User's Posture Research Articles

Continuous postural and movement monitoring system for wheelchair users assessment

The aim of this study is to develop a system to assist in diagnosing individuals with reduced mobility. Specifically, the posture of wheelchair users, which is closely related to their functional status, can be adversely affected by everyday movements and obstacles. To address this, the study proposes a combined monitoring device that tracks real-time users posture and wheelchair movement (distance, orientation, vibrations...) and quantifies the relationship between both. Tests were conducted on various environments, such as smooth floors, ramps, pavements, tramways, and lifts, to establish the relationship between wheelchair motion and user posture. Specific evaluation metrics were used to assess this relationship and the device’s ability to identify it. The results confirm the success of the combined approach, as the system can detect the impact of external agents on user posture. This robust and reliable device helps professionals quantify users functional status and understand the challenges faced by wheelchair users.

Simulation research on Tai Chi movement posture resolution based on multi-MEMS sensor combination

The combined system based on multiple MEMS sensors is a miniature measurement system used for dynamic output and display of 3D information about the user's posture. It is mainly used for various Tai Chi movement posture calculation simulation research, wearable devices, etc. This article explores MEMS sensor technology, focusing on MEMS sensor data processing, Tai Chi movement position calculation and fusion calculation positioning algorithm. Due to the high noise characteristics of MEMS sensor devices, time series analysis is used to model MIMU signals and Kalman filtering is optimized. As a research field, simulation of Tai Chi movement appears in the intersection of biomechanics, robotics and computer science. The purpose is to create a computer model to simulate the natural and real body movements of the human body under certain conditions. In addition to creating special effects, Tai Chi movement posture calculation simulation can also be used for operation training and research on body structure. This article first introduces the typical applications of several MEMS sensor combinations, and then introduces the key technology of studying Tai Chi movement simulation. The kinematics and mechanics data of Tai Chi are obtained using biomechanical measurement technology, while the individual simulation of Tai Chi dynamics is realized in a certain mode of the machine. By creating a kinematic model of the human upper limb, and finally creating a flexible machine that imitates the human upper limb, to analyze the kinematic characteristics of the human upper limb, and cleverly realize the imitation of active interaction, the simulation of human movement and the solution of Tai Chi movement posture Simulation.

Designing an adjustable ergonomic laptop desk and its evaluating by RULA and NERPA methods

BACKGROUND: Using a computer may lead to pain in wrists, neck, and back. In addition, adopting various body postures like sitting cross-legged, semi-fowler’s position, and putting the laptop on the leg may lead to the development of persistent and irreversible discomfort. OBJECTIVE: The purpose of this research is to design and build an adjustable ergonomic laptop desk based on the anthropometric characteristics of students in the age range of 20 to 30 years and to evaluate its efficiency using RULA and NERPA methods. METHODS: This cross-sectional study conducted on 108 students, in which an adjustable and portable ergonomic desk designed and built based on 10 anthropometric dimensions of students and the length and width of 10 different laptop models. Two assessment methods, RULA and NERPA, were used. Wilcoxon statistic test and SPSS version 26 software used for data analysis. RESULTS: The dimensions of the desk were calculated in three positions, and the desk was made with the ability to adjust height, width and tilt, each with two degrees of freedom. The statistical analysis comparing score of RULA and NERPA in two situations without using a desk and using an ergonomic laptop desk had a significant difference (P-value < 0.001). Comparison of RULA and NERPA scores showed that NERPA evaluated the low ergonomic risk level better than RULA method. CONCLUSIONS: Due to the ability to adjust the designed desk, the changes in RULA and NERPA score in all three modes, it indicates the effectiveness of the table in improving the body posture of users when using a laptop.

