VR Systems for Body Image and Body Schema

在新兴的具身认知领域的最新研究表明，理解技术影响我们的物理/生理因素的程度以及我们对身体的假设如何影响我们设计技术的方式是相互重要的。因此，研究身体图式和身体意象的基本过程变得越来越重要。身体图式包括负责典型的无意识过程（如姿势和运动）的过程的集合。身体意象指的是我们对自己身体的态度和信念，这些态度和信念会随着时间的推移而改变，或者当我们面临残疾或疾病时。身体图式和身体意象作为连续的、相互影响的过程发挥作用，提供关于用户的心理生理状态的重要信息。 这一建议旨在促进对身体图式和身体意象的基本人类过程的日益重要的研究，特别是当它们随着时间的推移而变化时。我们建议：（i）通过对身体图式和身体图像的相关关联进行抽象和建模来研究身体图式和身体图像的计算，（ii）识别身体图式和图像的关系，所述身体图式和图像一起指示可变的心理生理用户状态，（ii）开发与改变的用户状态相关的可视化，最初在VR化身中用于老年人的运动范围研究，（iii）开发使得能够对身体图像数据进行用户注释的界面，（iv）开发用于捕获用户状态数据的准确可重复性的方法，（v）可视化可变时间范围的聚合，用于以后对用户的心理生理状态的纵向数据的分析，以及（vi）开发经验评估的方法。这项研究的长期目标是双重的：1。确定设计可变体模式和图像数据的计算模型所需的理论基础和形式主义。2.制定评估方法，以提供有效性的经验证据。

Recent research in the emerging field of embodied cognition demonstrates the mutual importance of understanding the extent to which technologies affect our physical/physiological factors, and how our assumptions about our bodies affect the ways we design technology. Thus, it is increasingly important to study the fundamental processes of body schemas and body images. A body schema comprises the collection of processes that are responsible for typically non-conscious processes such as posture and movement. A body image refers to attitudes and beliefs we have about our body, which change over time, or when we face disability or disease. Body schema and body image function as continuous, mutually influential processes that provide important information about a user's psychophysiological state. This proposal aims to contribute to increasingly important research on fundamental human processes of body schema and body image, particularly as they change over time. We propose to: (i) investigate computation of body schema and body image by abstracting and modeling relevant correlates of each, (ii) identify relationships of body schema and image that together indicate variable psychophysiological user states, (ii) develop visualizations that correlate to changing user states, initially in VR avatars for range of movement studies in seniors, (iii) develop an interface that enables user annotations of body image data, (iv) develop methods for accurate repeatability of capturing user state data, (v) visualize aggregation of variable timeframes for later analysis of longitudinal data of users' psychophysiological states and (vi) develop methods of empirical assessment. The long-term objective of this research is two-fold: 1. To identify the theoretical underpinnings and formalisms necessary to devise computational models of variable body schema and image data. 2. To develop methods of assessment to provide empirical evidence of effectiveness.