PhysioMasterAI: Your AI Physiotherapist

This is a submission for the World's Largest Hackathon Writing Challenge: Building with Bolt.

Hello everyone! God bless!
I am Mrs. Shweta Kapoor from Rajkot, Gujarat, India. This has been my solo project. So no teammates.

Reach me here: [e-mail].

My Instagram post of PhysioMasterAI: https://www.instagram.com/reel/DLmY1-osg5v/?utm_source=ig_web_copy_link&igsh=enp5eWo3Z2phaHFz

My Linkedin post of PhysioMaster AI : https://www.linkedin.com/posts/ai-tools-enclave-for-non-techies_devpost-activity-7346102202291093504-RTvG?utm_source=share&utm_medium=member_desktop&rcm=ACoAAC5nEP4BmSGUV40CI0BqDyw0IgVQiDbWaxM

My Project Details: Name: PhysioMaster AI: Your personal AI Physiotherapist: https://physiomasterai.netlify.app/

My post in WLH: https://devpost.com/software/physiomaster-ai

In order to build PhysioMasterAI, I first prompted in Claude and asked it to write a prompt for bolt.new. I asked Claude to not build the app by itself. Then I simply copy-pasted this prompt into bolt.new and then deployed it to netlify.app. All thanks to this day's AI (especially Claude.ai, Bolt.new, and Netlify.app) that I simply followed onscreen instructions, myself being a non-techie, that I could build such an amazing app, which can help millions of people now on in their healing journeys with minimal cost, instead of paying high fees for innumerable physiotherapist sessions.

My project details:
Core App Concept: "PhysioMaster AI"
Primary Features & Functionality

1. Assessment & Diagnosis Module.
2. Personalized Exercise Prescription
3. Advanced Knowledge Base:
4. Technical Specifications for Vibe Agents
5. Data Architecture
6. AI Integration
7. User Experience Design

Expert-Level Content Requirements

1. Clinical Protocols
2. Exercise Database
3. Educational Content

Monetization & Professional Features

1. Subscription Tiers
2. Healthcare Integration
3. Development Roadmap Suggestions

AI-Powered Treatment Architecture:

1. Advanced AI Assessment Engine
2. Multi-Modal Data Analysis
3. Precision Diagnosis AI

Intelligent Treatment Protocols

1. Adaptive Program Design
2. Frequency-Specific Protocols:

3x/week protocol: Focus on compound corrective movements with longer recovery
5x/week protocol: Alternating muscle groups with targeted isolation work
6x/week protocol: Daily movement preparation with intensive corrective days
AI-Driven Progress Optimization

1. Real-Time Adaptation
2. Outcome Prediction

Smart Exercise Execution:

1. Form Analysis AI
2. Personalized Coaching

Data-Driven Success Metrics:

1. Comprehensive Tracking
2. Predictive Analytics

AI Treatment Specializations

1. Muscle Imbalance Categories
2. Exercise Intelligence

Success Optimization Features

1. Adherence AI
2. Recovery Intelligence

Implementation Considerations

1. AI Model Training
2. Quality Assurance

PhysioMaster AI - Frontend Design Recommendations:

1. Overall Design Philosophy
   Medical Professional + Modern Wellness Aesthetic

2. Core Layout Structure
   Dashboard-Centric Design

Main Navigation
Quick Actions
Status Cards
Progress Rings

Recommended Layout Sections

1. Onboarding Flow (Multi-Step): Design: Card-based progression with visual step indicators Interaction: Swipe/tap navigation with progress bar Visual: 3D body model for pain mapping, video demos for movement tests

2. Main Dashboard
   Top Section
   Middle Section
   Bottom Section

3. Assessment Interface
   Visual Body Map
   Smart Forms

1. Exercise Interface Session View

Exercise Card Design

1. Progress Tracking Visual Analytics

Milestone Celebrations

Color Palette Recommendations
Primary Colors:

Medical Blue
Healing Green
Warm White

Accent Colors:

Energy Orange
Calm Purple
Warning Red
Neutral Palette

Text Primary

Text Secondary
Background
Cards

Typography System
Headings
Body Text

Interactive Elements: Buttons:

Primary
Secondary
Floating
Cards
Forms
Mobile-First Responsive Design
Breakpoints
Touch Interactions

Accessibility Features
Visual
Motor

Advanced UI Components
AI Feedback Display
3D/AR Elements
Layout Framework Recommendations
For Development:

React Native: Cross-platform with native performance
Tailwind CSS: Rapid prototyping and consistent design
Framer Motion: Smooth animations and transitions
Three.js: 3D anatomy models and visualizations
Design Tools:

Figma: Collaborative design with component libraries
Principle/Framer: Interactive prototyping
Lottie: Lightweight animations
User Flow Optimization
First-Time Users:

Returning Users:

Dashboard → Today's Session → Exercise Execution → Progress Update
Maximum 2 taps to start exercising
Seamless session continuation

Most Elegant Framework Stack for 2025: Flutter + Dart
Key Advantages for my Physiotherapy App:

Superior Performance: Flutter renders all components on its own canvas, unlike React Native which transforms JavaScript components into native ones.
Flutter vs. React Native in 2025
Cross-Platform Excellence: Single codebase for mobile, web, and desktop
Rich Animations: Perfect for exercise demonstrations and progress visualizations
Consistent UI: Critical for medical/health apps requiring reliability
Better for AI Integration: More efficient handling of computer vision and ML models
Updated Tech Stack Recommendation
Frontend Framework:

Flutter 3.29 (latest 2025 version) with Dart
Reason: Flutter is ideal while building a visually rich, high-performance application or want long-term scalability across mobile, web, and desktop

Supporting Technologies:

TensorFlow Lite/Flutter: AI model integration
WebRTC Flutter: Real-time video analysis
Rive/Lottie: Sophisticated animations
Firebase/Supabase: Backend services
GraphQL: Efficient data fetching

Why This Beats React Native for Your Use Case
Performance Critical Areas:

Real-time AI Analysis: Flutter's compiled nature handles ML models better
Smooth Animations: Essential for exercise demonstrations
Camera/Video Processing: More efficient native performance
3D Visualizations: Better graphics rendering capabilities

Medical App Requirements:

Consistency: Flutter offers a consistent UI across platforms and potentially better performance.
Reliability: Compiled code is quite stable for health applications
Precision: Better control over UI elements for medical interfaces.