Sitting versus standing work postures during simulated laparoscopic surgery: in terms of user preferences, comfort, performance and biomechanics

Prolonged standing in surgery has been linked to an increased risk of musculoskeletal disorders. The aim of this study was to determine whether sitting could serve as an alternative work posture in laparoscopic procedures. Twenty medical students in their third and fourth years were recruited. Sitting and standing were compared at two task complexity levels on a laparoscopic surgery simulator. Measured variables included user posture preferences, perceived discomfort, performance and biomechanics. Electromyography data from the upper trapezius and erector spinae muscles were analysed. Results showed that posture did not affect surgical performance and erector spinae muscle activation. Sitting showed higher muscle activation at the trapezius muscles; however, perceived discomfort was unaffected. Most participants preferred sitting for the difficult task and standing for the easy task. Findings showed that sitting, with appropriate seat design considerations, could serve as an alternative or even as a preferred work posture for simulated laparoscopic procedures.

Comparison of Neck Pain and Posture with Spine Angle Tracking System between Static and Dynamic Computer Monitor Use

This study investigates the effect of dynamic changes in monitor height and tilt on neck pain and posture of computer users. Using a wearable device, we aim to compare neck pain and spine angle between static and dynamic monitors. A spine angle tracking system using the Inertial Measurement Unit (IMU) was proposed, and the accuracy was validated. Eight office workers participated for five hours over two days, and each day used either a static monitor or a dynamic monitor that changed height and tilt every 30 min. The angles of C0, C7, L1, and S1 endplates were estimated using the proposed system. Changes in neck pain and spine angle with time were compared in static and dynamic monitors. The intraclass correlation coefficient confirmed a high concordance between the estimated and actual angles (p < 0.001). Rehabilitation Bioengineering Group (RBG) score increased less in the dynamic monitor compared to the static monitor (p = 0.003). Spinal curvatures are bent in the static monitor compared to the dynamic monitor. The estimated angles aligned well with X-ray measurements. A dynamic monitor that changes height and tilt at regular intervals may reduce neck pain increase and reduce bend forward posture compared to a static monitor.

Hubungan Postur Kerja Pengguna Komputer Dengan Keluhan Muskuloskeletal Pada Staf Logistik Jakarta Timur

Background: Working using computer or also known as video display terminal (VDT) is a work which have a high risk of musculoskeletal disorder. The posture of body during work is one of the factors which may have effect on musculoskeletal disorder. Objective: The research was to discover the correlation of the working posture of computer user two towards musculoskeletal disorder on the Staffs of X Logistics East Jakarta. Methods: The research used cross sectional while the sampling was conducted using purposive sampling technique. The amount of sample for quantitative research is 79 respondents, while the amount of sample for qualitative research is 8 respondents. Respondents were analyzed using Rapid Office Strain Assessment (ROSA), Nordic Body Map (NBM), Global Physical Activity Questionnaire (GPAQ) version 2 and Copenhagen Psychosocial Questionnaire III (CopSoq III). Results: The result of research showed that, from 79 respondents, there were (45.6%) low category musculoskeletal disorder and (54.4%) moderate category musculoskeletal disorder. Statistical test analysis with Chi Square test (CI=95% and = 5%) showed the results of correlation between individual factors and musculoskeletal disorder, namely age (p=0.002), gender (p=0.000), physical activity (p=0.017) , duration of work (p=0.000), and unrelated factors, namely smoking habits (p=0.288), and work posture (p=0.641), chairs (p=1), desks (p=0.464), psychosocial (p=0.286), work demands (p=0.805), organizational characteristics and work content (p=1), interpersonal relationships at work and leadership (p=0.540). Conclusion: Based on the analysis, the factors which influenced musculoskeletal disorder on Staffs of X Logistics in East Jakarta are age, gender, physical activity, and duration of work.

Redesign the Wood Cutting Saw to Be More Ergonomic Using The TRIZ Method

A cutting saw is one of the tools used to cut wood material. In this regard, the cutting saw still has shortcomings in its application. Several testing methods were conducted to analyze the failures of cutting saws circulating in the community, including the Nordic body map questionnaire. After checking directly, there are complaints of pain when using a cutting saw, especially on the right hand. For this reason, it is necessary to redesign it as a consideration later expected to improve the shortcomings in the current cutting saw. Several methods are used in this redesign, including TRIZ, OWAS, and anthropometry. TRIZ is a method used in the development of a design. This method's concept leads to solutions to the problem of contradictions that occur and leads to innovative solutions that have been tested with 100% success. After obtaining the function or attributes of the product, the next stage is to improve the user's posture so that the cutting saw tool can be used optimally and can initiate. The OWAS method corrects the postural position used in cutting saws. The specification of the handsaw product design based on the processing of the voice of the customer using a tree analysis diagram is that the features are reducing fatigue levels and being able to cut quickly, as well as for reliability, namely the handle with anti-slip qualities.

