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2023 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2023

作者： Aqueveque, Pablo Gutierrez, Manuel Pena, Guisella Germany, Enrique Gomez, Britam Retamal, Gustavo Ortega-Bastidas, Paulina Universidad de Concepción Faculty of Engineering Electrical Engineering Department Concepción Chile Universidad de Concepción Faculty of Biological Sciences Ergonomics Department Concepción Chile Universidad de Santiago de Chile Biomedical Engineering Faculty of Engineering Santiago Chile Universidad de Concepción Faculty of Medicine Kinesiology Department Concepción Chile Universidad Rey Juan Carlos Health Sciences PhD Programme Madrid Spain

ISBN: (纸本)9781665493840

Work-related musculoskeletal disorders is a major problem for worker's health when dealing with repetitive tasks. The Occupational Repetitive Actions Index (OCRA) is one of the most widely used methods for determining upper extremity risk from repetitive actions. Traditional risk assessment consists in observing and recording the entire workday or part of it. This observational assessment depends on the evaluator's expertise, which lead to inter-evaluator variability in the results even for the same job. This paper presents preliminary results of a platform that combines motion capture data with a digitalized OCRA Index method to classify risks under repetitive tasks conditions. Repetitive action tasks were performed in a controlled laboratory environment on ten healthy subjects, where optical and inertial sensors were used to capture movement. Body segment positions, displacements and joint angles were fed into the platform comparing their processing time and reliability. Although results indicate that optical systems have a better performance than inertial sensors for posture evaluation, the last has better practical applicability since optical markers occlusion in the working setup induced measurement errors. In addition, inertial systems are more likely to be used on in real working scenarios due to their ease of use and portability. Finally, inertial sensors combined with the digitized OCRA index method platform effectively reduces 67% of the needed evaluation time compared to traditional observational methods. © 2023 IEEE.

关键词： Risk assessment

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Segmentation of Tumour Regions for Tubule Formation Assessment on Breast Cancer Histopathology Images 11th

Segmentation of Tumour Regions for Tubule Formation Assessme...

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11th International Conference on Robotics, Vision, Signal Processing and Power Applications, RoViSP 2021

作者： Jing, Tan Yee Mustafa, Nazahah Yazid, Haniza Rahman, Khairul Shakir Ab Biomedical Electronic Engineering Programme Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Kampus Alam UniMAP Pauh Putra Arau Perlis02600 Malaysia Department of Pathology Hospital Tuanku Fauziah Kangar Perlis01000 Malaysia

ISBN: (纸本)9789811681288

Breast cancer is the second leading cause of cancer death in women worldwide. In Malaysia, one out of 20 women will develop breast cancer once in their lifetime. Nottingham Histological Grading (NHG) system is widely accepted worldwide as the gold standard in providing the overall grade to breast cancer. Tubule formation is an important breast cancer feature used in the NHG system. Assessment of tubule formation requires pathologist to identify tumour regions. However, colour variation on breast histopathology images could provide nonstandard imaging and influence tumour regions detection. Manual identification of tumour regions using microscope may also vary between pathologists. Thus, automatic segmentation is crucial to detect tumour regions. By eliminating the irrelevant regions on breast histopathology images using automatic segmentation method, pathologist can focus on the tumour regions for further investigation. This study proposed a simple segmentation using global thresholding method to segment tumour regions on breast histopathology images. Partial contrast stretching and median filter were applied as pre-processing to provide better image quality for further segmentation processing. Post-processing using morphological operation and boundary padding were applied to enhance the segmentation results. The proposed method was able to segment the tumour regions on breast histopathology images and obtained accuracy, sensitivity and specificity of 84.22%, 85.83% and 84.89% respectively. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Tumors

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Elucidating of the metabolic impact of risperidone on brain microvascular endothelial cells using untargeted metabolomics-based LC-MS

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Toxicology Reports 2024年 13卷 101691页

作者： Ngamratanapaiboon, Surachai Srikornvit, Napatarin Hongthawonsiri, Patipol Pornchokchai, Krittaboon Wongpitoonmanachai, Siriphattarinya Mo, Jiajun Pholkla, Petchlada Yambangyang, Pracha Duchda, Phichanan Lohwacharin, Jenyuk Ayutthaya, Watcharaporn Devakul Na Division of Pharmacology Department of Basic Medical Sciences Faculty of Medicine Vajira Hospital Navamindradhiraj University Medical Student in Doctor of Medicine Programme Faculty of Medicine Vajira Hospital Navamindradhiraj University Department of Biomedical Engineering Faculty of Engineering Mahidol University Department of Environmental Engineering Faculty of Engineering Chulalongkorn University Professor Aroon Sorathesn Center of Excellence in Environmental Engineering Department of Environmental Engineering Faculty of Engineering Chulalongkorn University

