Computer Program to Generate Dimensional and Inertial Properties of the Human Body

1975 ◽  
Vol 97 (1) ◽  
pp. 49-57 ◽  
Author(s):  
J. A. Bartz ◽  
C. R. Gianotti
Keyword(s):  
Computer Program ◽  
Human Body ◽  
Contact Surface ◽  
Digital Computer ◽  
Body Segment ◽  
Anthropometric Data ◽  
Data Set ◽  
Moments Of Inertia ◽  
Standing Height ◽  
Program Library

A digital computer program has been developed to calculate dimensional and inertial properties of the human body. The program has been designed so that the user may either select a data set from a program library, or compute a data set from a geometric man-model. From primary program inputs of sex, standing height, seated height, and weight, the routines compute body segment link lengths, contact surface dimensions, masses, and moments of inertia from inputted sets of anthropometric data. Overall validity of the formulation and techniques has been established by comparing computed results with measurements on the human body reported by various investigators.

scholarly journals Acceleration Feature Extraction of Human Body Based on Wearable Devices

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 924
Author(s):  
Zhenzhen Huang ◽  
Qiang Niu ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Genetic Algorithm ◽  
Feature Extraction ◽  
Kalman Filter ◽  
Human Body ◽  
Wearable Devices ◽  
Human Motion ◽  
Data Set ◽  
Feature Extraction Method ◽  
Motion Data ◽  
Kalman Filter Algorithm

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.

A Digital Computer Program for Processing Turbine-Generator Acceptance Test Data

1962 ◽  
Vol 84 (3) ◽  
pp. 295-304 ◽  
Author(s):  
G. A. Maneatis ◽  
W. H. Barr
Keyword(s):  
Thermodynamic Properties ◽  
Computer Program ◽  
Steam Turbine ◽  
Test Data ◽  
Digital Computer ◽  
Heat Rate ◽  
Acceptance Test ◽  
Turbine Generator

This paper describes a digital computer program which processes rapidly all of the data taken during a steam turbine-generator acceptance test. Specifically, it determines all thermodynamic properties of steam and water, computes corrected test heat rate, and finally develops a contract heat rate for purposes of comparison with manufacturer’s guarantees. The application of this program on two 330-megawatt units is discussed. The thinking leading to certain key decisions involving the ultimate approach taken is presented for the benefit of those contemplating a similar effort.

scholarly journals Computation of electrostatic fields in anisotropic human tissues using the Finite Integration Technique (FIT)

2005 ◽  
Vol 2 ◽  
pp. 309-313 ◽  
Author(s):  
V. C. Motresc ◽  
U. van Rienen
Keyword(s):  
Coordinate System ◽  
Electromagnetic Fields ◽  
Human Body ◽  
Local Coordinate System ◽  
Anisotropic Materials ◽  
The Body ◽  
Integration Technique ◽  
Data Set ◽  
Computer Data ◽  
Finite Integration Technique

Abstract. The exposure of human body to electromagnetic fields has in the recent years become a matter of great interest for scientists working in the area of biology and biomedicine. Due to the difficulty of performing measurements, accurate models of the human body, in the form of a computer data set, are used for computations of the fields inside the body by employing numerical methods such as the method used for our calculations, namely the Finite Integration Technique (FIT). A fact that has to be taken into account when computing electromagnetic fields in the human body is that some tissue classes, i.e. cardiac and skeletal muscles, have higher electrical conductivity and permittivity along fibers rather than across them. This property leads to diagonal conductivity and permittivity tensors only when expressing them in a local coordinate system while in a global coordinate system they become full tensors. The Finite Integration Technique (FIT) in its classical form can handle diagonally anisotropic materials quite effectively but it needed an extension for handling fully anisotropic materials. New electric voltages were placed on the grid and a new averaging method of conductivity and permittivity on the grid was found. In this paper, we present results from electrostatic computations performed with the extended version of FIT for fully anisotropic materials.

scholarly journals Development and assessment of CootVR, a virtual reality computer program for model building

2021 ◽  
Vol 77 (1) ◽  
pp. 19-27
Author(s):  
Hamish Todd ◽  
Paul Emsley
Keyword(s):  
Virtual Reality ◽  
Computer Program ◽  
Model Building ◽  
Three Dimensional ◽  
Specific Model ◽  
Three Dimensions ◽  
Biological Macromolecules ◽  
Data Set ◽  
X Ray Crystallography ◽  
Order Of Magnitude

Biological macromolecules have complex three-dimensional shapes that are experimentally examined using X-ray crystallography and electron cryo-microscopy. Interpreting the data that these methods yield involves building 3D atomic models. With almost every data set, some portion of the time put into creating these models must be spent manually modifying the model in order to make it consistent with the data; this is difficult and time-consuming, in part because the data are `blurry' in three dimensions. This paper describes the design and assessment of CootVR (available at http://hamishtodd1.github.io/cvr), a prototype computer program for performing this task in virtual reality, allowing structural biologists to build molecular models into cryo-EM and crystallographic data using their hands. CootVR was timed against Coot for a very specific model-building task, and was found to give an order-of-magnitude speedup for this task. A from-scratch model build using CootVR was also attempted; from this experience it is concluded that currently CootVR does not give a speedup over Coot overall.

Sign in / Sign up

Export Citation Format

Share Document