Health informatics � Categorial structure for representation of 3D human body position system

This chapter situates public health informatics (PHI) within an informatics perspective and the two broad trends relevant to its understanding; the first concerns medical and health informatics, which focuses on the application of information and communications technologies for the better understanding of the human body. This includes clinical, nursing, radiology, drug-related informatics, among others. This domain has been driven largely by clinicians, and informed by the disciplines of medicine, informatics, and cognitive and behavioural psychology. This field of study and practice has largely been focused on in North America and Europe, while low and middle-income countries (LMICs) have broadly been excluded. The second trend is of PHI systems, which have focused on the population, and practised the collection and use of aggregate statistics. This focus has largely been promoted by statisticians and demographers, and practised primarily in LMICs. These two trends have remained isolated from each other, yet evolved simultaneously.

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Effect of human body position on gamma radiation dose rate from granite stones

Journal of Environmental Health Science and Engineering ◽

10.1007/s40201-021-00660-7 ◽

2021 ◽

Author(s):

Motahareh Kefalati ◽

S. Farhad Masoudi ◽

Akbar Abbasi

Keyword(s):

Radiation Dose ◽

Gamma Radiation ◽

Dose Rate ◽

Human Body ◽

Body Position ◽

Radiation Dose Rate ◽

Gamma Radiation Dose

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The Impact of Prolonged Sitting Hours on the Correct Standing up Position of Elementary School Students in Developed Rural Area

Materiale Plastice ◽

10.37358/mp.19.4.5273 ◽

2019 ◽

Vol 56 (4) ◽

pp. 831-839

Author(s):

Emanuela Georgiana Gal-Nadasan ◽

Norbert Gal-Nadasan ◽

Dan V. Poenaru ◽

Dan Surducan ◽

Diana Popa-Andrei ◽

...

Keyword(s):

Elementary School ◽

Rural Area ◽

Elementary School Students ◽

Human Body ◽

Body Position ◽

Spinal Column ◽

School Students ◽

Incorrect Position ◽

Standing Up ◽

The Impact

At young ages the spinal column, which is the central support system of the human body, is susceptible to malformations, especially if the children are sitting in an incorrect position for long period. Our study examines the case of several elementary school students from a developed rural area. The aim of this study to analyze the impact of long sitting hours (5-6 hours) in incorrect position at on the normal standing up position at elementary school students. The study group for our study consisted of 80 elementary school students were recruited from a local rural elementary school. Each student was evaluated using a Kinect based system to determine their general standing up position. For 14 weeks, twice a week, each student has executed 5 type of Schroth exercises to improve their general body position. The first evaluation has shown that the students general standing up position is affected from the long sitting hours in the school benches. Most of them have shown misalignments at the shoulder and hip levels. In many cases one of the shoulders was higher than the other and the same is true for the hips as well. After 14 weeks of physiotherapy based on Schroth exercises the miss alignments were reduced to a bare minim. The results have shown that long sitting hours in incorrect positions can affect the spinal column and the standing up posture of the human body. In many cases malicious postures start to develop from childhood. If not treated they can transform in hyper-kyphotic and scoliotic postures which can induce other complications. If these malicious postures are observed in early stages of the children and with only 2 hours a week of physiotherapy based on Schroth exercise the postures can be corrected and the hyper-kyphotic and scoliotic postures can be avoided.

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A Specific Algorithm Based on Motion Direction Prediction

Complexity ◽

10.1155/2021/6678596 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Zhesen Chu ◽

Min Li

Keyword(s):

Human Body ◽

Body Position ◽

Motion Vector ◽

Human Motion ◽

Generative Model ◽

Experimental Results ◽

Body Motion ◽

Motion Vectors ◽

Motion Direction ◽

Current Frame

In this paper, we study the estimation of motion direction prediction for fast motion and propose a threshold-based human target detection algorithm using motion vectors and other data as human target feature information. The motion vectors are partitioned into regions by normalization to form a motion vector field, which is then preprocessed, and then the human body target is detected through its motion vector region block-temporal correlation to detect the human body motion target. The experimental results show that the algorithm is effective in detecting human motion targets in videos with the camera relatively stationary. The algorithm predicts the human body position in the reference frame of the current frame in the video by forward mapping the motion vector of the current frame, then uses the motion vector direction angle histogram as a matching feature, and combines it with a region matching strategy to track the human body target in the predicted region, thus realizing the human body target tracking effect. The algorithm is experimentally proven to effectively track human motion targets in videos with relatively static backgrounds. To address the problem of sample diversity and lack of quantity in a multitarget tracking environment, a generative model based on the conditional variational self-encoder conditional generation of adversarial networks is proposed, and the performance of the generative model is verified using pedestrian reidentification and other datasets, and the experimental results show that the method can take advantage of the advantages of both models to improve the quality of the generated results.

