[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123874-en":3,"doc-seo-123874-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},123874,549758252649,"Ivy","https://ap-avatar.wpscdn.com/avatar/8000253669c5317157?_k=1778319167496531819",8,"Research & Report","Effectiveness validation of Physical Exercise Routines for Hypertensive Patients using Wearable Devices and Machine Learning","High blood pressure is a chronic condition characterized by increased arterial pressure. Physical exercise has been shown to produce medication-like benefits for hypertensive patients, yet therapy must be personalized because physiological responses differ. This work compiles information from bibliographic sources and expert surveys on hypertension factors, machine learning methods in medicine, and clinical patient datasets. The resulting data trains predictive models and evaluates how well prescribed exercise routines work using metrics such as accuracy, precision, and recall.","Effectiveness validation of Physical Exercise Routines for Hypertensive Patients using Wearable Devices and Machine Learning  \nMariuxi Toapanta Bernabé 1,2 , ∗ , César Alcívar Aray1,3 , David Ramos Tomalá 1 , and Nixon Quinde Merchán 1  \n1Universidad de Guayaquil, 090514 Guayaquil, Ecuador  \n2Universidad de Jaén, 23071 Jaén, Spain  \n3Universitat Oberta de Catalunya, 08018 Barcelona, Spain  \nAbstract. High blood pressure is a chronic disorder that consists of increased blood pressure. Research has demonstrated that physical exercise can have effects like the use of some medications in hypertensive patients, leading healthcare professionals to prescribe physical activities for these types of patients commonly. However, hypertensive patients have different physiological realities, so the treatment and prescribed exercises must be personalized and adapted to each one of them. Relevant information has been gathered from bibliographic sources and surveys of medical experts to identify the factors influencing hypertension, commonly used machine learning models in medicine, and clinical datasets of patients with hypertension. This data is used to train predictive models, enabling specialists to assess the effectiveness of prescribed exercises for hypertensive patients. A comparative analysis of machine learning models such as Naive Bayes, Decision Tree, and Logistic Regression was conducted to determine the best model for evaluating the effectiveness of prescribed exercises.  \nMetrics such as accuracy, precision, and recall were used for evaluation. The Decision Tree algorithm achieved the best performance with an accuracy rate of 79% . This evaluated model will be integrated into the platform developed in  \nthe subsequent phases of the FCI Research Project.  \n1 Introduction  \nHigh blood pressure is defined as increased pressure in the arteries. The WHO’s global objective is to reduce the prevalence of hypertension by 25% by 2025 compared to 2010 . In Ecuador, the Ministry of Health MSP carries out actions and efforts to prevent, diagnose, and control high blood pressure promptly. According to the ENSANUT National Health and Nutrition Survey carried out between 2011 and 2013, it was found that more than 30% of the Ecuadorian population over 10 years of age (3,187,665) are prehypertensive and 717,529 people from 10 to 59 years of age have high blood pressure [1] .  \nThe WHO has identified ten risk factors as determinants for the development of chronic diseases, of which five factors are closely related to diet and physical exercise. On the other hand, physical inactivity is considered the fourth risk factor [for mortality. in](for mortality. in) the world  \n∗[Corresponding author: mariuxi.toapantab@ug.edu.ec](Corresponding author: mariuxi.toapantab@ug.edu.ec)  \n© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 ([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)).  \n[2] . Currently, considered that unhealthy eating and lack of physical activity, also known as a sedentary lifestyle, are considered risk factors for the development of chronic noncommunicable diseases NCDs such as Hypertension which, in recent years, has become a prevalent public health problem throughout the world [3] .  \nIn 1989, the WHO and the International Society of Arterial Hypertension recommended for the first time, physical exercise among non-pharmacological measures to reduce blood pressure values, since pharmacological treatment is not enough to successfully treat hypertension. Most studies have since demonstrated its usefulness for the treatment and prevention of this disease.  \nTo improve blood pressure and reduce coronary risk factors, a hypertensive patient must be guided and motivated to perform low-weight physical exercise. Programs that include activities such as walking, dancing, running, swimming, and cycling, carr","cbCaibswlAWmPdWm","https://ap.wps.com/l/cbCaibswlAWmPdWm","pdf",1312320,1,29,"English","en",105,"# Introduction\n## Public health context and risk factors\n## Exercise as a non-pharmacological intervention\n## Need for personalization and monitoring with wearable tech\n# Evaluation approach\n## Machine learning models compared\n## Metrics and performance assessment","[{\"question\":\"Why is physical exercise considered for hypertensive patients?\",\"answer\":\"Research indicates physical exercise can reduce blood pressure and help prevent and treat hypertension, acting similarly to some medications. Pharmacological treatment alone is often not sufficient, so exercise is recommended as a key non-pharmacological measure.\"},{\"question\":\"How does the study handle the need for personalized exercise?\",\"answer\":\"Hypertensive patients present different physiological realities, so prescribed exercises must be adapted to each person. The document highlights that routines may fail to match adult physiology if precautions are not taken, motivating personalization and monitoring.\"},{\"question\":\"Which machine learning method performed best and how was it evaluated?\",\"answer\":\"The Decision Tree algorithm achieved the best performance with an accuracy rate of 79%. Evaluation used metrics including accuracy, precision, and recall to compare models such as Naive Bayes, Decision Tree, and Logistic Regression.\"}]","Effectiveness validation of Physical Exercise Routines for Hypertensive Patients using Wearable Devices and Machine Learning | PDF",1785819012,73,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"effectiveness-validation-of-physical-exercise-routines-for-hypertensive-patients-using-wearable-devices-and-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/effectiveness-validation-of-physical-exercise-routines-for-hypertensive-patients-using-wearable-devices-and-machine-learning/123874/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why is physical exercise considered for hypertensive patients?","Question",{"text":75,"@type":76},"Research indicates physical exercise can reduce blood pressure and help prevent and treat hypertension, acting similarly to some medications. Pharmacological treatment alone is often not sufficient, so exercise is recommended as a key non-pharmacological measure.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the study handle the need for personalized exercise?",{"text":80,"@type":76},"Hypertensive patients present different physiological realities, so prescribed exercises must be adapted to each person. The document highlights that routines may fail to match adult physiology if precautions are not taken, motivating personalization and monitoring.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning method performed best and how was it evaluated?",{"text":84,"@type":76},"The Decision Tree algorithm achieved the best performance with an accuracy rate of 79%. Evaluation used metrics including accuracy, precision, and recall to compare models such as Naive Bayes, Decision Tree, and Logistic Regression.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]