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Sensor system for Real-Time Classification of Manual Construction Tasks with Power Tools for Exoskeleton Control

Sensor System for Real-Time Classification of Manual Constru...

引用

2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Leudesdorff, Bent Strumpler, Lydia R. S. Dobosz, Thomas Maufroy, Christophe Schneider, Urs Bauernhansl, Thomas Fraunhofer Institute for Manufacturing Engineering and Automation Ipa Germany Institute for Industrial Manufacturing and Management University of Stuttgart Germany

ISBN: (纸本)9781665410205

Work-related musculoskeletal disorders (WMSD) continue to be a significant cause of work incapacity. Exoskeletons have the potential to prevent these disorders, with passive exoskeletons already proving their usefulness but also displaying limitations. However, currently there is a lack of suitable methods to control active exoskeletons that offer additional advantages like supporting the user just when needed. This paper proposes a novel sensor-based system and a classification methodology for various work-related activities, based on the kinematic and power tool activation signals. First, requirements and thresholds for the sensor system and its signals are derived from representative activities in the construction environment. Then, the paper introduces a sensor system that collects the tool's kinematic signals and activation. The sensor system consists of an inertial measurement unit (IMU), pressure sensor, and WiFi-capable micro-controller for data transmission. Based on the signals, a threshold-based algorithm, capable of identifying six predefined activities is designed. The validity of the sensor system and algorithm is assessed through a custom-designed test course, reflective of real-world construction scenarios. With the developed test course, a study is conducted, and the activities are classified using the signals of the sensor system. The results demonstrate that the defined activities can be distinguished based on the kinematic and activation signals of the power tools. © 2024 ieee.

关键词： Exoskeleton (Robotics)

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A Cell Diagnosis Support system with Providing the Reason for Prediction

A Cell Diagnosis Support System with Providing the Reason fo...

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2022 ieee international conference on systems, Man, and Cybernetics, smc 2022

作者： Imori, Yuichi Morimoto, Masakazu University of Hyogo Graduate School of Engineering Himeji Japan University of Hyogo Associate Engineering Himeji Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

In this paper we propose a cellular diagnostic support system for cervical cancer from WSI which presents the reason for diagnosis. First, cytoplasmic and nuclear regions are extracted from cell images using U-2-Net. For the extracted regions, 29 image features were calculated, and machine learning is applied to perform cell classification based on the Bethesda system. The results showed an accuracy of 68.5% in the 6-class classification of cervical cancer. © 2022 ieee.

关键词： Machine learning

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Predictive Control for Dynamic Scheduling and Maintenance in Open-Shop Manufacturing systems 19

Predictive Control for Dynamic Scheduling and Maintenance in...

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19th Annual international ieee conference on system of systems engineering (SoSE)

作者： Bozzi, Alessandro Graffione, Simone Sacile, Roberto Zero, Enrico Univ Genoa Dept Informat Bioengn Robot & Syst Engn DIBRIS I-16145 Genoa Italy

ISBN: (纸本)9798350365924;9798350365917

This paper addresses an open-shop scheduling problem within a manufacturing system modeled using Mixed Integer Linear Programming, which accounts for the progressive wear of machinery after job processing. The open-shop problem is transformed into a flow-shop problem, involving the enumeration of all possible job paths and the selection of paths that minimize the makespan. The research provides a comparison among an offline algorithm, unable to perform machinery maintenance and disregarding increases in processing times;an offline algorithm subject to machinery maintenance constraints after processing times exceed a certain threshold;and a dynamic algorithm utilizing Model Predictive Control concepts to reroute jobs at each relevant event, including unexpected job arrivals, as well as the initiation and completion of machine maintenance. The dynamic algorithm also considers the potential unavailability of machinery due to maintenance and deterioration. Its effectiveness is assessed through a simulated case study of a flexible manufacturing system, revealing a notable improvement in makespan approximately a 30% reduction compared to the offline scenario without maintenance. This showcases its potential for real-world applications in the manufacturing industry.

关键词： Machine failure Open-shop Problem Scheduling

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Field Oriented Control for Seven Phase Induction Machine with Comparative Control Method 12

Field Oriented Control for Seven Phase Induction Machine wit...

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12th international conference on Smart Grid (ICSmartGrid)

作者： Sultan, Ali H. Al-Badrani, Harith Ninevah Univ Dept Elect Engn Mosul Iraq

ISBN: (纸本)9798350361612;9798350361629

With the spread of electric motors in various fields of work, such that they have become the infrastructure for many aspects of life, it has become necessary to obtain a speed controller for these motors to make them more efficient in general uses. The Field-Oriented Control (FOC) methodology is frequently recognized as one of the most important and straightforward of all the alternatives for controlling the speed of an electric motor utilizing the vector control approach. In this study, a seven-phase induction motor's speed was controlled using FOC technology exploiting the advantages of multi-phase motors. This technique offers a variety of options for controlling methods. A system was created to control the speed of a seven-phase induction motor using Field Oriented Control technology and through two methods of control: Sliding Mode Control (smc) and Proportional Integral (PI) controller, within the principles of the sine pulse width modulation (SPWM) technique. This system was designed to control the motor speed and rotor flux in the event of a disruption brought on by an increase in the rotor's resistance as a result of the motor's temperature rising. Consequently, the system turns non-linear, and conventional controllers like PI are unable to stabilize it. Therefore, there is a pressing demand for controllers that ensure higher stability for non-linear systems like smc. The system was simulated using the Matlab/Simulink environment, monitored under various operating settings, and its stability was evaluated against external variables in addition to its quick reactions and stability at the pace required to work with it.

