scholarly journals The Role of the Location of Personal Exposimeters on the Human Body in Their Use for Assessing Exposure to the Electromagnetic Field in the Radiofrequency Range 98–2450 MHz and Compliance Analysis: Evaluation by Virtual Measurements

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Krzysztof Gryz ◽  
Patryk Zradziński ◽  
Jolanta Karpowicz
Keyword(s):  
Human Body ◽  
Measurement Errors ◽  
The Body ◽  
Back Side ◽  
Human Body Model ◽  
Field Exposure ◽  
Limit Values ◽  
Exposure Limit ◽  
Measurement Results ◽  
Exposure Conditions

The use of radiofrequency (98–2450 MHz range) personal exposimeters to measure the electric field (E-field) in far-field exposure conditions was modelled numerically using human body model Gustav and finite integration technique software. Calculations with 256 models of exposure scenarios show that the human body has a significant influence on the results of measurements using a single body-worn exposimeter in various locations near the body ((from −96 to +133)%, measurement errors with respect to the unperturbedE-field value). When an exposure assessment involves the exposure limitations provided for the strength of an unperturbedE-field. To improve the application of exposimeters in compliance tests, such discrepancies in the results of measurements by a body-worn exposimeter may be compensated by using of a correction factor applied to the measurement results or alternatively to the exposure limit values. The location of a single exposimeter on the waist to the back side of the human body or on the front of the chest reduces the range of exposure assessments uncertainty (covering various exposure conditions). However, still the uncertainty of exposure assessments using a single exposimeter remains significantly higher than the assessment of the unperturbedE-field using spot measurements.

scholarly journals Human Body Model for Channel Characterization Based on Ray-Tracing

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Lei Xiong ◽  
Haiyang Miao ◽  
Zhiyi Yao
Keyword(s):  
Ray Tracing ◽  
Human Body ◽  
Path Loss ◽  
Channel Modeling ◽  
The Body ◽  
60 Ghz ◽  
Human Body Model ◽  
Body Model ◽  
Measurement Results ◽  
Good Agreement

The propagation channel around human body will fluctuate due to the body effects, so it is essential to investigate the body channel. As an important method of channel modeling, ray-tracing (RT) is affected by the human body model. In this paper, a realistic human body is modeled with the idea of greedy algorithm. Based on the RT simulation and measurement results of path loss (PL), we derive the approximate shapes of the torso, head, arms, and legs, and propose a reference human body model whose credibility and accuracy have been verified at 2.4 GHz and 60 GHz. These results prove that the simulation results based on the reference human body model are in good agreement with the measurement values. In addition, the reference human body model can be adjusted according to the realistic dimension data of body.

A New Method to Concentrate Electromagnetic Field Within ROI Using a High Dielectric Material in 3T Body MRI

2013 ◽  
Author(s):  
Bu S. Park ◽  
Sunder S. Rajan ◽  
Leonardo M. Angelone
Keyword(s):  
Numerical Simulation ◽  
Electromagnetic Field ◽  
Human Body ◽  
Region Of Interest ◽  
Dielectric Materials ◽  
The Body ◽  
Human Body Model ◽  
Body Model ◽  
Simulation Results ◽  
High Dielectric

We present numerical simulation results showing that high dielectric materials (HDMs) when placed between the human body model and the body coil significantly alter the electromagnetic field inside the body. The numerical simulation results show that the electromagnetic field (E, B, and SAR) within a region of interest (ROI) is concentrated (increased). In addition, the average electromagnetic fields decreased significantly outside the region of interest. The calculation results using a human body model and HDM of Barium Strontium Titanate (BST) show that the mean local SAR was decreased by about 56% (i.e., 18.7 vs. 8.2 W/kg) within the body model.

Nitroethane Documentation of proposed values of occupational exposure limits (OELs)

2017 ◽  
Vol 33 (1(91)) ◽  
pp. 97-113
Author(s):  
Andrzej Sapota ◽  
Małgorzata Skrzypińska-Gawrysiak ◽  
ANNA KILANOWICZ
Keyword(s):  
Occupational Exposure ◽  
The Body ◽  
Exposure Level ◽  
Occupational Exposure Limits ◽  
Exposure Limits ◽  
Short Term ◽  
Cellulose Esters ◽  
Limit Values ◽  
Exposure Limit ◽  
Short Term Exposure