Diagnosis and management of transient smartphone blindness: A literature review

The development of smartphones worldwide has rapidly increased the number of smartphone users. Although smartphones have many benefits, prolonged use causes various visual disorders, of which transient smartphone blindness (TSB) is one of the most important concerns. This study aims to analyse the phenomenon of TSB and explore its etiology, pathophysiology, symptoms, and examination to determine the diagnosis and management. Transient smartphone blindness is a new physiologic phenomenon caused by exposure to a certain level of smartphone bright light and the body posture of the smartphone user. It leads to the use of monocular vision to stare at the smartphone. By exploring recent literature, this study found that patients with TSB experienced retinal photopigment bleaching, which decreased light sensitivity. Typically, the sensitivity returned physiologically after several minutes. Patients with this blindness showed several symptoms. For example, they perceived shapes, outlines, or figures during the blackout. The diagnosis of TSB should be primarily based on a detailed history of smartphone use, with the differential diagnosis based on circumstance or occurrence. This diagnosis is useful to distinguish it from transient ischemic attack (TIA). Transient smartphone blindness is a basic monocular transient loss that does not require therapy or drugs. However, it was found that the reassurance of patients’ condition and suggestions on smartphone use were sufficient for the intervention. With a limited scientific study of TSB, this review is the first to raise the discussion topic. It is expected to help physicians to diagnose TSB significantly. In addition, this study will enrich the literature, particularly on the scientific and clinical mechanisms of recognising TSB for clinical diagnosis and management.

Вплив занять кіберспортом на здоров’я здобувачів вищої освіти

Cyber athletes are affected by a number of threatening factors. Against the background of the growing popularity of e-sports among students of higher educational institutions, the question of the impact of e-sports on their health is becoming more and more relevant. The purpose of the study is to investigate the negative factors and check the impact of e-sports on the health of higher education students. The survey was conducted online using Google Forms. It lasted from January 20 to June 6, 2023 and involved 111 higher education students. The fact that e sports is much more popular among male students compared to female students was confirmed by previous analysis. Therefore, the questionnaires of 46 students were selected for further research, 27 of which were engaged in e-sports and 19 did not show a particular interest in such activity or did not play computer games at all. The results. To assess the impact of e-sports activities on players’ health, we compared student survey results based on their e-sports activities. It was established that, despite the absence of statistically significant differences (p>0.05), under the influence of e-sports, students have a tendency to disorders of the musculoskeletal system, increased muscle pain, and impaired vision. Under the influence of e-sports, the risk of psycho-emotional problems increases statistically (p<0.05). It has been proven that the most dangerous factors of negative impact on the health of e-sportsmen are constant interaction with the monitor, prolonged stay in a static position while sitting at the computer, violation of the ergonomically optimal posture of the PC user, as well as violation of the balance between e-sports and other types of activities, which causes psycho-emotional disorders. It was established that there are statistically significant (p<0.05) differences between the frequency of cases when e-sports players lead a passive lifestyle or devote less time to healthrecreational physical activity compared to students who do not engage in e-sports. Conclusions. The reduced level of physical activity of higher education students engaged in e-sports can increase the effect of negative factors.