关键词： Seven-phase induction motor FOC PI controller smc non-linear system SPWM

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Pursuing Equilibrium of Medical Resources via Data Empowerment in Parallel Healthcare system

Pursuing Equilibrium of Medical Resources via Data Empowerme...

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2023 ieee international conference on systems, Man, and Cybernetics, smc 2023

作者： Yu, Yi Yao, Shengyue Wang, Kexin Chen, Yan Wang, Fei-Yue Lin, Yilun Urban Computing Lab Shanghai Artificial Intelligence Laboratory Shanghai China School of Health Policy and Management Nanjing Medical University Nanjing China Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Gusu School Nanjing Medical University Suzhou China Jiangsu Provincial Institute of Health Nanjing China Institute of Automation Chinese Academy of Sciences Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology Macau China

ISBN: (纸本)9798350337020

The imbalance between the supply and demand of healthcare resources is a global challenge, which is particularly severe in developing countries. Governments and academic communities have made various efforts to increase healthcare supply and improve resource allocation. However, these efforts often remain passive and inflexible. Alongside these issues, the emergence of the parallel healthcare system has the potential to solve these problems by unlocking the data value. The parallel healthcare system comprises Medicine-Oriented Operating systems (MOOS), Medicine-Oriented Scenario engineering (MOSE), and Medicine-Oriented Large Models (MOLMs), which could collect, circulate, and empower data. In this paper, we propose that achieving equilibrium in medical resource allocation is possible through parallel healthcare systems via data empowerment. The supply-demand relationship can be balanced in parallel healthcare systems by (1) increasing the supply provided by digital and robotic doctors in MOOS, (2) identifying individual and potential demands by proactive diagnosis and treatment in MOSE, and (3) improving supply-demand matching using large models in MOLMs. To illustrate the effectiveness of this approach, we present a case study optimizing resource allocation from the perspective of facility accessibility. Results demonstrate that the parallel healthcare system could result in up to 300% improvement in accessibility. © 2023 ieee.

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Accelerometer-Based Pushing Location Feedback Mechanism for CPR Training

Accelerometer-Based Pushing Location Feedback Mechanism for ...

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2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Chao, Chien-Yu Yen, Chun-Han Lin, Wen-Yen Chang Gung University Dept. of Electrical Engineering Tao-Yuan Taiwan Division of Cardiology Department of Internal Medicine Chang Gung Memorial Hospital Tao-Yuan Taiwan

ISBN: (纸本)9781665410205

Using CPR training equipment with complete feedback mechanism is a key to help people learn how to deliver high quality CPR in the emergent occasions and hence the survival rate of people who suffered from cardiac arrest can be improved. However, on some advanced CPR training models, Resusci Anne, only pushing depth and frequency feedback information are provided, but no Resusci Anne is equipped with pushing location information feedback system. In this study, an accelerometer-based sensing mechanism on Resusci Anne has been proposed to provide the feedback information about the offset distances and directions from correct pushing location. With an accelerometer mounted on the center of correct pushing location, according to the inclination and rotation angles converted from the measured data of accelerometer, the offset distances, and directions of actual pushing locations on Resusci Anne can be derived. From the preliminary test, the system can successfully provide the pushing location information during CPR training and hence help people learn high quality CPR. © 2024 ieee.

关键词： Accelerometers

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Generating Requirements Documents for Embedded systems: A Device Knowledge-Guided Approach 32

Generating Requirements Documents for Embedded Systems: A De...

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32nd ieee international Requirements engineering conference (RE)

作者： Wang, Chunhui Zhao, Jiaqi Chen, Xiaohong Jin, Zhi Inner Mongolia Normal Univ Coll Comp Sci & Technol Hohhot Peoples R China East China Normal Univ Shanghai Key Lab Trustworthy Comp Shanghai Peoples R China Peking Univ Sch Comp Sci Beijing Peoples R China PKU Minist Educ Key Lab High Confidence Software Technol Beijing Peoples R China

ISBN: (纸本)9798350395525;9798350395518

Requirements documentation is an important activity in requirements development. Embedded systems consists of software and hardware, as well as multiple stakeholders. As systems grow in size and complexity, writing requirements documents becomes more time-consuming and laborious. Based on the strong correlation between embedded system and physical device, this paper proposes to use device knowledge base to support requirements documentation. Stakeholders only need to fill in the intention and device selection, and then the device and system requirements are supplemented by device knowledge. Templates and environment modeling and analysis methods are proposed to further guide requirements acquisition. This leads to considerably simplify and accelerate the requirements document development for embedded systems.

