Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Introduction: It has been hypothesized that bone loss arising from long-duration space travel is caused by a reduction in mechanical stimuli to the skeleton. The daily load stimulus (DLS) theory was first proposed to relate daily time histories of mechanical loading from ground reaction forces to bone homeostasis. In this methods paper, an enhanced daily load stimulus (EDLS) is proposed to account for recently developed theories on saturation and recovery of the osteogenic potential of bone with repeated cyclic loading and the potential benefits of standing.
Model Development: To determine periods of continuous activity (sitting, standing, walking, running, and other activity), an activity determination algorithm based on entire days of in-shoe forces was developed. The rainflow peak counting method was used to analyze the in-shoe force data from entire working days in preparation for the calculation of the EDLS. Parameters characterizing saturation and recovery with cyclical loading from running and walking as well as the effects of standing were estimated based on data in the literature.
Discussion: The activity algorithm proved to be accurate and robust when applied to in-shoe force data from entire waking days. The EDLS may be useful in prescribing "dose-based" exercise prescriptions to crewmembers during long-duration spaceflights and missions to the Moon and Mars. Validation of the proposed EDLS model will be possible with data from an ongoing human bed rest study examining changes in bone mineral density with controlled skeletal loading.
Download full-text PDF |
Source |
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http://dx.doi.org/10.3357/asem.2380.2009 | DOI Listing |
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