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On motion artifacts arising when integrating inertial sensors into loose clothing such as a working jacket

Michael Lorenz; Rebecca Keilhauer; Takayuki Akiyama; Takehiro Niikura; Didier Stricker; Bertram Taetz; Gabriele Bleser
In: Proceedings of the 9th International Conference on Control, Decision and Information Technologies. International Conference on Control, Decision and Information Technologies (CoDIT-2023), July 3-6, Rom, Italy, IEEE Xplore, 2023.


Inertial human motion capture (IHMC) has become a robust tool to estimate human kinematics in the wild such as industrial facilities. In contrast to optical motion capture, where occlusions might take place, the kinematics of a worker can be continuously provided. This is for instance a prerequisite for an ergonomic assessments of the workers. State-of-the-art IHMC solutions require inertial sensors to be tightly attached to body segments. This requires an additional setup time and lowers the practicability and ease of use when it comes to an industrial application. In contrast, sensors integrated into loose clothing such as a working jacket, may yield corrupted kinematics estimates due to the additional motion of loose clothing. In this work we present a study of orientations deviations obtained from kinematics estimates using tightly attached inertial sensors and into a working jacket integrated ones. We performed a quantitative analysis using data from the two hardware setups worn by 19 subjects performing different industry related tasks and measures of their body shapes. Using this data we approximated probability distributions of the deviation angles for each person and body segment. Applying different statistical measures we could gain insights to questions like, how severe orientation deviations are, if there is an influence of body shapes on th


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