的反思，新手研究人员可能会混淆为他或她的研究选择适当的指标。
关于键盘设计的研究也很容易进行，操作和分析。随着屏幕技术的蓬勃发展，可以很容易地收集更多的行为数据来深入评估键盘设计（例如，两个键之间的转换时间和每个接触点的坐标数据）。基于上述数据，研究人员可以精确地探索键盘设计的细节，并分析其缺点和优点。与其他人机交互研究相比，便携式智能手机键盘设计的研究也具有很高的应用价值，因为其庞大的用户群不需要昂贵的设备，复杂的材料或巨大的实验室空间。关于研究的问卷，量表和Python脚本是开源的，易于访问。
本研究的目的是总结以前的方法，以展示一种系统，精确和通用的协议来评估和分析智能手机上的键盘设计。示例实验和结果旨在展示与传统QWERTY键盘相比，带有大小可调按钮的曲面QWERTY键盘是否可以优化5英寸智能手机上单手输入的输入体验，并分享数据分析的可视化方法和Python脚本。
Protocol
Representative Results
Discussion
在这项研究中，基于屏幕技术的发展，我们提出了一个总结和通用的键盘设计评估方案，以系统，准确地评估键盘设计。先前研究中的现有指标和方法，由英文字符匹配的对以及两个键之间的过渡时间被集成和修改以生成有效的协议。
在此协议中需要注意几个关键点。变量和指标的选择至关重要，因为它们决定了分析的视角，并且可以在键盘设计评估实验的后期阶段使用它?…
Disclosures
The authors have nothing to disclose.
Acknowledgements
该研究得到了清华大学倡议科学研究计划（智能设备上曲面键盘的人体工程学设计）的支持。作者感谢刘天宇对图形的善意建议和编码帮助。
Materials
| Changxiang 6S smartphone | Huawei | Smartphone used in the examplar study | |
| Curved QWERTY keyboard software | Tsinghua University | Developed by authors | |
| SPSS software | IBM | Data analysis software | |
| G*Power software | Heinrich-Heine-Universität Düsseldorf | Sample size calculation | |
| E4 portable wireless wristband | Empatica | Recording galvanic skin response and heart rate | |
| Arqus | Qualysis | Motion capture camera platform | |
| Passive marker | Qualysis | Appropriate sizes: 2.5 mm, 4 mm, and 6.5 mm | |
| Trigno sEMG | Delsys | Recording electromyographic activity | |
| Visual Studio Code | Microsoft | Python editor |
References
- Lee, S., Zhai, S. The performance of touch screen soft buttons. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2009).
- Smith, B. A., Bi, X., Zhai, S. Optimizing touchscreen keyboards for gesture typing. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems. , (2015).
- . Global smartphone penetration rate as share of population from 2016 to 2020 [Fact sheet] Available from: https://www.statista.com/statistics/203734/global-smartphone-penetration-per-capita-since-2005 (2020)
- Top Countries by Smartphone Users [Fact sheet]. Newzoo Available from: https://newzoo.com/insights/rankings/top-countries-by-smartphone-penetration-and-users (2019)
- Gboard – the Google Keyboard [Press release]. Google Play Available from: https://play.google.com/store/apps/details?id=com.google.android.inputmethod.latin (2020)
- Eitivipart, A. C., Viriyarojanakul, S., Redhead, L. Musculoskeletal disorder and pain associated with smartphone use: A systematic review of biomechanical evidence. Hong Kong Physiotherapy Journal. 38 (2), 77-90 (2018).
- Chang, J., Choi, B., Tjolleng, A., Jung, K. Effects of button position on a soft keyboard: Muscle activity, touch time, and discomfort in two-thumb text entry. Applied Ergonomics. 60, 282-292 (2017).
- Gehrmann, S. V., et al. Motion deficit of the thumb in CMC joint arthritis. Journal of Hand Surgery. 35 (9), 1449-1453 (2010).
- Kim, G., Ahn, C. S., Jeon, H. W., Lee, C. R. Effects of the Use of Smartphones on Pain and Muscle Fatigue in the Upper Extremity. Journal of Physical Therapy Science. 24 (12), 1255-1258 (2012).
- Girouard, A., et al. One-handed bend interactions with deformable smartphones. Proceedings of the 33rd annual ACM conference on human factors in computing systems. , (2015).
- Lee, M., Hong, Y., Lee, S., Won, J., Yang, J., Park, S. The effects of smartphone use on upper extremity muscle activity and pain threshold. Journal of Physical Therapy Science. 27 (6), 1743-1745 (2015).
