Move Manual

Move Manual is a front-end fitness application designed to help users discover, save, and organize personalized workout exercises. The app uses the ExerciseDB API to fetch real exercise data and provides a mobile-inspired interface for browsing workouts by body part, target muscle, equipment, and workout type.

This project was built to consolidate core front-end concepts including HTML, CSS, JavaScript, Fetch API, Bootstrap, and LocalStorage.

PURPOSE

Discover, save, and organize workouts using personalized filters and real-time exercise data.

PROBLEM

Fitness content is scattered, overwhelming, and rarely tailored to individual needs.

SOLUTION

A filter-driven interface that surfaces relevant exercises instantly.

WHO IT’S FOR

Active adults who want simple, flexible workout planning—at home or in the gym.

CORE VALUE

Faster decisions, personalized workouts, and saved routines that encourage repeat use.

HOW IT WORKS

Dynamic Filtering — Select muscle group, equipment, or difficulty to instantly refine results in real time

API Data — Exercises are pulled from an external API, providing a broad, structured dataset

Favorites — Save exercises for quick access and repeat use

Details — Each exercise includes key info like target area, equipment, and movement type

Design Approach

The design focuses on speed, clarity, and low cognitive load.

Instead of overwhelming users with full workout programs, the interface prioritizes:

  • quick filtering

  • visual scanning

  • minimal steps to action

Key UX Decisions

Filter-first interaction
Users start by narrowing down options instead of browsing endlessly.

Card-based layout
Exercises are displayed in digestible units, making it easy to compare and select.

Minimal navigation
The experience avoids deep page hierarchies to keep users focused and efficient.

Technical Overview

The application is built as a front-end web app that integrates with an external exercise API.

  • Fetches and renders exercise data dynamically

  • Uses state-based filtering to update results in real time

  • Stores saved exercises locally for persistence

Key Focus Areas

  • Handling asynchronous API data

  • Structuring and filtering large datasets

  • Managing state for a responsive UI

(For full technical details, see the project README.)

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