IJRTI
International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)

Call For Paper

For Authors

Forms / Download

Published Issue Details

Editorial Board

Other IMP Links

Facts & Figure

Impact Factor : 8.14

Issue per Year : 12

Volume Published : 11

Issue Published : 120

Article Submitted : 24204

Article Published : 9239

Total Authors : 24597

Total Reviewer : 847

Total Countries : 165

Indexing Partner

Licence

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Published Paper Details
Paper Title: Human-Centric Companion System for Enhancing Personal Wellbeing Using Machine Learning
Authors Name: Mrs. A. Rajeswari , K. Yashwanth , M. Kushal , M. Uday Kiran
Download E-Certificate: Download
Author Reg. ID:
IJRTI_211485
Published Paper Id: IJRTI2604273
Published In: Volume 11 Issue 4, April-2026
DOI:
Abstract: This paper presents the Human-Centric Companion System (HCCS), an intelligent framework designed to enhance personal wellbeing through real time emotion recognition and stress analysis using Machine Learning. The system combines facial emotion detection via a CNN Bi-LSTM model and stress estimation through physiological sensor data (PPG and accelerometer signals). It integrates multimodal data using a Fast API-based backend and a React + Vite frontend interface. The model classifies emotional states such as happiness, sadness, fear, and anger, while computing a stress score derived from wearable signals. The solution provides a personalized dash- board for monitoring mental wellness, generating insights, and promoting emotional awareness. The proposed system achieves 85% accuracy in emotion recognition and 82% correlation between facial and physiological stress metrics, demonstrating its effectiveness in human centered wellbeing applications.
Keywords: Emotion Recognition, Stress Detection, CNN- Bi LSTM, Machine Learning, Fast API, React, Physiological Signals, Human Wellbeing
Cite Article: "Human-Centric Companion System for Enhancing Personal Wellbeing Using Machine Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b990-b993, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604273.pdf
Downloads: 000205506
ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2604273
Registration ID:211485
Published In: Volume 11 Issue 4, April-2026
DOI (Digital Object Identifier):
Page No: b990-b993
Country: -, -, India
Research Area: Engineering
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2604273
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2604273
Share Article:

Click Here to Download This Article

Article Preview
Click Here to Download This Article

Major Indexing from www.ijrti.org
Google Scholar ResearcherID Thomson Reuters Mendeley : reference manager Academia.edu
arXiv.org : cornell university library Research Gate CiteSeerX DOAJ : Directory of Open Access Journals
DRJI Index Copernicus International Scribd DocStoc

ISSN Details

ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

DOI (A digital object identifier)


Providing A digital object identifier by DOI.ONE
How to Get DOI?

Conference

Open Access License Policy

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

Creative Commons License This material is Open Knowledge This material is Open Data This material is Open Content

Important Details

Join RMS/Earn 300

IJRTI

WhatsApp
Click Here

Indexing Partner