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The Gait Analysis System Based on the First-person Video for Applications on Home Health Care

机译:基于第一人称视频的步态分析系统在家庭保健中的应用

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Gait can be a concrete manifestation of an individual's athletic traits, but also can become an essential feature of the judgment of the physical condition. Making an accurate gait analysis has become one of the critical medical information needs. However, the measurement and analysis of gait in medical institutions are still mainly based on the visual experience of physicians, or expensive and complicated motion capture system that are not suitable for use in the home environment; and the simple wearable sensors do not provide enough information to assist medical judgment. In this research project, a novel gait analysis method based on an image recorder is proposed, which has the advantages of making the gait analysis more natural and more suitable for the home environment. A more realistic gait profile can be measured without having to be in close contact with the observed body parts like motion capture system or inertial measurement device. This research project, a gait analysis system based on the first-person video will be developed, and the characteristics of captured video will be transformed into the features of clinical medicine. This system will be used in combination with traditional clinical medicine. The experimental results show that the generated measurement information can be correctly converted for clinical medicine using, and is more suitable for home environments. Further, we will cooperate with clinicians to provide a useful evaluation of home exercise rehabilitation and predicting the long-term trend. That can give the appropriate treatment regimen matching the development of the disease.
机译:步态可以是个人运动特征的具体体现,但也可以成为判断身体状况的基本特征。进行准确的步态分析已成为关键的医学信息需求之一。但是,医疗机构中步态的测量和分析仍然主要基于医师的视觉经验,或者是昂贵且复杂的运动捕捉系统,这些系统不适合在家庭环境中使用;并且简单的可穿戴传感器无法提供足够的信息来帮助医学判断。在该研究项目中,提出了一种基于图像记录仪的新型步态分析方法,该方法具有使步态分析更自然,更适合家庭环境的优点。无需与诸如运动捕捉系统或惯性测量设备之类的观察到的身体部位紧密接触,就可以测量出更加逼真的步态轮廓。该研究项目将开发一种基于第一人称视频的步态分析系统,并将捕获的视频的特征转换为临床医学的特征。该系统将与传统的临床医学结合使用。实验结果表明,所生成的测量信息可以正确地用于临床医学,并更适合家庭环境。此外,我们将与临床医生合作,为家庭运动康复提供有用的评估并预测长期趋势。这样可以根据疾病的发展提供适当的治疗方案。

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