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Selected dynamic anthropometrics and body characteristics for posture corrector fit

Communications in Development and Assembling of Textile Products ◽

10.25367/cdatp.2020.1.p96-103 ◽

2020 ◽

Vol 1 (2) ◽

pp. 96-103

Author(s):

Inga DABOLINA ◽

Jelizaveta Fomina ◽

Eva Lapkovska ◽

Liene Silina

Keyword(s):

Human Body ◽

Sedentary Lifestyle ◽

Body Position ◽

Physical Activities ◽

The Body ◽

Body Posture ◽

Body Measurements ◽

Postural Changes

Correct body posture is a balanced musculoskeletal body position; however, today many people face severe posture defects, and their body posture may be far from a normal, causing progressive musculoskeletal deformities and pain, as well as affecting the functionality and appearance of the body. Human daily habits, lack of physical activities and overall a sedentary lifestyle cause such phenomena. The research focuses on studies of human body measurements and body characteristics while wearing posture-corrective equipment for the assessment of the effectiveness of different posture correctors (abbreviated as PoC). Four test-persons were selected and scanned using 3D anthropometrical scanner in relaxed stand position wearing five different posture correctors for a prolonged period of time in order to determine the effectiveness and functionality of each PoC. Four distance (linear) human body measurements were gained to quantify postural changes - scapula position depth, upper torso position, shoulder projection height and hip-waist depth. General feedbacks on each subject impression of wearing PoCs were also received. Correction of posture could serve as a preventive or treatment for spine-related problems; though, commercially available correctors could negatively affect wearer’s health due to non-conformity of the design and/or used material. Therefore, PoC selection and wearing procedures should be solved with more personalized and customized approaches.

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Multiple-Person Tracking by Multiple Cameras and Laser Range Scanners in Indoor Environments

Journal of Robotics and Mechatronics ◽

10.20965/jrm.2010.p0221 ◽

2010 ◽

Vol 22 (2) ◽

pp. 221-229 ◽

Cited By ~ 11

Author(s):

Hiroshi Noguchi ◽

◽

Taketoshi Mori ◽

Takashi Matsumoto ◽

Masamichi Shimosaka ◽

...

Keyword(s):

Particle Filter ◽

Human Body ◽

Body Position ◽

Human Head ◽

Specific Information ◽

Indoor Environments ◽

Multiple Cameras ◽

Laser Range ◽

Person Tracking ◽

Weak Points

In this paper, we propose a method for multiple-person tracking using cameras and laser range scanners. Our method estimates 3D positions of human body and head, and labels them with their identities. Individual particle filters track person correctly by integrating information from laser range scanners and target-specific information from cameras, thus compensating for weak points of each. We also develop a particle filter framework that tracks the human head simultaneously using the estimated body position. Results of experiments demonstrate the effectiveness and robustness of the proposal in tracking multiple persons with multiple scanners and cameras.

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Volleyball Action Extraction and Dynamic Recognition Based on Gait Tactile Sensor

Journal of Sensors ◽

10.1155/2021/9204123 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Limin Qi

Keyword(s):

Human Body ◽

Difference Method ◽

Body Position ◽

Capture Rate ◽

Detection Algorithm ◽

Human Motion ◽

Position Estimation ◽

Test Method ◽

Frame Difference ◽

Background Segmentation

At present, the industry research of volleyball technology is relatively in-depth, and the analysis of the muscle strength characteristics and coordination of the jumping ball is less, which is not conducive to the control of technical movements. This study used a wireless portable surface EMG tester (16 lines) to analyze the EMG of the main muscle groups in athletes’ volleyball and conducted a video synchronization test method to find the position of the human body. Therefore, a background-based frame difference method is proposed to detect the position and obtain the precise position of the human body. Experiments show that the background-based three-frame difference method effectively eliminates the “hole” effect of the original three-frame difference method and provides an accurate and complete framework for identifying the human body. Adjust the recognition frame according to the proportion of the human body in the image, and use the predefined parameters of the severe frame to perform forward/volleyball background segmentation. The novelty of this document lies in the completion of the complete human body placement of the above three tasks, precapture/background segmentation, and an improved human body position estimation algorithm to extract the human body pose from the video. First, locate the human body in each frame of the video, and then, perform the process of estimating the position of the graphic model based on the color and texture of the unit. After recognizing the gesture of each image in the video, the recognition result will be displayed. Experiments show that after detecting the position of the human body, the predefined frame setting process of the tomb is carried out in two steps, which improves the automation of the human body image detection algorithm, effectively extracts the human motion video, and increases the motion capture rate by more than 30%, to provide a useful reference for the improvement of college volleyball players’ movement skills and training competitions.

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