Evaluating the efficacy of singular spectrum transformation in detecting working posture changes in a time series
In the current workplace, most manual labor is composed of high-frequency tasks with low physical workloads. Moreover, traditional ergonomic evaluation methods often have difficulty identifying slight variations in working postures and physical workloads in manual tasks. The aim of this study is to...
Guardado en:
Autores principales: | Kazuki HIRANAI, Akisue KURAMOTO, Akihiko SEO |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
The Japan Society of Mechanical Engineers
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/0c237e6ac40b4a6b97bc970033b16974 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Evaluation of time-varying working posture based on interjoint coordination features extracted from sparse structure learning
por: Kazuki HIRANAI, et al.
Publicado: (2021) -
An Application of Hybrid Forecasting Singular Spectrum Analysis – Extreme Learning Machine Method in Foreign Tourists Forecasting
por: Muhammad Fajar
Publicado: (2019) -
An Ergonomic Assessment of Different Postures and Children Risk during Evacuations
por: Xiaohu Jia, et al.
Publicado: (2021) -
Remarks on the mutual singularity of multifractal measures
por: Selmi,Bilel
Publicado: (2021) -
Enable Fair Proof-of-Work (PoW) Consensus for Blockchains in IoT by Miner Twins (MinT)
por: Qian Qu, et al.
Publicado: (2021)