Risperidone is useful for the treatment of schizophrenia symptoms;however, it also has side effects, and an overdose can be harmful. The metabolic effects of risperidone at high therapeutic doses and its metabolites have not been elucidated. Endogenous cellular metabolites may be comprehensively analyzed using untargeted metabolomics-based liquid chromatography-mass spectrometry (LC-MS), which can reveal changes in cell regulation and metabolic pathways. By identifying the metabolites and pathway changes using a nontargeted metabolomics-based LC-MS approach, we aimed to shed light on the potential toxicological effects of high-dose risperidone on brain microvascular endothelial cells (MVECs) associated with the human blood brain barrier. A total of 42 metabolites were selected as significant putative metabolites of the toxicological response of high-dose risperidone in MVECs. Six highly correlated pathways were identified, including those involving diacylglycerol, fatty acid, ceramide, glycerophospholipid, amino acid, and tricarboxylic acid metabolism. We demonstrated that methods focused on metabolomics are useful for identifying metabolites that may be used to clarify the mechanism of drug-induced toxicity. © 2024 The Authors

关键词： Brain microvascular endothelial cells Liquid chromatography-mass spectrometry Risperidone Untargeted metabolomics

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The Response of EEG Signal on Brain Relaxation Meditation Using Different Type of Zikr

The Response of EEG Signal on Brain Relaxation Meditation Us...

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2021 International Conference on biomedical engineering, ICoBE 2021

作者： Razak, N.N. Abd Sidek, K.A. Alaa, K.Y.D. Nasir, N.F. Mohd Department of Electrical and Computer Engineering Kulliyyah of Engineering International Islamic University Malaysia Department of Computer Engineering College of Computer Science and Engineering University of Ha’il Saudi Arabia Biomedical Electronic Engineering Programme Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Malaysia

Depression and stress are increasingly prevalent in today’s society, owing to people's hectic, competitive, and demanding lifestyles. These illnesses had become very common, particularly among young and middle-aged people, and suicidal ideation had been identified as one of the leading causes of death by the World Health Organization (WHO). Nature sound (sound of downpours or beach) has been linked to depression and anxiety in neurology research, and it has been shown to be an alternative to alleviate anxiety. The electroencephalogram (EEG) waveform has been discovered to possess the potential in identifying information from the brain signal as well as data from the past via Bluetooth communication. The waveform use in the study are the result of a few experiments. In this study, EEG data were collected from eight subjects, four males and four females, in between the age of 20 to 30 years old and in good health, using the BrainLink device. The participants were asked to listen to two playlists of zikr, Allah, Ya Allah, and SubhanAllah, during the experiments. To smooth the signal, the Butterworth filter was used. Later, the extracted features were Alpha, Beta, and Delta waves, which were segmented based on the filtered signal. To complete the decision-making stage, the average value of amplitude differences and the p-value test were performed in the final phase. Based on the results of the experiments, it is clear that zikr is dominant in Delta wave. In terms of data hypothesis analysis, the results of both experiment were differentiated to determine which brain signal was dominant, and p-value testing was performed. Furthermore, this research is an alternative to current methods because it suggest that zikr has the tendency to alter a person's brain state to be either in a relaxed or calm mode regardless of the type of zikr recitation. As an outcome, the study recommends the relationship of the reaction of EEG signal on brain relaxation with different types of zikr

关键词： Electroencephalography

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Synthesizing and Optimization the Hydroxyapatite Based on Corbiculacea Seashells 3rd

Synthesizing and Optimization the Hydroxyapatite Based on Co...

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3rd Symposium on Intelligent Manufacturing and Mechatronics, SympoSIMM 2020

作者： Mohd Roslan, Mohd Riza Mohd Nasir, Nashrul Fazli Mohammad, Nur Farahiyah Meng, Cheng Ee Mohd Amin, Nasrul Amri Abdul Khalid, Mohd Farid Zakaria, Mohd Zakimi Azizan, Muhammad Mokhzaini Jusoh, Muzammil Biomedical Electronic Engineering Programme Faculty of Electronic Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra Arau Perlis Malaysia Mechanical Engineering Programme Faculty of Mechanical Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra Arau Perlis Malaysia Shah Alam Selangor Malaysia Faculty of Electrical Engineering Technology Universiti Malaysia Perlis Kampus Pauh Putra Arau Perlis Malaysia Pauh Putra Arau Perlis02600 Malaysia

ISBN: (纸本)9789811608650

Hydroxyapatite (HA) is one of the main components in bone which functions to enhance its cell regeneration. Synthetically produced HA, based on seashell resources has higher biocompatibility, and in high demand especially in bone tissue engineering. However, the secondary phase of HA production are calcium oxide and carbonate, which impedes its performance. HA is synthesized via wet chemical precipitation and optimization were done to obtain nearly pure HA by manipulating the pH value and sintering temperature. It is expected that the combination of these parameters will optimize the amount of secondary phase hence attained nearly stoichiometric or pure HA. HA powders were analyzed through Fourier Transform Infrared Spectroscopy (FTIR) and Energy Dispersive X-ray Spectrometry (EDX). © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Chemical Precipitation Corbiculacea Hydroxyapatite