Strain Detecting Smart Chair

Abstract: Prolonged sitting with poor posture can lead to discomfort and health issues. This paper presents the design and implementation of a posture-detecting smart chair aimed at promoting ergonomic awareness and preventing discomfort associated with improper sitting positions. The proposed system utilizes an Arduino Uno microcontroller and ultrasonic sensors to monitor the user's posture in real-time. The system consists of an Arduino Uno microcontroller, an ultrasonic sensor (HCSR04), power supply, connectivity. The ultrasonic sensor is strategically positioned to measure the distance between the chair and the user's back. The Arduino Uno processes the sensor data and notify the user to encourage a correct sitting posture when improper positioning is detected. The algorithm involves continuous monitoring of the ultrasonic sensor's readings. When the distance between the user and the chair falls below a predefined threshold, indicative of poor posture, the system notify user to change the posture. Additionally, feedback mechanisms such as LEDs or buzzers provide real-time alerts to the user, enhancing their awareness of their sitting habits. This low-cost, Arduino-based solution offers a practical and accessible means to address the increasingly prevalent issue of poor posture. The proposed smart chair contributes to the growing field of smart furniture, leveraging simple yet effective technology to promote health-conscious behaviors in daily life

ANALISIS INDIKASI RESIKO POSTUR PENGGUNA DESAIN MEJA BELAJAR PORTABEL

Study portable desks can help people easily move from one another place. Using a study portable desk would make users fix the position once a few moments so that they risk experiencing bodily discomfort. Analysis indications of posture risk can be done by selecting launch rapid upper limb assessment (RULA) analysis from the ergonomic tools toolbar in CATIA software. This research aims to identify movements that occur when using a portable study desk and to analyze user posture risks that can be experienced when using a portable study desk. Based on the research results, it is known that the body posture of portable study desk users for group A on the upper arms is in the range of 20-45°, and the lower arms are in the range of 60-100°. The wrist enters the neutral position range. The rotation of the wrist can be seen that the hand is pointing inward. It has a degree of freedom of 90° with a maximum flexion angle of 160° and a minimum extension angle of 0°. Group B body posture for the stem body has a degree of freedom of 0°. The legs experience a slight downward movement with a degree of freedom of 6.061° and a maximum flexion angle of 135°. Posture analysis results for body parts. Details of the upper arm, forearm, wrist, and wrist twist have a score of 1, which means no posture needs to be corrected and the posture is acceptable. Details of body parts, namely neck, trunk, and legs, are indicated in green, which means no posture needs to be corrected and the posture is acceptable. The score results for body parts with the static posture option get an assessment score of 2 with a green color indication, so it can be concluded that the risk indication for this posture is acceptable.

Deep-reinforcement-learning-based robot motion strategies for grabbing objects from human hands

BackgroundRobot grasping encompasses a wide range of research areas; however, most studies have been focused on the grasping of only stationary objects in a scene; only a few studies on how to grasp objects from a user's hand have been conducted. In this paper, a robot grasping algorithm based on deep reinforcement learning (RGRL) is proposed. MethodsThe RGRL takes the relative positions of the robot and the object in a user's hand as input and outputs the best action of the robot in the current state. Thus, the proposed algorithm realizes the functions of autonomous path planning and grasping objects safely from the hands of users. A new method for improving the safety of human–robot cooperation is explored. To solve the problems of a low utilization rate and slow convergence of reinforcement learning algorithms, the RGRL is first trained in a simulation scene, and then, the model parameters are applied to a real scene. To reduce the difference between the simulated and real scenes, domain randomization is applied to randomly change the positions and angles of objects in the simulated scenes at regular intervals, thereby improving the diversity of the training samples and robustness of the algorithm. ResultsThe RGRL's effectiveness and accuracy are verified by evaluating it on both simulated and real scenes, and the results show that the RGRL can achieve an accuracy of more than 80% in both cases. ConclusionsRGRL is a robot grasping algorithm that employs domain randomization and deep reinforcement learning for effective grasping in simulated and real scenes. However, it lacks flexibility in adapting to different grasping poses, prompting future research in achieving safe grasping for diverse user postures.

Influence of user posture and virtual exercise on impression of locomotion during VR observation.

