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An Intelligent System For Exercise Planning And Physical Activity Recognition Using Mobile Technologies

BROWSE_DETAIL_CREATION_DATE: 23-08-2017

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BROWSE_DETAIL_TYPE: Thesis

BROWSE_DETAIL_SUB_TYPE: EngD

BROWSE_DETAIL_PUBLISH_STATE: Unpublished

BROWSE_DETAIL_FORMAT: PDF Document

BROWSE_DETAIL_LANG: English

BROWSE_DETAIL_SUBJECTS: TECHNOLOGY,

BROWSE_DETAIL_CREATORS: Kalem, Güler (Author),

BROWSE_DETAIL_CONTRIBUTERS: Turhan, Çiğdem (Advisor),

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Mobile technology, healthcare, classification, activity recognition, intelligent system, case-based reasoning, Multiclass SVM (Support Vector Machines), KNN (K-Nearest Neighbors), LDA (Linear Discriminant Analysis)


BROWSE_DETAIL_TAB_ABSTRACT

Intelligent guidance in the healthcare domain using mobile technologies is an important development since users can benefit from the individual exercise plans that are specifically designed for their purpose, demographic information and health background. Furthermore, with the system continuously tracking their activities, the users are motivated and guided to complete their daily specified exercises. The developed system determines the specific exercise program suitable to the user with case-based reasoning. With the help of the accelerometer and gyroscope facilities of a mobile phone, users' activities are recognized and classified using KNN (K-Nearest Neighbors) algorithm. Based on their individual exercise routine and the performed activities in the current day, the rest of the exercises are calculated and presented to the user as a message to guide and encourage them. For the evaluation, the system is tested by users, and a questionnaire is conducted. The results show that the system is found to be beneficial and effective by all the participants.


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