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The effect of polyvinylpyrrolidone-coated (PVP) on bismuth-based nanoparticles cell cytotoxicity

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Materials Today: Proceedings 2022年 66卷 2948-2951页

作者： Jamil, Amirah Geso, Moshi Algethami, Merfat Wan Sohaimi, Wan Fatihah Abdul Razak, Khairunisak Rahman, Wan Nordiana Medical Radiation Programme School of Health Sciences Health Campus Universiti Sains Malaysia Kubang Kerian Kelantan Malaysia Division of Medical Radiation School of Health and Biomedical Sciences RMIT University Bundoora VIC Australia Physics Department Faculty of Science Taif University Taif Saudi Arabia Department of Nuclear Medicine and Oncology Hospital Universiti Sains Malaysia Kubang Kerian Kelantan Malaysia School of Materials and Mineral Resources Engineering Engineering Campus Universiti Sains Malaysia Nibong Tebal Penang Malaysia

Cancer statistics display high malignant breast cancer cases every year due to its aggressive growth rate. The emergence of nanomedicines has helped tremendously eradicate cancer, starting with diagnosis, therapy, intensive analysis, and further interventions. Bismuth-based nanoparticles are one of the various metal nanoparticles used as radiosensitizers to increase cancer tissue sensitivity when irradiated in radiotherapy treatment. In-vitro cytotoxicity assay is mandatory to ensure that the nanoparticles do not induce lethal toxicity to the cells before being deemed suitable for clinical use. The research aims to investigate the cytotoxicity effect of polyvinylpyrrolidone-coated-coated (PVP) bismuth nanoparticles on the MCF-7 cancer cell line. Uncoated bismuth nanoparticles (BiNPs) and PVP-coated bismuth sulphide nanoparticles (Bi2S3-PVP 8000 and Bi2S3-PVP 29000) within the range of 0.00005 to 0.5 mMol/L were tested on MCF-7 cancer cell lines for 24, 48, and 72 h. The cytotoxicity assay results indicate the uncoated bismuth nanoparticles have minimal toxicity on MCF-7 treated with BiNPs across 24 to 72 h of incubation compared to PVP-coated counterparts. Reduction of cell viability within 1.6 – 11.3% is observed during 48 h post-treatment of BiNPs with different concentrations, with a slight improvement of viability after 72 h. However, Bi2S3-PVP 8000 and Bi2S3-PVP 29000 exhibit non-toxic effects on cells yet induced abnormally high cell proliferation levels up to 5.4 folds for Bi2S3-PVP 8000 and 5.9 folds for Bi2S3-PVP 29000 compared to their control groups. The unwanted proliferation is counterproductive as the nanoparticles must withhold the growth of cancer cells besides increasing the radiosensitivity when irradiated. The results concluded that MCF-7 cell viability and cell proliferation are concentration-dependent when using PVP as bismuth nanoparticles coating. Further study is needed to investigate the PVP-coated bismuth nanoparticles effect on different t

关键词： Coatings

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Automatic Platform for Upper Extremity Musculoskeletal Disorder Risks Estimation from Repetitive Actions -Preliminary results.

Automatic Platform for Upper Extremity Musculoskeletal Disor...

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IEEE International Workshop on Medical Measurement and Applications (MEMEA)

作者： Pablo Aqueveque Manuel Gutiérrez Guisella Peña Enrique Germany Britam Gómez Gustavo Retamal Paulina Ortega-Bastidas Electrical Engineering Department Faculty of Engineering Universidad de Concepción Concepción Chile Ergonomics Department Faculty of Biological Sciences Universidad de Concepción Concepción Chile Biomedical Engineering Faculty of Engineering Universidad de Santiago de Chile Santiago Chile Kinesiology Department Faculty of Medicine Universidad de Concepción Concepción Chile Health Sciences PhD Programme Universidad Rey Juan Carlos Madrid Spain

Work-related musculoskeletal disorders is a major problem for worker’s health when dealing with repetitive tasks. The Occupational Repetitive Actions Index (OCRA) is one of the most widely used methods for determining upper extremity risk from repetitive actions. Traditional risk assessment consists in observing and recording the entire workday or part of it. This observational assessment depends on the evaluator’s expertise, which lead to inter-evaluator variability in the results even for the same job. This paper presents preliminary results of a platform that combines motion capture data with a digitalized OCRA Index method to classify risks under repetitive tasks conditions. Repetitive action tasks were performed in a controlled laboratory environment on ten healthy subjects, where optical and inertial sensors were used to capture movement. Body segment positions, displacements and joint angles were fed into the platform comparing their processing time and reliability. Although results indicate that optical systems have a better performance than inertial sensors for posture evaluation, the last has better practical applicability since optical markers occlusion in the working setup induced measurement errors. In addition, inertial systems are more likely to be used on in real working scenarios due to their ease of use and portability. Finally, inertial sensors combined with the digitized OCRA index method platform effectively reduces 67% of the needed evaluation time compared to traditional observational methods.