A seated user watching his avatar walking in Virtual Reality (VR) may have an impression of walking. In this paper, we show that such an impression can be extended to other postures and other locomotion exercises. We present two user studies in which participants wore a VR headset and observed a first-person avatar performing virtual exercises. In the first experiment, the avatar walked and the participants (n=36) tested the simulation in 3 different postures (standing, sitting and Fowler's posture). In the second experiment, other participants (n=18) were sitting and observed the avatar walking, jogging or stepping over virtual obstacles. We evaluated the impression of locomotion by measuring the impression of walking (respectively jogging or stepping) and embodiment in both experiments. The results show that participants had the impression of locomotion in either sitting, standing and Fowler's posture. However, Fowler's posture significantly decreased both the level of embodiment and the impression of locomotion. The sitting posture seems to decrease the sense of agency compared to standing posture. Results also show that the majority of the participants experienced an impression of locomotion during the virtual walking, jogging, and stepping exercises. The embodiment was not influenced by the type of virtual exercise. Overall, our results suggest that an impression of locomotion can be elicited in different users' postures and during different virtual locomotion exercises. They provide valuable insight for numerous VR applications in which the user observes a self-avatar moving, such as video games, gait rehabilitation, training, etc.

The correlation between smartphone use and musculoskeletal symptom

Several issues arise from using smartphones while sitting and lying down, such as poor posture and physical discomfort. Therefore, this research aims to assess the ergonomic risk level of smartphone users and determine the correlation between self-reported musculoskeletal disorders (MSDs) and ergonomic risk level. Data were collected from 90 participants, aged 18 to 24, through video recording while seated and using a smartphone. MSDs were measured using the Modified Standardised Nordic Questionnaires (SNQ) and the Numerical Rating Scale (NRS). Rapid Upper Limb Assessment (RULA) was used to evaluate ergonomic risks in the posture of smartphone users. Furthermore, the correlation between MSDs and the ergonomic risk levels was evaluated using Chi-Square and Fisher's exact tests. Most smartphone users had RULA scores between 6 and 7 for both the left and right sides, suggesting a need for immediate investigation and improvement. The results showed a strong correlation between the right sided RULA total score and MSDs in the neck and upper back. Other results showed there was a significant correlation between RULA B and RULA D scores with neck MSDs, as well as between the RULA score of the right upper arm and MSDs in the right shoulder, and between the RULA score of the neck and MSDs in the neck. The trunk RULA score also had a significant correlation with upper back MSDs. The research showed that smartphone users face significant ergonomic risks.

Gym & Yoga Trainer Using Machine Learning

Abstract: The project titled "Gym and Yoga Trainer Using Machine Learning" aims to leverage the power of machine learning algorithms to enhance the gym and yoga training experience. This innovative system utilizes computer vision, motion tracking, and data analysis to create an intelligent training platform. The primary objective of this project is to develop a system that can analyze the user's movements during gym workouts and yoga sessions in real-time. By employing computer vision techniques, the system captures and analyzes the user's posture, form, and technique, providing instant feedback on areas that require improvement. This real-time feedback helps users perform exercises correctly, reduce the risk of injury, and optimize their fitness routines.

The effect of hands synchronicity on users perceived arms Fatigue in Virtual reality environment

The use of virtual reality (VR) system has become more common with the arrival of a new generation of headsets. This increase in accessibility has in turn led to VR being used for applications which require longer sessions, such as video games, artistic expression, rehabilitation, and so on. Taking muscular fatigue in account for the VR applications is therefore becoming essential to ensure a comfort of usage and also to avoid injuries. In addition, usual interactions in these diverse applications are very varied and may require the use of one or two hands, synchronized or not. However, little research has focused on fatigue produced by one and two handed interactions especially during mid-air interaction in VR environment. In this paper, we examine the effect of hands synchronicity and movement direction on the user perceived arm fatigue in VR environment during a simple (one line of targets) and a composite (two lines of targets) pointing tasks performed using both controlled and free hands synchronicity. Our findings indicate that to optimize the relationship between fatigue and efficiency, it seems necessary to select the synchronicity of hands depending on the performed task. Furthermore, it is desirable to permit the users to use the hands synchronicity they prefer. In addition, distance covered by the hand and changes in user posture could be used in real-time as indicators of fatigue to trigger changes in the interface, or notifications. Finally, our findings reveal that the directions of movement along the vertical axis and some diagonals are more tiring than those of the horizontal plane, which suggests that it would be better to favor the use of horizontal directions.

