TrainCal

Problem

College students practising calisthenics at home need a way to check whether they are performing foundational movements correctly without in-person coaching. The research identified correct technique as the main concern, alongside questions about workout duration, progress, and important training considerations.

Approach

TrainCal turns a self-directed workout into a guided flow: users select a basic movement, review instructions, analyse their movement with vision technology, and receive real-time feedback. The app then uses the result to recommend a beginner exercise programme and saves analysis history to help users track progress over time.

The native iOS experience was built with UIKit and Storyboards, bringing together movement analysis, video and audio capabilities, speech support, local data, and privacy-aware handling of workout data.

Core workflow

Users can start a workout analysis, receive a suggested exercise programme, and revisit their analysis history from one clear flow.

Interface refinement

The team refined the instructional and programme screens from the high-fidelity prototype into clearer final layouts that help users focus on the next exercise or action.

Outcome

TrainCal was delivered as a native iOS app concept for guided at-home calisthenics practice. It gives users a way to analyse a movement, review feedback, follow a suggested programme, and retain their analysis history. The supplied materials do not include validated user-impact metrics, so none are claimed here.

Responsibilities

• Designed the Core Data schema for movement-analysis results, exercise programmes, and analysis history.
• Implemented several UIKit and Storyboard-based interfaces across the exercise, analysis, report, programme, and history flows.
• Collaborated with the project manager, designers, and fellow engineers to translate the product flow into a working iOS application.