Lumme automatically detects when you smoke in real-time, eliminating the need to manually log habits
Lumme combines your individual smoking habits with additional data such as location, time of day, social interactions and other behaviors to accurately predict when you will have a cigarette craving
Lumme intervenes in real-time six minutes before you are predicted to feel a craving, using personalized messages that effectively prevent you from smoking
Simply download the Lumme Quit Smoking app, strap a smartwatch to your primary cigarette smoking hand and let Lumme be your guide on our 8-week quit program with extended support program to stay quit.
Lumme put its solution to the test on the leading cause of preventable deaths in the U.S. – smoking.
of any smoking cessation product*
Lumme achieved a 49% quit rate in a clinically-validated trial, overseen by the National Cancer Institute at the Yale School of Medicine — the highest quit rate of any smoking-cessation product, including nicotine patches, drugs and other apps.
Lumme effectiveness vs. control odds ratio: 2.24x
*Results based on subjects who regularly used the apps and/or smartwatch. Lumme’s estimates were 59.65% vs 26.80%. N = 87
*Lumme’s results were validated in a randomized clinical trial with 140 subjects conducted at the Yale School of Medicine and overseen by the National Cancer Institute. Lumme’s users had a quit rate of 49.2% vs 30% for the well-known smoke-free TXT program at the end of 8 weeks. Users of Lumme were 2.24 times more likely to quit smoking in comparison to the SmokeFreeTXT program users. Non-quitters reduced their smoking by 72.3% at the end of the 8-week Lumme’s smoking cessation program. Those who followed Lumme’s program regularly for 8 weeks improved their odds to quit smoking by 4.17 times.
False positive gesture rate: 0.005
False episodes detection rate: 1.4 cigarettes/day
5 high risk situations
6 minutes in advance
User wears the smartwatch and we gather data passively – the user doesn’t have to do anything.
Data gathered includes:
1. When the user smokes
2. WheRE the user smokes
3. Who is nearby* when the user smokes
* Based on seeing the same Bluetooth static address—we do not collect identities
1. Based on the data gathered in Phase 1, our machine-learning algorithm predicts when the user will crave a cigarette.
2. We can reliably predict cravings six minutes in advance.
3. We target the user with cognitive behavioral therapy based messages at just the right time to prevent them from smoking.
4. We continuously monitor the user’s smoking behavior and refine our interventions for each individual user.
5. We show the user how well they are doing and how much money they are saving on cigarettes.
6. We provide aggregated, de-identified data to the employer on how well their employees are doing overall with reducing and quitting smoking.
Still have questions?
Visit our FAQ page and find out more about the Lumme Health Quit Smoking App