A low-cost rapid upper limb assessment method in manual assembly line based on somatosensory interaction technology

Jiang, Shengqian; Liu, Peng; Fu, Danni; Yang, Xue; Luo, Wentao; Wang, Mingjie

doi:10.1063/1.4981575

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…The performance of automatic assembly of the machine vision system was measured using the parameters, and the corresponding experimental conclusions were obtained. Moreover, it was compared with the traditional manual assembly technology [20], and corresponding experimental conclusions were obtained for reference.…”

Section: Experimental Methods and Parametersmentioning

confidence: 99%

Industrial Automatic Assembly Technology Based on Machine Vision Recognition

Xiang¹

2021

Manufacturing Technology

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With the rapid development of science and technology, the means of industrial production have become more diversified and intelligent, and the development of new means of industrial production has become an increasingly important research topic. Therefore, the automatic assembly technology was studied, taking machine vision system as the main research subject in this study. An automated assembly model of industrial technology based on machine vision recognition was established, parameters, such as the part positioning parameter, assembly time, the number of parts wrongly assembled, the number of parts missing, and the assembly qualification rate were obtained, and the corresponding experimental conclusions were obtained. Moreover, it was compared with the traditional manual assembly technology, and it was found that the automatic assembly technology based on machine vision recognition had better performance and more remarkable experimental results compared with the traditional manual assembly technology, and the traditional manual assembly technology needed continuous modification and optimization. This work provides a new route for automatic assembly technology in industrial technology.

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Section: Experimental Methods and Parametersmentioning

confidence: 99%

Industrial Automatic Assembly Technology Based on Machine Vision Recognition

Xiang¹

2021

Manufacturing Technology

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“…Jiang [17] Develop a posture load risk recognition method to evaluate the body RULA level. Work posture Toro [18] Design a low cost EMG system for assessing muscle fatigue.…”

Section: Work Posturementioning

confidence: 99%

Integrated Measurement System of Postural Angle and Electromyography Signal for Manual Materials Handling Assessment

Isa

Saptari

Abulais

et al. 2021

IJIE

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Improper design of manual materials handling (MMH) tasks at workplace can cause musculoskeletal disorders such as muscle strain to industrial workers. To avoid these disorders, ergonomists and engineers require an integrated measurement system which allows them to study the interaction of body posture and muscle effort during performing MMH tasks. However, far too little attention has been paid to develop an integrated measurement system of body posture and muscle activity for assessing MMH tasks. The aim of this study was to develop and test a prototype of integrated system for measuring postural angles and electromyography (EMG) signals of a worker who doing MMH tasks. The Microsoft Visual Studio software, a 3D camera (Microsoft Kinect), Advancer Technologies muscle sensors and a microcontroller (NI DAQ USB-6000) were applied to develop the integrated postural angle and EMG signal measurement system. Additionally, a graphical user interface was created in the system to enable users to perform body posture and muscle effort assessment simultaneously. Based on the testing results, this study concluded that the patterns of EMG signals are depending on the postural angles which consistent with the findings of established works. Further study is required to enhance the validity, reliability and usability of the prototype so that it may facilitate ergonomists and engineers to assess work posture and muscle activity during MMH task.

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“…Real application scenarios might require the use of other sectors, such as shown in other upper-limb studies [57] simulating assembly scenarios, that were excluded in this study due to limitations of the Kinect system tracking algorithms. Also, the number of movements could be expanded to mimic real scenarios, including other upper-limb gestures useful in industry [47,66,67] and including the tracking of other body segments such as legs [52,63]. Including a total body model would allow to inspect a wider number of degrees of freedom and compare the performances on full 3D movement.…”

Section: Limitationsmentioning

confidence: 99%

Analysis of Upper-Limb and Trunk Kinematic Variability: Accuracy and Reliability of an RGB-D Sensor

Scano¹,

Mira²,

Cerveri³

et al. 2020

MTI

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In the field of motion analysis, the gold standard devices are marker-based tracking systems. Despite being very accurate, their cost, stringent working environments, and long preparation time make them unsuitable for small clinics as well as for other scenarios such as industrial application. Since human-centered approaches have been promoted even outside clinical environments, the need for easy-to-use solutions to track human motion is topical. In this context, cost-effective devices, such as RGB-Depth (RBG-D) cameras have been proposed, aiming at a user-centered evaluation in rehabilitation or of workers in industry environment. In this paper, we aimed at comparing marker-based systems and RGB-D cameras for tracking human motion. We used a Vicon system (Vicon Motion Systems, Oxford, UK) as a gold standard for the analysis of accuracy and reliability of the Kinect V2 (Microsoft, Redmond, WA, USA) in a variety of gestures in the upper limb workspace—targeting rehabilitation and working applications. The comparison was performed on a group of 15 adult healthy subjects. Each subject had to perform two types of upper-limb movements (point-to-point and exploration) in three workspace sectors (central, right, and left) that might be explored in rehabilitation and industrial working scenarios. The protocol was conceived to test a wide range of the field of view of the RGB-D device. Our results, detailed in the paper, suggest that RGB-D sensors are adequate to track the upper limb for biomechanical assessments, even though relevant limitations can be found in the assessment and reliability of some specific degrees of freedom and gestures with respect to marker-based systems.

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A low-cost rapid upper limb assessment method in manual assembly line based on somatosensory interaction technology

Cited by 7 publications

References 7 publications

Industrial Automatic Assembly Technology Based on Machine Vision Recognition

Industrial Automatic Assembly Technology Based on Machine Vision Recognition

Integrated Measurement System of Postural Angle and Electromyography Signal for Manual Materials Handling Assessment

Analysis of Upper-Limb and Trunk Kinematic Variability: Accuracy and Reliability of an RGB-D Sensor

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