Motion Analysis Using Global Navigation Satellite System and Physiological Data

نویسندگان

چکیده

Motion analysis by wearable sensors forms a very important research topic with general mathematical background and applications in different areas including engineering, robotics, neurology. This paper presents the use of global navigation satellite system (GNSS) for detecting recording position moving body simultaneous acquisition signals from further sensors. The application is related to monitoring physical activity heart rate dynamics during run at route segments slopes changing speed, forming an alternative on treadmill ergometer. proposed computational method includes digital methods data preprocessing, time synchronization, resampling enable their correlation, feature extraction both frequency domains, classification. datasets include acquired ten experimental runs selected area. detection patterns motion segmenting analysing GNSS data, evaluating patterns, classifying under terrain conditions. classification provides comparison neural networks, support vector machine, Bayesian, k -nearest neighbour methods. highest accuracy 93.3 % was achieved using combined features two-layer network into three classes slopes. graphical user interface suggest efficiency multi-channel multi-dimensional signal processing rehabilitation, fitness movement monitoring, neurology, cardiology, robotic systems as well.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2023

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2023.3270102