Track your meals and bowel movements to identify potential food sensitivities. The app learns your eating habits and reports correlations without requiring nutritional data or a large food database. It's a simple tool to help you understand your digestive health.
1.1.1
October 16, 2024
Fixes for iOS 18 users: log entries now persist correctly and immediately, deleting log entries no longer crashes the app, Brown Note Shortcuts will no longer fail to run, and the keyboard will now correctly focus when starting a new log entry. Minor improvements: the app will no longer ask for clarification of food/drink items that have already been clarified, and when logging or clarifying multiple food/drink items the list of entered items & autocomplete options will both now sort alphabetically correctly, regardless of language.
MoreBrown Note is a mobile application designed to help users correlate their meals with their bowel movement quality. It learns your eating habits and reports potential correlations without needing extensive nutritional data.
No, Brown Note explicitly states that it does not provide medical diagnoses. Users are advised to consult with a doctor before making any dietary changes that could affect their health.
Brown Note is available on the Apple Watch, iPhone, and iPad, offering flexibility for users to track their health data across their devices.
The latest version of Brown Note is 1.1.1, which was last updated on October 16, 2024. This indicates active development and maintenance of the application.
Brown Note has an age rating of 4+, making it suitable for a wide range of users interested in tracking their digestive health.
Brown Note learns by having you type in what you ate and logging your bowel movements. It then asks for more information asynchronously to identify correlations.
Yes, Brown Note is available for free. There are no in-app purchases or advertisements mentioned, making it a completely free tool for users.
Brown Note has a high rating of 5.0 stars from 2 ratings, suggesting positive initial user sentiment. Users appreciate its simple approach to identifying food correlations.
