VR Systems for Body Image and Body Schema

用于身体图像和身体模式的 VR 系统

• 批准号: RGPIN-2018-06814
• 负责人: Gromala, Diane
• 金额: $ 2.04万
• 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: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714489
• 关键词: VR; Systems; Body; Image; Schema

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. The focus of proposed body image/body schema research will be on immersive VR. Research in body ownership of VR avatars has led to important findings regarding visual, motor and tactile phenomena, as well as the role of time in how VR users gain a sense of “ownership” of their VR avatars. In essence, this tells us important information about body schema, but far less about body image. Moreover, while this research includes the adoption or ownership of non-human body parts, such as tails, it nevertheless assumes a healthy, normative body. However, certain conditions such as chronic and phantom pain are known to profoundly disturb body image and body schema. Moreover, while VR has been shown to be a form of pain alleviation, the mechanism that may explain this effect is still in its infancy, as are varied outcomes about how long this effect may persist after VR exposure. These are some examples of why it is important to gain a better understanding of how users gain an embodied sense of a VR avatar from a first person perspective - a perspective that includes body image. This proposal aims to contribute to increasingly important research on fundamental human processes of body schema and body image. 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, (iii) develop visualizations that correlate to changing user states, initially in VR avatars for range-of-movement studies in seniors, (iv) develop an interface that enables user annotations of body image data, (v) develop methods for accurate repeatability of capturing user state data, (vi) visualize aggregation of variable time frames for later analysis of longitudinal data of users. 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.

新兴的具身认知领域的最新研究表明， 了解技术在多大程度上影响我们的身体/生理因素，以及我们的身体如何 对我们身体的假设会影响我们设计技术的方式。因此，研究变得越来越重要。 身体图式和身体图像的基本过程 身体图式包括以下内容的集合。 负责典型无意识过程（例如姿势和运动）的过程。 形象是指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，或者当我们面对 身体图式和身体意象作为持续的、相互影响的过程发挥着作用。 提供有关用户心理生理状态的重要信息。 拟议的身体图像/身体图式研究的重点将是沉浸式 VR 对 VR 化身的身体所有权的研究已经得出了有关视觉、运动和触觉现象以及时间在 VR 用户如何获得感觉中的作用的重要发现。本质上，这告诉我们关于身体图式的重要信息，但关于身体形象的信息却少之又少，而且，虽然这项研究包括非人类身体部位的采用或所有权，例如尾巴，尽管如此，它仍然假设身体健康、正常，但众所周知，某些情况（例如慢性疼痛和幻痛）会严重扰乱身体形象和身体图式，而且，虽然 VR 已被证明是一种缓解疼痛的形式，但这一机制可以解释。这种效应仍处于起步阶段，关于这种效应在 VR 暴露后会持续多久的结果也各不相同，这些例子说明了为什么更好地了解用户如何从 VR 头像中获得具体的感觉是很重要的。第一人称视角-a包括身体意象的视角。 该提案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。我们建议： (i) 通过对各自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) 识别共同指示可变心理生理用户状态的身体图式和图像的关系，(iii) 开发与不断变化的用户状态相关的可视化，最初用于老年人运动范围研究的 VR 化身，(iv) 开发一个界面，使用户能够对身体图像数据进行注释，(v) 开发精确重复捕获用户状态数据的方法，(vi) 可视化聚合可变时间范围，以便以后分析用户的纵向数据。 这项研究的长期目标有两个： 1. 确定设计可变身体模式和图像数据的计算模型所需的理论基础和形式。 2. 制定评估方法以提供有效性的经验证据。