Design and modeling using finite element analysis for the sitting posture of computer users based on ergonomic perspective

Design and modeling using finite element analysis for the sitting posture of computer users based on ergonomic perspective

USING ANTHROPOMETRIC DATA TO DESIGN A FORTABLE STUDY DESK AND USER POSTURE ANALYSIS WITH THE RAPPID UPPER LIMB ASSESSMENT (RULA) METHOD

The use portable study desk that is designed to be easy moved still make complaints in muscles and bones give risk for posture. Design improvements can be based on measurements results of static anthropometric and dynamic anthropometric to identify the risk of posture. The method used in this reaserch is a Rapid Upper Limb Assessment (RULA) method to analyze the risk of posture users of portable study desk, while for the design of study desk using anthropometric data, The purpose of this study was to design a portable study table and analyze the risk posture that occur when users use a portable study desk using the RULA method. The results of study show that design desk study using anthropometric data obtained dimensions of 800 mm in length and 420 mm in width. The table height from the floor to the table surface is 220 mm high. a place to put a D100 mm glass, and there is a place to put a 400 mm cell phone or iPad along with a hole for the cable, there is a Diameter 40 mm. The 2-dimensional and 3-dimensional design process uses Catia software. The results of the Rapid Upper Limb Assessment (RULA) analysis show that the user's posture risk is indicated in green color, which means that there is no posture that needs to be corrected and that posture is acceptable except for the posture muscles (muscles) which are are indicated red color so needed move as soon possible or muscle stretching, this is in line with Osha (2020) who states that static postures are recommended for stretching muscles to avoid muscle fatigue.

Modelling Proper and Improper Sitting Posture of Computer Users Using Machine Vision for a Human–Computer Intelligent Interactive System during COVID-19

Human posture recognition is one of the most challenging tasks due to the variation in human appearance, changes in the background and illumination, additional noise in the frame, and diverse characteristics and amount of data generated. Aside from these, generating a high configuration for recognition of human body parts, occlusion, nearly identical parts of the body, variations of colors due to clothing, and other various factors make this task one of the hardest in computer vision. Therefore, these studies require high-computing devices and machines that could handle the computational load of this task. This study used a small-scale convolutional neural network and a smartphone built-in camera to recognize proper and improper sitting posture in a work-from-home setup. Aside from the recognition of body points, this study also utilized points’ distances and angles to help in recognition. Overall, the study was able to develop two objective datasets capturing the left and right side of the participants with the supervision and guidance of licensed physical therapists. The study shows accuracies of 85.18% and 92.07%, and kappas of 0.691 and 0.838, respectively. The system was developed, implemented, and tested in a work-from-home environment.

Managing Identity and Access Management (IAM) in Amazon Web Services (AWS)

Identity and Access Management (IAM) plays a pivotal role within Amazon Web Services (AWS) by governing the utilization of cloud resources and enhancing the overall security of the AWS ecosystem. IAM allows AWS users to effectively manage resource access while ensuring a robust security framework. This exploration delves into the fundamental concepts that underpin IAM, shedding light on authentication and authorization processes, best practices, practical implementation scenarios, and the convergence of IAM and security, and provides a forward-looking perspective into emerging trends in the field. IAM's significance lies in its ability to control access for individual users and groups, roles, and policies, ensuring the principle of least privilege and minimizing security risks. Multi-factor authentication (MFA) is a key facet of IAM within AWS, offering an extra layer of security and identity verification. This enables organizations to fortify access control measures, safeguarding their AWS resources from potential threats. In addition to these foundational concepts, this exploration delves into practical implementations, elucidating how IAM can be leveraged to meet realworld security and compliance requirements. IAM's robust features enable users to define and manage access permissions with precision, catering to the specific needs of their organizations. Furthermore, this abstract introduces the IAM Query API, which provides a means to interact directly with AWS services. The IAM Query API supports GET and POST methods through APIs, offering developers and administrators a more streamlined approach to managing access to AWS resources. IAM is a linchpin in AWS security, ensuring that access to cloud resources is fine-tuned, well-protected, and compliant with best practices. The continued evolution of IAM, including integrating emerging technologies and security measures, promises to further enhance the security posture of AWS users and the cloud computing ecosystem.