Multi-Objective Optimization Method for Posture Prediction of Symmetric Static Lifting Using a Three-Dimensional Human Model

Azizi, Sirous; Dadarkhah, Afsaneh; Masouleh, Alireza Asgharpour

doi:10.5812/amh.104283

Cited by 6 publications

(4 citation statements)

References 23 publications

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“…In this applied research, a mixed quantitative and qualitative method was used, the quantitative part of which was done with a descriptive survey and the qualitative part of which included case study. For literature review, data was collected and criticized from articles, treatises, and textbooks, and theoretical framework was developed to extract variables and develop the objective table; then, the questionnaire was developed and surveyed in the area [27][28][29][30][31][32][33][34][35][36][37][38].…”

Section: Methodsmentioning

confidence: 99%

Designing a Desirable House with consideration of Strengthening the Sense of Peace of the Residents

Sabaroo,

Mehrali

2023

Teh. glas. (Online)

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Humans in modern society are faced with different environmental changes; creation of residential spaces is one of these changes in environmental structure of people in society. The sense of place means people's mental perception of the environment and their more or less conscious feelings about their environment, which places one in an internal relationship with the environment so that one’s understanding and feeling are linked and integrated with the semantic context of the environment. This feeling is a factor that transforms a space into a place with special sensory and behavioral characteristics for certain people. This study investigates the sense of peace in residential buildings and its constituent factors. Now the question is, how to increase the sense of peace in people with proper design in residential environments? For this purpose, this study tends to examine the effect of a desirable house on strengthening the sense of peace of the residents by using a quantitative-qualitative method and using documents, observation, and questionnaires to find out how a suitable design induces a sense of peace in people. Based on findings obtained from field studies and data extracted from the questionnaire, it was found that residential complex indicators and residents' sense of peace have a significant effect on the satisfaction of the residents of the residential complex (p < 0.05). Therefore, it can be claimed with 95% confidence that residential complex indicators and residents' sense of peace had a significant effect on the satisfaction of the residents of the studied residential complex in Tehran. The results also show that using more simple lines and fewer broken lines in the design of building form and considering areas and separating them from each other, as well as color, light, perception, and psychology of the environment are factors that cause a sense of satisfaction and a sense of peace in residents.

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Section: Methodsmentioning

confidence: 99%

Designing a Desirable House with consideration of Strengthening the Sense of Peace of the Residents

Sabaroo,

Mehrali

2023

Teh. glas. (Online)

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“…Medical device certification by the FDA involves a rigorous evaluation process to assess the device's safety and effectiveness, as well as its compliance with relevant regulations. This evaluation considers the specific intended use, indications, and potential risks associated with the device [123]. The FDA may require the submission of clinical data, performance testing, and the validation of the machine learning algorithms to ensure that the device meets the necessary standards.…”

Section: Medical Device Certificationmentioning

confidence: 99%

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors

Amiri,

Heidari,

Darbandi

et al. 2023

Sustainability

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With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the medical and healthcare fields are utilizing machine learning (ML) methodologies in numerous inventive ways. ML techniques have outstripped formerly state-of-the-art techniques in medical and healthcare practices, yielding faster and more precise outcomes. Healthcare practitioners are increasingly drawn to this technology in their initiatives relating to the Internet of Behavior (IoB). This area of research scrutinizes the rationales, approaches, and timing of human technology adoption, encompassing the domains of the Internet of Things (IoT), behavioral science, and edge analytics. The significance of ML in medical and healthcare applications based on the IoB stems from its ability to analyze and interpret copious amounts of complex data instantly, providing innovative perspectives that can enhance healthcare outcomes and boost the efficiency of IoB-based medical and healthcare procedures and thus aid in diagnoses, treatment protocols, and clinical decision making. As a result of the inadequacy of thorough inquiry into the employment of ML-based approaches in the context of using IoB for healthcare applications, we conducted a study on this subject matter, introducing a novel taxonomy that underscores the need to employ each ML method distinctively. With this objective in mind, we have classified the cutting-edge ML solutions for IoB-based healthcare challenges into five categories, which are convolutional neural networks (CNNs), recurrent neural networks (RNNs), deep neural networks (DNNs), multilayer perceptions (MLPs), and hybrid methods. In order to delve deeper, we conducted a systematic literature review (SLR) that examined critical factors, such as the primary concept, benefits, drawbacks, simulation environment, and datasets. Subsequently, we highlighted pioneering studies on ML methodologies for IoB-based medical issues. Moreover, several challenges related to the implementation of ML in healthcare and medicine have been tackled, thereby gradually fostering further research endeavors that can enhance IoB-based health and medical studies. Our findings indicated that Tensorflow was the most commonly utilized simulation setting, accounting for 24% of the proposed methodologies by researchers. Additionally, accuracy was deemed to be the most crucial parameter in the majority of the examined papers.

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“…(In this section, bi-criterion objective functions are also categorized as multiple objective functions.) Multiple objective functions can also be categorized into two types: one is the product of different cost functions [22], while the other is weighted sum of different cost functions [1,2,8]. It has been reported that the combination of different cost functions (i.e., multiple objective functions [23]) is able to increase the accuracy of predicted body postures [16].…”

Section: Body Oosture Optimization and Cost Functionmentioning

confidence: 99%

“…An example is that it has been validated in the prediction of human body postures while reaching buttons in a car, which can help to re-design the location of those buttons [2]. Second, it is useful for the ergonomic simulation of manual tasks [4][5][6][7][8], which enables the corresponding ergonomic risks to be proactively assessed. With proactively estimated body posture, necessary adjustments will be made to the tasks in advance [5,6].…”

Section: Introductionmentioning

confidence: 99%

Determining human upper limb postures with a developed inverse kinematic method

Chen

Li²

2022

Robotica

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Body posture determination methods have many applications, including product design, ergonomic workplace design, human body simulation, virtual reality, and animation industry. Initiated in robotics, inverse kinematic (IK) method has been widely applied to proactive human body posture estimation. The analytic inverse kinematic (AIK) method is a convenient and time-saving type of IK methods. It is also indicated that, based on AIK methods, a specific body posture can be determined by the optimization of an arbitrary objective function. The objective of this paper is to predict the postures of human arms during reaching tasks. In this research, a human body model is established in MATLAB, where the middle rotation axis analytic kinematic method is accomplished, based on this model. The joint displacement function and joint discomfort function are selected to be initially applied in this AIK method. Results show that neither the joint displacement function nor the joint discomfort function predicts postures that are close enough to natural upper limb postures of human being, during reaching tasks. Therefore, a bi-criterion objective function is proposed by integrating the joint displacement function and joint discomfort function. The accuracy of the arm postures, predicted by the proposed objective function, is the most satisfactory, while the optimal value of the coefficient, in the proposed objective function, is determined by golden section search.

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Multi-Objective Optimization Method for Posture Prediction of Symmetric Static Lifting Using a Three-Dimensional Human Model

Cited by 6 publications

References 23 publications

Designing a Desirable House with consideration of Strengthening the Sense of Peace of the Residents

Designing a Desirable House with consideration of Strengthening the Sense of Peace of the Residents

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors

Determining human upper limb postures with a developed inverse kinematic method

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