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Seroprevalence of SARS-CoV-2 antibodies and demographic predictors among asymptomatic individuals in Osun State, Nigeria

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Discover Public Health 2025年第1期22卷 1-9页

作者： Oyetunde, Oluwapelumi Breakthrough Alao, Jude Oluwapelumi Akinsola, Oluwatomisin Aderonke Awobiyi, Hezekiah Oluwajoba Aremu, Rasidat Oyindamola Ajimoh, Oreoluwa Deborah Lawal, Khadijah Dolapo Oluwasanya, Glory Jesudara Abiosun, Olanike Moyoloye Oladipo, Elijah Kolawole Biomedical Health Department College of Science and Engineering University of Derby Derby England School of Public Health and Interdisciplinary Studies Auckland University of Technology Auckland New Zealand Microbiology Programme Engineering and Science College of Agric Bowen University Iwo Nigeria Faculty of Natural Science Redeemer’s University Ede Nigeria Microbiology Department Adeleke University Ede Nigeria School of Life Sciences University of Essex Essex England

This study assesses the seroprevalence of SARS-CoV-2 antibodies (IgM, IgG, and IgA) among asymptomatic and unvaccinated individuals in Osun State, Nigeria, to quantify hidden infections and inform targeted public health interventions. A total of 300 participants from diverse socio-demographic backgrounds were tested using ELISA in this cross-sectional study, conducted between February and May 2021. The study revealed a seroprevalence of 58.0%, with notable differences between urban and rural areas, emphasizing the influence of urbanization on virus transmission. No significant associations were found between seropositivity and demographic factors such as age, gender, or occupation, indicating widespread transmission across all groups. However, elevated seroprevalence was observed among married individuals and self-employed workers, suggesting higher exposure in household and occupational settings. These findings underscore the urgent need for tailored public health strategies in low- and middle-income countries, with a focus on urban centers, reducing household transmission, and safeguarding informal workers. The alignment of these results with global trends highlights the critical role of local data in shaping effective public health responses. This study calls for targeted interventions, continuous surveillance, and comparative studies to better manage the current pandemic and prepare for future public health crises. The research provides valuable insights into controlling COVID-19 transmission in similar settings, with significant implications for global health strategies.

关键词： SARS-CoV-2 Seroprevalence Asymptomatic Infections Public Health Cross-Sectional Studies

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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Development of a Platform to Assess the Risk of Musculoskeletal Disorders in Manual Load Handling Activities - Preliminary Results

Development of a Platform to Assess the Risk of Musculoskele...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Pablo Aqueveque Manuel Gutierrez Gustavo Retamal Enrique Germany Guisella Peña Britam Gómez Paulina Ortega-Bastidas Electrical Engineering Department Faculty of Engineering Universidad de Concepción Concepción Chile Ergonomics Department Faculty of Biological Sciences Universidad de Concepción Concepción Bío Bío Chile Biomedical Engineering Faculty of Engineering Universidad de Santiago de Chile Santiago Chile Kinesiology Department Faculty of Medicine Universidad de Concepción Concepcion Chile Healt Sciences PhD Programme International Doctoral School Universidad Rey Juan Carlos Madrid Spain

Risk identification on workstations is a crucial step to prevent the occurrence of musculoskeletal disorders (MSD) in workers. The available methods and tools used by ergonomists to assess and estimate the risk related to manual handling of loads under repetitive work cycles are usually biased by the inter-evaluator error that can lead to a subjective determination of work-related risks due to the application of, mainly, observational methods. This paper shows the preliminary results of a platform to assess the risk of musculoskeletal disorders during manual load-handling tasks using an instrumented system and using the National Institute for Occupational Safety & Health (NIOSH) method. Eight healthy subjects were measured during lifting activities using an optical-based and inertial-based motion capture systems. The developed software implements a semi-automated instrumented version of the NIOSH method, helping the evaluator with automated calculations of body segment locations, displacements and joint angles making it possible to obtain a objective risk classification. Also, we achieved a reduction of 85% in the time for the estimation of the necessary factors for the digital evaluation methodology, making the proposed platform a promising and attractive alternative for its application in real environments for risk *** health relevance— This work proposes an assistance tool for the detection of musculoskeletal disorders in activities related to manual handling of loads, essential to initiate modification strategies in the workplace, reduce the occurrence of occupational diseases and reduce the time of risk classification.

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