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Article summary:
1. Motion capture technology is essential for action recognition, motor function assessment and dexterous human-robot interaction.
2. A wearable motion capture device has been proposed to accurately measure three-dimensional velocity, acceleration, and attitude angles of limbs in dynamic motions.
3. A neural network model has been established to characterize the natural intra-limb coordination for human lower limb and used to determine the thigh motion from the shank motion in human walking and running.
Article analysis:
The article is generally reliable and trustworthy as it provides a detailed description of the proposed wearable motion capture device, its design, data fusion algorithm, and neural network model for intra-limb coordination between shank and thigh motions in human walking and running. The article also provides evidence for its claims by citing relevant research papers in the field of motion capture technology. Furthermore, the article does not contain any promotional content or partiality towards any particular product or company.
However, there are some points that could be improved upon in terms of trustworthiness and reliability. Firstly, the article does not provide any information on possible risks associated with using the proposed device such as potential health hazards due to prolonged use or potential interference with other medical devices. Secondly, while the article cites relevant research papers in support of its claims, it does not explore counterarguments or present both sides equally when discussing various methods for motion capture technology such as optical systems or goniometers. Lastly, while the article mentions that reducing wearing nodes and lightening weights are important considerations for next generation of wearable systems, it does not provide any details on how this can be achieved or what materials can be used to achieve this goal.