Nitroethane is a colorless oily liquid with a mild fruity odor. It is used mainly as a pro-pellant (e.g., fuel for rockets), and as a solvent or dissolvent agent for cellulose esters, resins (vinyl and alkyd) and waxes, and also in chemical synthesis.Occupational exposure to nitroethane may occur during the process of its production and processing. There are no data on air concentra-tions of nitroethane in occupational exposure. In 2010–2015, workers in Poland were not exposed to nitroethane concentrations exceed-ing the maximum allowable value – 75 mg/m3 (the limit value valid since 2010).Nitroethane can be absorbed into the body via inhalation of its vapors or by ingestion.The discussed cases of nitroethane acute poi-soning caused by an accidental ingestion of artificial fingernail remover containing pure nitroethane concerned children under three years. Few hours after ingestion, cyanosis and sporadic vomiting were observed in children. The methemoglobin level reached 40÷50%.Neither data on chronic nitroethane poisoning in humans nor data obtained from epidemio-logical studies are available.On the basis of the results of acute toxicity studies nitroethane has been categorized in the group of hazardous compounds. However, eye and dermal irritation or allergic effects have not been evidenced. The studies of sub-chronic (4 and 90 days) and chronic (2 years) exposure to nitroethane per-formed on rats and mice (concentration range 310 ÷ 12 400 mg/m3) revealed the methemo-globinogenic effect of this compound and a minor damage to liver, spleen, salivary gland and nasal turbinates.Niroethane has shown neither mutagenic nor carcinogenic effects. Its influence on fertility has not been evidenced either. After chronic exposure (2 years) of rats to ni-troethane at concentration of 525 mg/m3 (the lowest observed adverse effect level – LOAEL), a slight change in a body mass of exposed fe-male animals and subtle changes in biochemi-cal parameters were observed, but there were no anomalies in hematological and histopatho-logical examinations.The value of 62 mg/m3 has been suggested to be adopted as the MAC value for nitroethane after applying the LOAEL value of 525 mg/m3 and relevant coefficients of uncertainty. The STEL value for nitroethane was proposed ac-cording to the methodology for determining short term exposure level value for irritating substances as three times MAC value (186 mg/m3) to prevent the effects of sensory irri-tations in humans. Because of its methemoglo-binogenic effect, 2% Met-Hb has been suggest-ed to be adopted as the value of biological ex-posure index (BEI), like the value already adopted for all methemoglobinogenic sub-stances.The Scientific Committee on Occupational Exposure Limits (SCOEL) proposed the time-weighted average (TWA) for nitroethane (8 h) as 62 mg/m3 (20 ppm), short-term exposure limit (STEL, 15 min) as 312 mg/m3 (100 ppm) and “skin” notation.Proposed OEL and STEL values for nitroethane were subjected to public consultation, con-ducted in 2011 by contact points, during which Poland did not raise any objections to the pro-posals. The proposed values for nitroethane by SCOEL has been adopted by the Advisory Committee on Safety and Health at Work UE (ACSH) and included in the draft directive establishing the IV list of indicative occupa-tional exposure limit values.

The Key Role of Headrest Optimization in Driver Comfort

2019 ◽  
Vol 24 (3) ◽  
pp. 592-599
Author(s):  
Hamid Gheibollahi ◽  
Masoud Masih-Tehrani ◽  
Mohammadmehdi Niroobakhsh
Keyword(s):  
Human Body ◽  
The Body ◽  
Human Body Model ◽  
Sitting Posture ◽  
Conventional Vehicle ◽  
Body Model ◽  
Basic Model ◽  
Proposed Model ◽  
Stiffness And Damping

In this study, adding a headrest to the conventional vehicle driver seat is investigated to improve the driver comfort and decrease the driver damages. For this purpose, a conventional biomechanical human body model of wholebody vibrations is provided and modified by adding a head degree of freedom to the body model and a headrest to the seat model. The basic model is in the sitting posture, lumped parameters and has nine DOFs for the human body, on contrary to the proposed model which has ten DOFs. The new human body DOF is the twisting motion of the head and neck. This new DOF is generated because of headrest adding to the driver’s seat. To determine the head discomforts, the Seat to Head (STH) indexes are studied in two directions: horizontal and vertical. The Genetic Algorithm (GA) is used to optimize the STH in different directions. The optimization variables are stiffness and damping parameters of the driver’s seat which are 12 for the basic model and are 16 for a new seat. The integer programming is used for time reduction. The results show that new seat (equipped by headrest) has very better STH in both directions.

scholarly journals Human Motion Gesture Recognition Based on Computer Vision

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Rui Ma ◽  
Zhendong Zhang ◽  
Enqing Chen
Keyword(s):  
Computer Vision ◽  
Gesture Recognition ◽  
Human Body ◽  
Spatial Relationship ◽  
Research Direction ◽  
Human Motion ◽  
The Body ◽  
Body Parts ◽  
Human Body Model ◽  
Relationship Of