- Word Flow keyboard [Press release]. Microsoft Garage Available from: https://www.microsoft.com/en-us/garage/profiles/word-flow-keyboard/ (2020)
- The glory of kings [Press release]. Tencent Games Available from: https://pvp.qq.com/ (2020)
- Bi, X., Zhai, S. Ijqwerty: what difference does one key change make? Gesture typing keyboard optimization bounded by one key position change from qwerty. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems. , (2016).
- Bi, X., Smith, B. A., Zhai, S. Quasi-qwerty soft keyboard optimization. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2010).
- Fitts, P. The information capacity of the human motor system is controlled by the amplitude of movement. Journal of Experimental Psychology. 47, 381-391 (1954).
- Bi, X., Li, Y., Zhai, S. FFitts law: modeling finger touch with fitts’ law. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2013).
- Dunlop, M., Levine, J. Multidimensional pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2012).
- Li, Y., Chen, L., Goonetilleke, R. S. A heuristic-based approach to optimize keyboard design for single-finger keying applications. International Journal of Industrial Ergonomics. 36 (8), 695-704 (2006).
- Benligiray, B., Topal, C., Akinlar, C. SliceType: fast gaze typing with a merging keyboard. Journal on Multimodal User Interfaces. 13 (4), 321-334 (2019).
- Wang, Y., Ai, H., Liang, Q., Chang, W., He, J. How to optimize the input efficiency of keyboard buttons in large smartphone? A comparison of curved keyboard and keyboard area size [Conference presentation]. International Conference on Human-Computer Interaction. , (2019).
- Bergstrom-Lehtovirta, J., Oulasvirta, A. Modeling the functional area of the thumb on mobile touchscreen surfaces. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , (2014).
- Brooke, J. SUS: A retrospective. Journal of Usability Studies. 8 (2), 29-40 (2013).
- Borg, G. Principles in scaling pain and the Borg CR Scales. Psychologica. 37, 35-47 (2004).
- Hart, S. G., Staveland, L. E., Hancock, P. A., Meshkati, N. Development of NASA-TLX (task load index): results of empirical and theoretical research. Human mental workload. , 139-183 (1988).
- Trudeau, M. B., Asakawa, D. S., Jindrich, D. L., Dennerlein, J. T. Two-handed grip on a mobile phone affords greater thumb motor performance, decreased variability, and a more extended thumb posture than a one-handed grip. Applied Ergonomics. 52, 24-28 (2016).
- Turner, C. J., Chaparro, B. S., He, J. Text input on a smartwatch qwerty keyboard: tap vs. trace. International Journal of Human Computer Interaction. 33 (1-3), 143-150 (2017).
- Zhai, S., Kristensson, P. O. The word-gesture keyboard: reimagining keyboard interaction. Communications of the ACM. 55 (9), 91-101 (2012).
- Azenkot, S., Zhai, S. Touch behavior with different postures on soft smartphone keyboards. Proceedings of the 14th international conference on Human-computer interaction with mobile devices and services. , (2012).
- Yi, X., Yu, C., Shi, W., Shi, Y. Is it too small?: Investigating the performances and preferences of users when typing on tiny qwerty keyboards. International Journal of Human Computer Studies. 106, 44-62 (2017).
- Li, Y., You, F., Ji, M., You, X. Smartphone text input: effects of experience and phrase complexity on user performance, physiological reaction, and perceived usability. Applied Ergonomics. 80, 200-208 (2019).
- Gerard, M. J., Jones, S. K., Smith, L. A., Thomas, R. E., Wang, T. An ergonomic evaluation of the Kinesis ergonomic computer keyboard. Ergonomics. 37 (10), 1661-1668 (1994).
- Van Galen, G. P., Liesker, H., Haan, A. Effects of a vertical keyboard design on typing performance, user comfort and muscle tension. Applied Ergonomics. 38 (1), 99-107 (2007).
- Baker, N. A., Cham, R., Cidboy, E. H., Cook, J., Redfern, M. S. Kinematics of the fingers and hands during computer keyboard use. Clinical Biomechanics. 22 (1), 34-43 (2007).
- Soukoref, R. W., MacKenzie, I. S. Metrics for text input research: an evaluation of MSD and KSPC, and a new unified error metric. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. , 113-120 (2003).
- Mackenzie, I. S., Soukoreff, R. W. Phrase sets for evaluating text entry techniques. CHI’03 Extended Abstracts on Human Factors in Computing Systems. , 754-755 (2003).
- Trudeau, M. B., Sunderland, E. M., Jindrich, D. L., Dennerlein, J. T., Federici, S. A data-driven design evaluation tool for handheld device soft keyboards. Plos One. 9 (9), 107070 (2014).
- Cao, S., Ho, A., He, J. Modeling and predicting mobile phone touchscreen transcription typing using an integrated cognitive architecture. International Journal of Human-Computer Interaction. 34 (4-6), 544-556 (2018).
