Impact of ISO/TS 20646-1 `Ergonomic Procedures for the Improvement of Local Muscular Workloads' on Work-Related Musculoskeletal Disorders

Ebara, Takeshi; Khuvasanont, Tanavadee; Krungkraiwong, Sudthida; Amornratanapaichit, Ratanaporn; Tachi, Norihide; Takeyama, Hidemaro; Murata, Kazuyo; Takanishi, Toshimasa; Inoue, Tatsuki; Suzumura, Hatsuko; Mori, Midori; Itani, Toru

doi:10.2486/indhealth.45.256

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…(30); 3) affected zones (lumbar zone, dorsal zone, cervical zone, neck, shoulders, forearm, arm, arm, hand), 4) gender, 5) posture 6) working place. Posture analysis was evaluated using the EWA (Ergonomic Workplace Analysis), this is an instrument which allows analysis of the situation at the workplace and is based on work physiology, occupational biomechanics, information psychology, industrial hygiene and the socio-technical model of organization of the work (18).…”

Section: Methodsmentioning

confidence: 99%

Ergonomic factors that cause the presence of pain muscle in students of dentistry

Díaz-Caballero

Gómez-Palencia²,

Díaz-Cárdenas³

2010

Med Oral

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Objective: To identify the ergonomic factors and the presence of muscular pain in dental students of VIII, IX, X semesters presently practicing at the clinics of the College of Dentistry of university of Cartagena, Colombia, South America. Materials and methods: This is a descriptive study carried out in dental students of the VIII, IX, and X semesters which were undergoing clinical practice at the College of Dentistry of University of Cartagena. A convenience sample of 83 students who met the inclusion criteria was taken and those who agreed to participate signed an informed consent. Data collection was obtained by means of a structured questionnaire for ergonomic factors and the presence of pain was identified palpating the muscles object of the study by a physical therapist. The variables evaluated were: presence of pain, affected muscles, affected zones, gender, postures and work environment. Results: The adoption of inadequate postures such as exaggerated flexions or cervical torsions could generate a higher frequency of muscular pain in dental students. The approximating muscle of the thumb showed 11% frequency of pain. The presence of muscular pain was higher for the female group participating in this study. Conclusions: Dentists are prone, since the beginning of their clinical practice as students, to lesions of the skeletal muscle system due to the clinical exercise of the profession, being the most common, muscle pain in the back, neck, shoulders and hands. This would imply initiating an occupational health program promoting healthy lifestyles in their academic environment and their future professional life, at the beginning of their clinical practice in dental school.

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Section: Methodsmentioning

confidence: 99%

Ergonomic factors that cause the presence of pain muscle in students of dentistry

Díaz-Caballero

Gómez-Palencia²,

Díaz-Cárdenas³

2010

Med Oral

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“…In medicine, the MF analysis in the diagnosis of neuromuscular diseases is essential [8]. Also, ergonomics has procedures for reducing local muscular workloads for employers, occupational health-related staff, and workers [9].…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Approach for Upper Limb Fatigue Estimation Based on Wearable Sensors

Otálora,

Segatto,

Monteiro

et al. 2023

Sensors

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Muscle fatigue is defined as a reduced ability to maintain maximal strength during voluntary contraction. It is associated with musculoskeletal disorders that affect workers performing repetitive activities, affecting their performance and well-being. Although electromyography remains the gold standard for measuring muscle fatigue, its limitations in long-term work motivate the use of wearable devices. This article proposes a computational model for estimating muscle fatigue using wearable and non-invasive devices, such as Optical Fiber Sensors (OFSs) and Inertial Measurement Units (IMUs) along the subjective Borg scale. Electromyography (EMG) sensors are used to observe their importance in estimating muscle fatigue and comparing performance in different sensor combinations. This study involves 30 subjects performing a repetitive lifting activity with their dominant arm until reaching muscle fatigue. Muscle activity, elbow angles, and angular and linear velocities, among others, are measured to extract multiple features. Different machine learning algorithms obtain a model that estimates three fatigue states (low, moderate and high). Results showed that between the machine learning classifiers, the LightGBM presented an accuracy of 96.2% in the classification task using all of the sensors with 33 features and 95.4% using only OFS and IMU sensors with 13 features. This demonstrates that elbow angles, wrist velocities, acceleration variations, and compensatory neck movements are essential for estimating muscle fatigue. In conclusion, the resulting model can be used to estimate fatigue during heavy lifting in work environments, having the potential to monitor and prevent muscle fatigue during long working shifts.

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Effects of a Healthy Unit Guidance (HUG) program on work environments and health outcomes among nursing personnel

Songkham¹,

Siriwong

Robson³

2011

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Impact of ISO/TS 20646-1 `Ergonomic Procedures for the Improvement of Local Muscular Workloads' on Work-Related Musculoskeletal Disorders

Cited by 4 publications

References 18 publications

Ergonomic factors that cause the presence of pain muscle in students of dentistry

Ergonomic factors that cause the presence of pain muscle in students of dentistry

Data-Driven Approach for Upper Limb Fatigue Estimation Based on Wearable Sensors

Effects of a Healthy Unit Guidance (HUG) program on work environments and health outcomes among nursing personnel

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