Professional advice on fitness tool design
1. Data dimension design:
- Must containBasic indicators: Length of training, calories burned, subjective fatigue (on a scale of 1-10)
- Proposed increasederived indicator:: Weekly attainment rates, comparative trends for similar projects
- Advanced users can addBiological data: Resting heart rate, sleep recovery score (requires external device)
2. Optimization of interaction logic:
- set upSmart Defaults: Pre-filled weights/groups based on historical data
- addVoice input support: quick record during training ('squat 60kg 5 sets')
- deviseAchievement System: Automatically triggers the 'Continuous Clocking Reward' tip
3. Integration of specialized functions:
- Calling Apple Health data to automatically supplement training details
- Affiliated Sports Tutorial Library (need to describe 'video demo required')
- Add 'compensatory movement detection' Q&A module (need to state 'show corrective training when I enter shoulder discomfort')
4. Memory system configuration:Inform the AI during the creation phase: 'Remember I work on my glutes and legs every Wednesday' 'Prioritize displaying shaping suggestions over muscle building options' and these preferences are continuously learned.
This answer comes from the articleMacaron: The AI assistant that creates chat conversations as shortcut toolsThe
English 
简体中文 
日本語 
Deutsch 
Português do Brasil