CSUN Senior Design — Spring 2026

trAIn

An AI-powered mobile fitness coach that watches your form, counts your reps, and guides your fitness journey — all from your phone's camera.

Explore Features ↓ How It Works
5+
Exercises
30fps
Real-Time
ON-DEVICE
AI Inference

Beginners Deserve Better

Most new gym-goers face the same barriers: no guidance, no feedback, and no confidence. trAIn was built to change that.

🤷

No Starting Point

Beginners don't know which exercises to do, how to structure workouts, or where to even begin their fitness journey.

👁️

No Form Feedback

Exercising alone means nobody corrects your form. Bad habits build up silently, increasing injury risk and reducing effectiveness.

📉

No Visible Progress

Without tracking or summaries, users can't see whether they're improving — making it easy to lose motivation and quit.

💸

Trainer Cost Barrier

Personal trainers are expensive. trAIn brings guided coaching to anyone with a smartphone — at zero cost.

What trAIn Does

A complete training pipeline: from onboarding to real-time coaching to post-workout analysis.

01

Smart Onboarding Survey

A short, beginner-friendly questionnaire captures age, weight, goals, and motivations to personalize every session.

User Experience
02

Guided Workout Selection

Curated bodyweight routines — push-ups, squats, lunges, crunches — tailored for beginners with clear instructions.

User Experience
03

Real-Time Pose Estimation

On-device computer vision tracks body landmarks at 30fps, enabling live rep counting and movement phase detection.

Computer Vision
04

Live Form Correction

Instant feedback on depth, alignment, posture, and range of motion. Corrective cues appear in real-time as you move.

Computer Vision
05

Post-Workout Reports

Session summaries with rep totals, quality scores, fatigue estimates, and comparison data over time.

Data & Analytics
06

Doctor Dopamine AI Coach

A motivational AI persona delivers personalized recommendations, reflections, and encouragement tied to your goals.

AI Coach

How The Vision System Works

From camera frame to coaching feedback in milliseconds — all running on-device for speed and privacy.

📷
Step 1
Camera Feed
CameraX streams live frames to the inference engine
🧠
Step 2
Pose Model
MediaPipe extracts 33 body landmarks per frame
📐
Step 3
Exercise Logic
Joint angles are analyzed against exercise-specific rules
🔄
Step 4
Rep Detection
Phase changes trigger accurate rep counting
💬
Step 5
Live Feedback
Form corrections appear on-screen in real time
📊
Step 6
Summary
Aggregated metrics generate the post-workout report

Inside the App

Every screen is designed to be readable at arm's length while exercising — minimal friction, maximum clarity.

👋

Welcome & Onboarding

Sets the tone with Doctor Dopamine and guides users into profile setup.

📋

Profile & Survey

Short form collecting age, weight, goals, and motivation preferences.

🏋️

Workout Selection

Browse beginner routines with clear descriptions and expected difficulty.

📸

Active Session

Camera view with live rep count, form feedback, and exercise progress.

📊

Post-Workout Report

Performance summary with quality scores, rep data, and AI coaching.

📈

History & Progress

View past sessions, track trends, and identify areas for improvement.

Built With

A modern Android-native stack combining Jetpack Compose, on-device ML, and cloud services.

🤖
Kotlin
Native Android development language
🎨
Jetpack Compose
Modern declarative UI framework
📷
CameraX
Android camera pipeline for live frame streaming
🧠
MediaPipe / MoveNet
On-device pose estimation & landmark detection
🔥
Firebase
Auth, Firestore, and user data storage
🛠️
Android Studio
Primary IDE & emulator environment
✏️
Figma
UI/UX design and prototyping
🐙
GitHub
Version control & team collaboration

Doctor Dopamine

🧬
AI Training Persona

Your Personal Coach

Doctor Dopamine is the AI personality behind every motivational message, post-workout reflection, and goal-aware recommendation in trAIn. More than a chatbot — it's a training companion that remembers your goals and celebrates your progress.

"Great work today — your squat depth improved 15% since last Tuesday. Your consistency this week is building real strength. Tomorrow, try adding one extra set of lunges. You've got this."

Who Built trAIn

Five CSUN Computer Science seniors combining frontend, computer vision, backend, database, and AI expertise.

JR

Jesus Ramirez

Backend · AI · Pose Logic
  • Dynamic user data display system with Firebase
  • Workout metrics integration into profile dashboard
  • AI Coach feedback module & prompt engineering
  • Pose estimation threshold alignment for rep detection
  • Movement state & edge-case handling for form eval
CE

Christian Estrada

Backend · CV · AI Coach
  • User body overlay visualization
  • User data storage design with SQL
  • AI Coach implementation & motivational response generation
BB

Brian Bonilla

Camera · Pose Estimation
  • Camera API implementation
  • Live feed view for body outline & pose tracking
  • Workout form correction visualization
RM

Reenu Mohan

Frontend · UI/UX Design
  • Home screen design & navigation
  • Workouts screen with organized workout lists
  • Workout Detail screen with instructions & tutorials
  • Profile & About screens
VC

Vishal Chaudhari

Backend · Database
  • User Signup/Login page
  • Firebase database architecture
  • User data storage: emails, passwords & profile data
// source code
github.com/tabee1024/trAIn →

Senior Design Project — Spring 2026

California State University, Northridge

Department of Computer Science