关键词： requirements documentation embedded system device knowledge-guided requirements document generation requirements template

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Integrating Task Allocation and Hierarchical Reinforcement Learning for Optimized Cargo Transport Routing

Integrating Task Allocation and Hierarchical Reinforcement L...

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2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Hayashida, Tomohiro Sekizaki, Shinya Furukawa, Ryuya Nishizaki, Ichiro Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashihiroshima Hiroshima7398527 Japan

ISBN: (纸本)9781665410205

In recent years, there have been growing expectations for the improvement of operational efficiency through the use of artificial intelligence (AI: Artificial Intelligence) in various fields such as healthcare, industry, and services. Additionally, advancements in robotics technology have enabled widespread collaborative operations among multiple autonomous mobile robots. Since the 1980s, there has been active research on improving the efficiency of coordinated actions by multiple autonomous mobile robots using Multi-Agent Robot systems (MARS) (Cao et al.;1997, Yan et al.;2013, Ismail and Sariff;2019). This study focuses on robots that transport cargo within a warehouse and aims to develop learning methods for effective division of labor among multiple robots. In large and complex environments, agents need to undergo extensive repetitive learning to make appropriate action choices solely through machine learning techniques such as reinforcement learning. Traditional multi-agent methods like QMIX (Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning) (Rashid et al.;2020) and MADDPG (Multi-Agent Deep Deterministic Policy Gradient) (Lowe et al.;2017) require substantial computational time for environmental exploration, presenting a significant challenge. Therefore, this paper proposes a two-tiered learning model that separates overall optimization, such as establishing a general procedure for task performance, from individual optimization based on local situational judgments. Additionally, to demonstrate the effectiveness of the proposed method, a simulation system tailored to the target environment is constructed, and simulation analysis based on this system is conducted. © 2024 ieee.

关键词： Reinforcement learning

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Development of Tracking system for Swallowing Movement Using Optical Flow

Development of Tracking System for Swallowing Movement Using...

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2024 ieee international conference on systems, Man, and Cybernetics, smc 2024

作者： Yagi, Naomi Nishihara, Ryosuke Kawamura, Naoko Maezawa, Hitoshi Kashioka, Hideki Hirata, Masayuki Yanagida, Toshio Sakai, Yoshitada Hata, Yutaka Advanced Medical Engineering Research Institute University of Hyogo Hyogo670-0836 Japan Graduate School of Information Science University of Hyogo Japan Himeji Dokkyo University Faculty of Health Care Science Japan Kansai Medical University Department of Physical Medicine and Rehabilitation Japan National Institute of Information and Communications Technology Japan Graduate School of Medicine Osaka University Department of Neurological Diagnosis and Restoration Japan Kobe University Graduate School of Medicine Division of Rehabilitation Medicine Japan

ISBN: (纸本)9781665410205

Currently, population in Japan has been aging at a speed unparalleled in other countries, and countermeasures against aging population and the worsening of disease for people with disabilities have become urgent issues. Pneumonia and aspiration pneumonia are the leading causes of death. It is said that swallowing function tends to decline from around age of 40, however it is important to keep it in good condition without deteriorating function as much as possible. The gold standard for swallowing functional evaluation is swallowing contrast testing, however X-ray exposure disables to repeat testing. In addition, Repetitive Saliva Swallowing Test (RSST) of screening test is difficult for self-check. Therefore, in this study, we develop a system to self-evaluate swallowing ability for keeping swallowing function healthy. It is proposed by applying optical flow and artificial intelligence of DeepLabcut. As a result, we were able to visualize movement of larynx during swallowing. © 2024 ieee.

关键词： Diagnosis

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sRPE and ACWR to Control Fatigue Levels and Minimize Injuries in Performance Sports

sRPE and ACWR to Control Fatigue Levels and Minimize Injurie...

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2023 ieee international conference on systems, Man, and Cybernetics, smc 2023

作者： Biró, Attila Cuesta-Vargas, Antonio Ignacio Szilágyi, László George Emil Palade University of Medicine Pharmacy Science and Technology of Targu Mures Department of Electrical Engineering and Information Technology Str. Nicolae Iorga Nr. 1 Targu Mures540088 Romania University of Malaga Department of Physiotherapy Malaga29071 Spain Malaga29590 Spain School of Clinical Science Queensland University Technology Faculty of Health Science Brisbane4000 Australia Computational Intelligence Research Group Sapientia Hungarian University of Transylvania Targu Mures540485 Romania Physiological Controls Research Center Óbuda University Budapest1034 Hungary

ISBN: (纸本)9798350337020

sRPE and ACWR are valuable tools for controlling fatigue levels and minimizing injuries in performance sports. Their ability to provide individualized assessment, integrate subjective and objective measures, and inform data-driven decision-making makes them essential components of a comprehensive sports safety and performance monitoring system. The goal of this study was to provide first a computer-assisted solution to predict the fatigue level, and then to expand this with an artificial intelligence-supported solution for a more advanced pipeline in performance sports, to minimise the injury level. © 2023 ieee.

关键词： ACWR fatigue control injury prevention recovery sports safety sRPE

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