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
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Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
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Function: require_once
Objective: This study aimed to determine the accuracy of 3 sensor configurations and corresponding algorithms deriving clinically relevant outcomes of everyday life motor activities in children undergoing rehabilitation. These outcomes were identified in 2 preceding studies assessing the needs of pediatric rehabilitation. The first algorithm estimates the duration of lying, sitting, and standing positions and the number of sit-to-stand transitions with data from a trunk and a thigh sensor. The second algorithm detects active and passive wheeling periods with data from a wrist and a wheelchair sensor. The third algorithm detects free and assisted walking periods and estimates the covered altitude change during stair climbing with data from a single ankle sensor and a sensor placed on walking aids.
Design: The participants performed a semi-structured activity circuit while wearing inertial sensors on both wrists, the sternum, and the thigh and shank of the less-affected side. The circuit included watching a movie, playing, cycling, drinking, and moving around between facilities. Video recordings, which 2 independent researchers labeled, served as reference criteria to determine the algorithms' performance.
Setting: In-patient rehabilitation center.
Participants: Thirty-one children and adolescents with mobility impairments who were able to walk or use a manual wheelchair for household distances (N=31).
Interventions: Not applicable.
Main Outcome Measure(s): The algorithms' activity classification accuracies.
Results: The activity classification accuracy was 97% for the posture detection algorithm, 96% for the wheeling detection algorithm, and 93% for the walking detection algorithm.
Conclusion(s): The 3 sensor configurations and corresponding algorithms presented in this study revealed accurate measurements of everyday life motor activities in children with mobility impairments. To follow-up on this promising results, the sensor systems needs to be tested in long-term measurements outside the clinic before using the system to determine the children's motor performance in their habitual environment for clinical and scientific purposes.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.apmr.2023.05.015 | DOI Listing |
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