Human motion gesture recognition is the most challenging research direction in the field of computer vision, and it is widely used in human-computer interaction, intelligent monitoring, virtual reality, human behaviour analysis, and other fields. This paper proposes a new type of deep convolutional generation confrontation network to recognize human motion pose. This method uses a deep convolutional stacked hourglass network to accurately extract the location of key joint points on the image. The generation and identification part of the network is designed to encode the first hierarchy (parent) and the second hierarchy (child) and show the spatial relationship of human body parts. The generator and the discriminator are designed as two parts in the network, and they are connected together in order to encode the possible relationship of appearance and, at the same time, the possibility of the existence of human body parts and the relationship between each part of the body and its parental part coding. In the image, the key nodes of the human body model and the general body posture can be identified more accurately. The method has been tested on different data sets. In most cases, the results obtained by the proposed method are better than those of other comparison methods.

scholarly journals Analysis of Human Body Shadowing Effect on Wireless Sensor Networks Operating in the 2.4 GHz Band

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3412 ◽  
Author(s):  
Łukasz Januszkiewicz
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Human Body ◽  
Path Loss ◽  
Small Region ◽  
The Body ◽  
Wireless Sensor ◽  
Indoor Environments ◽  
Human Body Model ◽  
Shadowing Effect

Miniaturized wireless sensors are designed to run on limited power resources, requiring minimization of transmit power and lowering of the fade margin in the link budget. One factor that has an important impact on wireless sensor network design is path loss between the transmitter and the receiver. This paper presents an analysis of the influence of human bodies on path loss in the 2.4 GHz band, which is commonly used for wireless sensor networks. The effect of body shadowing was first analyzed in full wave computer simulations using the finite-difference time-domain method. Due to the high numerical burden, the simulations were limited to only a small region around the human body. To analyze the performance of networks in larger indoor environments, a human body model is proposed that can be used for simulations with a ray-based computer program. The proposed model of human body is the main contribution of this paper. It was used to analyze the body shadowing effect in a typical indoor environment. The results were found to be in good agreement with measurements.

A Momentum-Based Algorithm for Identifying the Inertia Properties of a Human Body: A Preliminary Study

2010 ◽  
Author(s):  
Qi Lu ◽  
Ou Ma
Keyword(s):  
Human Body ◽  
Measurement Errors ◽  
Equations Of Motion ◽  
Least Square Method ◽  
Internal Force ◽  
Momentum Equation ◽  
The Body ◽  
Least Square ◽  
Identification Algorithm ◽  
Force Data

The body segment parameters (BSP) of a human body are critical information for modeling, simulating, and understanding human dynamics. The determination of BSPs of human bodies has received increasing attention in biomechanics, sport science, ergonomics, rehabilitation and other fields. This paper presents a momentum-based identification algorithm for dynamically estimating the BSPs of a human body. The human body is modeled as a multibody dynamical system, and the momentum equation of the system can be derived by applying the principle of impulse and momentum. It is possible to formulate the momentum equations corresponding to a set of experiment tests into a linear regression form with respect to the unknown BSPs, which then can be solved using the least square method or other methods. The momentum-based algorithm requires inputting position, velocity, and external force data only. Since acceleration and all the internal force data is not needed, the algorithm is less demanding on measurements and is also less sensitive to measurement errors. As a result, it is practically more appealing than the algorithms depending on the equations of motion. The paper presents the momentum-based inertia identification algorithm along with a simulation study of the algorithm using a simplified trunk-leg model representing a main portion of a human body.

Human Body Pose Estimation with Particle Swarm Optimisation

2008 ◽  
Vol 16 (4) ◽  
pp. 509-528 ◽  
Author(s):  
Špela Ivekovič ◽  
Emanuele Trucco ◽  
Yvan R. Petillot
Keyword(s):  
Pose Estimation ◽  
Human Body ◽  
Particle Swarm ◽  
Search Space ◽  
The Body ◽  
Particle Swarm Optimisation ◽  
Human Body Model ◽  
Still Images ◽  
Body Pose Estimation

In this paper we address the problem of human body pose estimation from still images. A multi-view set of images of a person sitting at a table is acquired and the pose estimated. Reliable and efficient pose estimation from still images represents an important part of more complex algorithms, such as tracking human body pose in a video sequence, where it can be used to automatically initialise the tracker on the first frame. The quality of the initialisation influences the performance of the tracker in the subsequent frames. We formulate the body pose estimation as an analysis-by-synthesis optimisation algorithm, where a generic 3D human body model is used to illustrate the pose and the silhouettes extracted from the images are used as constraints. A simple test with gradient descent optimisation run from randomly selected initial positions in the search space shows that a more powerful optimisation method is required. We investigate the suitability of the Particle Swarm Optimisation (PSO) for solving this problem and compare its performance with an equivalent algorithm using Simulated Annealing (SA). Our tests show that the PSO outperforms the SA in terms of accuracy and consistency of the results, as well as speed of convergence.

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