SHB: Type I (EXP): High Accuracy Motion Analysis using Commodity Depth Camera for Clinical Lower-Extremity Assessment

SHB：I 型 (EXP)：使用商品深度相机进行高精度运动分析，进行临床下肢评估

• 批准号: 1231545
• 负责人: Ruigang Yang
• 金额: $ 56.63万
• 依托单位: University of Kentucky Research Foundation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1231545&HistoricalAwards=false
• 关键词: SHB; Type; EXP; Accuracy; Motion

AbstractPhysical therapy has been widely adopted to treat a wide range of medical conditions, from disabilities, injuries, to crippling diseases such as arthritis, lower back pain, or cerebral palsy. A central issue in physical therapy is the assessment of a patient's kinematic performance. With technology advancement, physical therapists can now utilize commercial motion capture (mocap) system to quantify the 3D mechanics common to many conditions they treat. The 3D kinematic feedback leads to more accurate diagnosis and faster progression. Unfortunately the current state of the art for technology to measure 3D motion is expensive, cumbersome, and not widely available to physical therapists. Thus a strong need remains for the development of a portable, low cost, mocap system to give physical therapists precise 3D measurements of movement dysfunction. This research aims to use the depth information from a single depth camera (SDC) to capture high-accuracy motion data comparable to that from a commercial mocap system. While depth-camera-based pose tracking solutions exist, such as the Kinect system from Microsoft, medical assessment demands almost an order-high accuracy than that for digital entertainment. Based on prior medical studies, this project's goal is to achieve a positional error of less than 10mm and angular error less than 1 degree. That is four to 10 times better than the current state of the art in SDC mocap. For the scope of this project, a new motion capture framework will be developed and thoroughly evaluated for medical applications, in particular to help physician, physical therapists, and other medical professionals to diagnosis, treat, and monitor patients with movement disorders in the lower-extremity.

物理治疗已被广泛采用，以治疗各种医疗条件，从残疾，受伤，以致残性疾病，如关节炎，腰痛，或脑瘫。物理治疗中的一个中心问题是评估患者的运动学表现。随着技术的进步，物理治疗师现在可以利用商业运动捕捉（mocap）系统来量化他们治疗的许多疾病的3D力学。3D运动反馈导致更准确的诊断和更快的进展。不幸的是，测量3D运动的技术的当前状态是昂贵的、笨重的，并且不能被物理治疗师广泛使用。因此，仍然强烈需要开发便携式、低成本的mocap系统，以给予物理治疗师运动功能障碍的精确3D测量。本研究的目的是使用来自单个深度相机（SDC）的深度信息来捕获与商业mocap系统相当的高精度运动数据。虽然存在基于深度相机的姿势跟踪解决方案，例如微软的Kinect系统，但医疗评估需要比数字娱乐高出几乎一个数量级的准确度。基于先前的医学研究，该项目的目标是实现小于10mm的位置误差和小于1度的角度误差。这比SDC mocap的当前技术水平好4到10倍。 在该项目的范围内，将开发一个新的运动捕捉框架，并对医疗应用进行全面评估，特别是帮助医生，物理治疗师和其他医疗专业人员诊断，治疗和监测下肢运动障碍患者。