步态和姿态摇摆分析,一个多模态系统

Hafsa Ismail
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引用次数: 3

摘要

在跌倒发生之前发现它将对老年人的生活产生积极影响。虽然跌倒的主要原因与姿势摇摆和行走有关,但确定其中一项或两项活动的异常情况将有助于预测跌倒的可能性。需要一种便携式步态和姿势摆动分析系统,它可以为个人提供真实世界中步态变化和质量的实时信息,而不仅仅是在实验室中。在这个研究项目中,我的目标是建立一个多模态系统,找到视觉提取的特征与加速度计和力板数据之间的相关性,以确定一般的步态和身体摆动模式。然后,这些信息被用来评估与标准年龄和性别相关模式的差异,以及随时间的任何变化。这可以提供一个更广泛的健康和衰老和疾病功能的核心指标。
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Gait and Postural Sway Analysis, A Multi-Modal System
Detecting a fall before it actually happens will positively affect lives of the elderly. While the main causes of falling are related to postural sway and walking, determining abnormalities in one of these activities or both of them would be informative to predicting the fall probability. A need exists for a portable gait and postural sway analysis system that can provide individuals with real-time information about changes and quality of gait in the real world, not just in a laboratory. In this research project I aim to build a multi-modal system that finds the correlation between vision extracted features and accelerometer and force plate data to determine a general gait and body sway pattern. Then this information is used to assess a difference to normative age and gender relevant patterns as well as any changes over time. This could provide a core indicator of broader health and function in ageing and disease.
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