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: 3122
Function: getPubMedXML
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
Background: Physical health monitoring may take several forms, from individual quality changes to complex health checks carried out by health staff. Present health issues are detected with monitoring, and potential health problems are expected. Wearable sensors provide users with ease in everyday tracking, although many issues must be addressed in such sensor systems. The devices take a long time to obtain the requisite detection and diagnostic expertise and produce false alarms.
Objective: In this paper, the Internet of Things-assisted Health Condition Monitoring system (IoT-HCMS) has been proposed to track and analyze the patient physical health condition.
Method: The proposed IoT-HCMS utilizes the intelligent monitoring model to follow the patient physical health day by day activities and instantaneously generate the health records. The system will indeed support patients in tracking psychological signs to minimize risks to their well-being.
Results: The experimental results show that the IoT-HCMS improves accuracy in patient health monitoring and has less response time.
Download full-text PDF |
Source |
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http://dx.doi.org/10.3233/THC-213011 | DOI Listing |
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