Novel human computer interaction methods and algorithms for medical applications

医疗应用的新型人机交互方法和算法

• 批准号: RGPIN-2015-05664
• 负责人: Atkins, Stella
• 金额: $ 2.62万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=613680
• 关键词: Novel; human; computer; interaction; methods

Efficient and effective human-computer interaction is essential for real-time medical applications. My program of research is to develop image processing algorithms and human computer interaction (HCI) techniques, with the long-term applied goal of expanding the role of smartphones into mobile healthcare applications. In the short-term, I will perform research in two distinct, complementary research areas: image analysis algorithms and eye tracking. Two important medical areas will provide context and data for this fundamental research: dermatology (skin) image analysis, and laparoscopic (keyhole) surgery training. With wearable eye trackers and augmented reality displays integrated into smartphones, these research areas will merge, by developing eye tracking and pupil responses as novel interaction controls for smartphone apps. Image Analysis: Mole images acquired with a magnifying dermoscope attached to a smartphone camera can show several textural features just below the skin surface, not visible to the naked eye. Sophisticated dermoscopy image analysis algorithms will be developed and extended for application in a mole imaging smartphone app, to provide detailed quantitative analysis about these textural features. Image registration algorithms will be developed to identify changes in skin lesions over time. Interactive functions will be investigated to allow users to identify where the image is taken on the body and to monitor changes over time. Eyegaze tracking: In laparoscopic surgery training, the surgeon looks at the surgery scene through a remote monitor display, and computer simulators are often used to teach novices expert strategies for eye-hand coordination. Eyegaze responses can differentiate novices and experts in surgery training, and I plan to develop new training methods based on so-called “gaze training”, which encourages novices to adapt the eyegaze strategies of experts during eye-hand coordination tasks. Surgery training simulators will be developed for smartphones enhanced with eye tracking and hand motion sensors, employing novel interaction methods based on eyegaze glances, blinks and fixations. Furthermore, pupil responses, which provide insights into the physiological state of the user, can be used to monitor the state of the user while performing surgery simulations. This research will advance and merge the fields of image analysis and human computer interaction.

高效和有效的人机交互对于实时医疗应用至关重要。我的研究计划是开发图像处理算法和人机交互（HCI）技术，长期应用目标是将智能手机的作用扩展到移动的医疗保健应用中。在短期内，我将在两个不同的，互补的研究领域进行研究：图像分析算法和眼动跟踪。两个重要的医学领域将为这项基础研究提供背景和数据：皮肤病学（皮肤）图像分析和腹腔镜（锁孔）手术培训。随着可穿戴眼动仪和增强现实显示器集成到智能手机中，这些研究领域将合并，通过开发眼动跟踪和瞳孔反应作为智能手机应用程序的新型交互控制。 图像分析：用连接到智能手机摄像头的放大皮肤镜获取的鼹鼠图像可以显示皮肤表面下方的几个纹理特征，肉眼不可见。将开发和扩展复杂的皮肤镜图像分析算法，以应用于痣成像智能手机应用程序，以提供有关这些纹理特征的详细定量分析。将开发图像配准算法，以识别皮肤病变随时间的变化。将对交互功能进行调查，以使用户能够识别图像在身体上的位置，并监测随着时间的推移而发生的变化。 视线追踪：在腹腔镜手术培训中，外科医生通过远程监视器显示器查看手术场景，计算机模拟器通常用于教授新手眼手协调的专家策略。在手术训练中，目光反应可以区分新手和专家，我计划开发基于所谓的“凝视训练”的新训练方法，该方法鼓励新手在眼手协调任务中适应专家的目光策略。将为智能手机开发手术训练模拟器，增强眼球跟踪和手部运动传感器，采用基于目光扫视、眨眼和注视的新型交互方法。此外，提供对用户的生理状态的洞察的瞳孔响应可以用于在执行手术模拟的同时监测用户的状态。 这项研究将推进和融合图像分析和人机交互领域。