Introducing LifePal, your machine learning powered health companion.

We believe that maintaining good health is vital for overall well-being. It is essential to prioritize basic needs such as sleep, nutrition, and hydration in order to take care of one’s health.

Leveraging Apple’s HealthKit, LifePal utilizes the capabilities of machine learning to generate personalized recommendations for food, water intake, and bedtime. This integration enables LifePal to provide tailored suggestions based on individual health data.

Live Demo

The static health data presented is a representation of a statistical average early-20s male. The activity data is dynamically sourced from Apple HealthKit in real-time.


Food Recommendation

LifePal incorporates a selection of food items from Brandywine, one of the largest UCI dining halls, into its own database. By analyzing the user’s health data and goals, LifePal suggests suitable food options from the menu. Additionally, it presents the complete menu to the user if they wish to explore other choices.


Water Intake Recommendation

LifePal calculates the user’s optimal water intake based on their health data. Users can log their water consumption and monitor their progress towards their hydration goals.


Sleep Recommendation:

LifePal enables users to input their desired wake-up time and utilizes their health data to recommend an appropriate bedtime. This feature assists users in optimizing their sleep schedule for improved well-being.


HealthKit Integration

LifePal utilizes Apple’s HealthKit to access the user’s health data. This integration enables LifePal to provide personalized recommendations based on the user’s health data as they are produced in real time.

Of course, the user’s privacy is of utmost importance to us. LifePal only accesses the user’s health data with their explicit permission. Furthermore, the user can revoke LifePal’s access to their health data at any time.


Full Product Launch Event


  • Programming Language: Swift, Python
  • Libraries: HealthKit, SwiftUI, Django
  • Technologies: AWS, PostgreSQL

GitHub Repositories


  • Shengyuan Lu: iOS
  • Arkin Verma: iOS
  • Chi Zhang: Machine Learning
  • Anthony Hou: Server & API