Abstract
This paper presents the development of a system to estimate the attitude (inclination and orientation) and joint angles between two consecutive segments of the human body, using only accelerometers and gyroscopes. A Markov approach is used where the jumps are chosen according to the type of observation carried out in the system, which can be: (a) based on both segments of the body (nominal), (b) based on the segment with the lowest dynamic acceleration index (local). In contrast to previous studies that use Markov systems with inertial sensors and encoders for absolute angular estimation in lower limb exoskeletons, this research expands the use of this type of system in devices and situations where the encoder is not present.
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Funding
This work was carried out with funding from the Coordination for the Improvement of Higher Education Personnel - Brazil (CAPES) - Project 88882.441241/2019-01 and the São Paulo Research Foundation - Brazil (FAPESP), process 2020/13936-8.
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All authors contributed to the study, conception, and design. Coding, filtering design, and data processing were performed by M.Sc. Edson Francelino, Mr. Mateus Pereira, and Professor Samuel Nogueira. The first draft of the manuscript was written by M.Sc. Edson Francelino and all authors have assisted in editing the manuscript. All authors read and approved the final manuscript.
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Francelino, E., Pereira, M., Inoue, R. et al. Markov System with Self-Aligning Joint Constraint to Estimate Attitude and Joint Angles Between Two Consecutive Segments. J Intell Robot Syst 104, 43 (2022). https://doi.org/10.1007/s10846-022-01572-w
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DOI: https://doi.org/10.1007/s10846-022-01572-w