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 longterm trend. That can give the appropriate treatment regimen matching the development of the disease.
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