Digital filter design of frequency weighting function to measure and assess human vibration

Oh, Han-eum; Park, D.J.; Park, J.P.; Ahn, Se Jin; Jeonge, W.B.

doi:10.3397/1/376436

Cited by 4 publications

(2 citation statements)

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“…erefore, high-pass filter is used to remove low-frequency interference signal (baseline drift). Digital filters are divided into FIR filters and IIR filters [19][20][21]. Because FIR filters are more stable than IIR filters and can achieve linear phase characteristics, this paper uses FIR-based adaptive high-pass filters to remove baseline drift [22,23].…”

Section: Preprocessing Of Surface Electromyography Signal Andmentioning

confidence: 99%

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Dai

2021

Mathematical Problems in Engineering

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Today, while people’s satisfaction with materials is high, the pursuit of health has begun and sports are becoming increasingly important. Volleyball is a good physical and mental exercise, which helps improve the health of the body. However, excessive exercise usually leads to muscle strain and more serious accidents. Therefore, how to effectively prevent excessive fatigue and sports injuries becomes more and more important. In the past, some methods of exercise fatigue detection were mostly self-assessment through some indicators, which lacked real-time and accuracy. With the advancement of smart technology, in order to better detect sports fatigue, smart wearable technology and equipment are used in volleyball. Firstly, surface electromyography signals (sEMG) are collected through wearable technology and equipment. Secondly, the signal is preprocessed to extract features that are conducive to exercise fatigue assessment. Finally, a motion fatigue detection algorithm is designed to identify and classify features and evaluate the motion status in real-time. The simulation results show that it is feasible to collect ECG signals and EMG signals to detect exercise fatigue. The algorithm has good recognition performance, can evaluate exercise conditions in real-time, and prevent fatigue and injury during exercise.

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Section: Preprocessing Of Surface Electromyography Signal Andmentioning

confidence: 99%

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Dai

2021

Mathematical Problems in Engineering

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“…For step profile, the parameter comfort can be quantified by σ as , which is the RMS value of the acceleration a s of the suspended mass, and for the rough road profile by σ a f , which is the RMS value of a s filtered using the ISO 2631-1 W k weighting filter [19]. Safety can be quantified, for both profiles, by σ Ft , which is the RMS value of the force imposed on the tire.…”

Section: Objective Functionmentioning

confidence: 99%

Performance Analysis of an Asymmetric Damper Suspension on Rough Roads and Steps

Ribeiro

2023

Preprint

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This paper analyzes the advantages of employing an asymmetric suspension compared to a symmetric suspension. The road profiles considered are rough roads and steps, and the optimization parameters include comfort and safety. The optimal suspension is achieved using the Cross-Entropy method, and the obtained results for each profile are contradictory. Asymmetric dampers confer specific advantages over symmetric counterparts, notably in their ability to mitigate transient vibrations experienced during steps. However, their advantage becomes less pronounced during steady-state vibrations induced by rough road conditions. The results obtained show that if a suspension is optimized for steps, the resulting configuration is asymmetric. On the other hand, for rough roads, the resulting configuration is symmetric. This disparity indicates that the optimization of an asymmetric suspension must consider a combination of both scenarios.

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Neck/Shoulder Muscle Fatigue of Military Vehicle Drivers Exposed to Whole-Body Vibration on Field Terrain Road

Lee

Park²,

Song

et al. 2020

Int.J Automot. Technol.

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Digital filter design of frequency weighting function to measure and assess human vibration

Cited by 4 publications

References 0 publications

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Application Analysis of Wearable Technology and Equipment Based on Artificial Intelligence in Volleyball

Performance Analysis of an Asymmetric Damper Suspension on Rough Roads and Steps

Neck/Shoulder Muscle Fatigue of Military Vehicle Drivers Exposed to Whole-Body Vibration on Field Terrain Road

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