| 000 -LEADER |
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| fixed length control field |
02271nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
FT8766 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251105131416.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
251105b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
T58.64 M55 2024 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Mijares, Kenneth L.; Sabar, John Ian B.; Tabañag, James Serafin L. |
| 245 ## - TITLE STATEMENT |
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| Title |
Uplift-Mobility analysis for post-stroke recovery with exercise tracking and virtual-assisted therapy |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2024 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Other physical details |
Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
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| Source |
text |
| Content type term |
text |
| Content type code |
text |
| 337 ## - MEDIA TYPE |
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| Source |
unmediated |
| Media type term |
unmediated |
| Media type code |
unmediated |
| 338 ## - CARRIER TYPE |
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| Source |
volume |
| Carrier type term |
volume |
| Carrier type code |
volume |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
ABSTRACT: Stroke remains a leading cause of long-term disability worldwide, significantly impairing individuals mobility and quality of life. Traditional post-stroke rehabilitation methods, while effective, often face challenges related to consistency, patient adherence, and accessibility. This study investigates the impact of modern technological interventions, such as exercise tracking and virtual-assisted therapy, on enhancing post-stroke mobility recovery. The primary objective was to develop the Uplift Mobility mobile application, which offers real-time data collection, personalized exercise programs, and immediate feedback. Utilizing a sprint (scrum) methodology, key features of the application include facial recognition for secure user identification, mobility analysis using MediaPipe for optimizing exercise routines, and an emergency alert system employing audio notifications. The study successfully achieved its objectives, with the facial recognition system implemented using Dlib achieving 95.65% accuracy, and the pose estimation module using MediaPipe reaching 88.25% accuracy. Despite challenges such as limited tool access and connectivity issues, the Uplift Mobility application demonstrated significant potential in supporting post-stroke rehabilitation by enhancing exercise adherence and improving patient outcomes. Future iterations, informed by user feedback, aim to further optimize the application’s functionality and user experience |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Source of classification or shelving scheme |
|
| Item type |
Thesis/Dissertation |