| 000 -LEADER |
|---|
| fixed length control field |
02441nam a22002417a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
ft8866 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20251210151525.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
251210b ||||| |||| 00| 0 eng d |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
T58 D45 2025 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
. |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
AI-powered intelligent mindfulness-based cognitive therapy companion for emotion recognition and context-aware therapy |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2025 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Other physical details |
Capstone Project: (Bachelor of Science in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2025 |
| 336 ## - CONTENT TYPE |
|---|
| Source |
text |
| Content type term |
text |
| Content type code |
text |
| 337 ## - MEDIA TYPE |
|---|
| Source |
unmediated |
| Media type term |
unmediated |
| Media type code |
unmediated |
| 338 ## - CARRIER TYPE |
|---|
| Source |
volume |
| Carrier type term |
volume |
| Carrier type code |
volume |
| 505 ## - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
ABSTRACT: Mindfulness-Based Cognitive Therapy (MBCT) is effective in managing depression and other mental health challenges but faces barriers such as accessibility and engagement. A key challenge is the lack of integration of advanced technologies in these practices. To address this, research aims to develop an adaptive mobile application that incorporates three key technologies: (1) speech and facial recognition to provide users with an accessible MBCT companion, (2) a context aware algorithm to tailor therapeutic practices based on the user’s location and time, and (3) LSTM-based emotional forecasting to enhance emotion management. A mobile application was made called “Felii” using Android Studio, Java Kotlin for the app back-end development as well as Java, Figma and Photoshop 2020 for the front-end development and phototyping. The speech and facial emotion model demonstrates high accuracy in detecting Joy (30/30) and strong performance in recognizing Sad (26/29), Angry (25/26), Fear (30/39), and Neural (26/26), with minimal misclassifications. Meanwhile, the LSTM-based emotion forecasting model shows promise but has some errors, such as Sad being misclassified as Angry (3 instances) and Fear occasionally misclassified as Neural (4 instances), indicating a need for further refinement. Additionally, the system provides therapy recommendations tailored to the time of the day and user location, enhancing its adaptability. These results confirm the effectiveness of the intelligent companion in supporting MBCT through accurate emotion and personalized therapy. |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
|---|
| Classification |
Filipiniana |
| 655 ## - INDEX TERM--GENRE/FORM |
|---|
| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Thesis/Dissertation |