tanyagupta2004 / Stress-Level-Predictor Public

Notifications You must be signed in to change notification settings
Fork 0
Star 0

The project aims to predict stress levels in order to prioritize cardiovascular health by enabling early intervention and preventing potential health complications.

0 stars 0 forks Branches Tags Activity

Notifications

Name		Name	Last commit message	Last commit date
Latest commit History 21 Commits
Hardware		Hardware
README.md		README.md
Report.pdf		Report.pdf
SaYoPillow.csv		SaYoPillow.csv
source_code.ipynb		source_code.ipynb
stressapp.py		stressapp.py
trained_model.sav		trained_model.sav

Repository files navigation

Stress-Level-Predictor

Employed PuTTY for logging sensor values and ThingSpeak for analysis.
Data imputation for body temperature, blood oxygen, & sleeping hours.
Utilized machine learning algorithms for stress level prediction (0-3).

Tech Stack: PuTTY, ThingSpeak, Streamlit, Random Forest, LR, DT.

Hardware: Arduino Uno, MAX3010 Pulse & SPo2 sensor, Vibration sensor.

Web Interface

     When Person is not Stressed

   When Person is Stressed

About

The project aims to predict stress levels in order to prioritize cardiovascular health by enabling early intervention and preventing potential health complications.

machine-learning random-forest putty logistic-regression arduino-uno thingspeak decision-tree pyhton3 vibration-sensor streamlit streamlit-webapp max3010x

Report repository

Releases

No releases published

Packages

No packages published

Languages

Jupyter Notebook 98.5%
Other 1.5%