Extreme Learning Machine/Finite Impulse Response Filter and Vision Data-Assisted Inertial Navigation System-Based Human Motion Capture.

Yuan Xu, Rui Gao, Ahong Yang, Kun Liang, Zhongwei Shi, Mingxu Sun, Tao Shen

Abstract read

In one paragraph

Article in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Adaptive Expectation-Maximization-Based Kalman Filter/Finite Impulse Response Filter for MEMS-INS-Based Posture Capture of Human Upper Limbs.Micromachines · 2024
Article

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yuan XuSchool of Electrical Engineering, University of Jinan, Jinan 250022, China.ORCID 0000-0002-5966-945X

Rui GaoSchool of Electrical Engineering, University of Jinan, Jinan 250022, China.

Ahong YangSchool of Music, University of Jinan, Jinan 250022, China.

Kun LiangSchool of Electrical Engineering, University of Jinan, Jinan 250022, China.

Zhongwei ShiSchool of Electrical Engineering, University of Jinan, Jinan 250022, China.

Mingxu SunSchool of Electrical Engineering, University of Jinan, Jinan 250022, China.

Tao ShenSchool of Electrical Engineering, University of Jinan, Jinan 250022, China.

Funding

Shandong Natural Science Foundation ZR2023MF121 and ZR2020MF067the 2022 Shandong Province Science and Technology Small 268 and Medium Enterprises Innovation Ability Enhancement Project 2022TSGC2037

6 · The paper itself

Abstract

To obtain accurate position information, herein, a one-assistant method involving the fusion of extreme learning machine (ELM)/finite impulse response (FIR) filters and vision data is proposed for inertial navigation system (INS)-based human motion capture. In the proposed method, when vision is available, the vision-based human position is considered as input to an FIR filter that accurately outputs the human position. Meanwhile, another FIR filter outputs the human position using INS data. ELM is used to build mapping between the output of the FIR filter and the corresponding error. When vision data are unavailable, FIR is used to provide the human posture and ELM is used to provide its estimation error built in the abovementioned stage. In the right-arm elbow, the proposed method can improve the cumulative distribution functions (CDFs) of the position errors by about 12.71%, which shows the effectiveness of the proposed method.

Indexed as

ELMFIRhuman positionINSvision

Identifiers

PMID38004945

DOI10.3390/mi14112088

PMCPMC10673149

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.