The tobacco epidemic is one of the biggest public health issues in history. There are more than one billion smokers worldwide and smoking kills more than seven million people annually. Although many smokers recognize how deadly their habit can be and express the desire to stop smoking, quitting remains very difficult. To help smokers kick their habit once and for all, Somatix, an Israeli company, developed SmokeBeat.
SmokeBeat is an innovative smoking cessation tool that uses an individual’s personal smartwatch or smartband to detect smoking by tracking the user’s hand-to-mouth gestures. SmokeBeat is unique in that it does not require smokers to manually record their smoking habits. The platform offers real-time intervention strategies and cognitive behavioral tools to help users quit smoking. It also allows healthcare providers to gain a better understanding of their patients’ smoking habits and adherence to their prescribed smoking cessation plans, enabling them to adjust those plans appropriately.
To learn more about SmokeBeat, we at Medgadget had the chance to interview Eran Ofir, CEO and Co-founder of Somatix.
Kenan Raddawi, MD, Medgadget: Can you give our readers an overview of SmokeBeat and how it works?
Eran Ofir: SmokeBeat offers automatic remote monitoring for improving smoking cessation rates among smokers. The solution taps into smartwatch and smartband accelerometer and gyroscope sensors, among others, to identify and distinguish smoking gestures from other hand-to-mouth gestures. Powered by the Somatix real-time gesture detection platform, SmokeBeat features outstanding automatic raw data collection and applies Machine Learning and predictive Big Data analytics to generate and issue actionable insights to healthcare providers via an enterprise dashboard.
Medgadget: What hardware requirements and sensors need to be in the activity tracker in order for SmokeBeat to function properly? Does Somatix have its own activity tracker or do you have plans to make one?
Ofir: SmokeBeat is device agnostic. It has the ability to tap into wearables’ accelerometer and gyroscope sensors, allowing the use of any wearable that provides access to these sensors’ signals. Currently, SmokeBeat is compatible with Android Wear devices since they have both requested sensors. We plan to support iOS in the future as well.
Moving forward, we will also offer our customers the option of a proprietary low-cost Somatix smartband with fully autonomous operation. This wearable device includes sensors such as accelerometer, gyroscope, and step detector, and it runs our real-time smoking detection algorithm.
Medgadget: What smoking cessation treatment elements does SmokeBeat aim to address?
Ofir: SmokeBeat enhances and supplements any type of smoking cessation treatment such as Nicotine Replacement Therapy (NRT) or Non-NRT therapy/prescription drugs by addressing the major gaps common in treatments:
a) Patients lack support and communication in-between visits with their physicians, leaving them on their own during an emotionally and physically draining period. This creates a huge challenge in treatment adherence and effectiveness.
b) Current treatments do not provide physicians with transparency into patients’ true progress, which they require to provide effective adjustments to treatment.
SmokeBeat also addresses the need for real-time personalized intervention. By creating a profile of each smoker based on their habits, patterns and psychological persona, physicians can intervene in a more productive and tailored manner. SmokeBeat complements medical treatment and enables clinics to implement the two-pronged approach* that defines the combination of behavioral strategies and medicines as the best way to tackle smoking cessation challenges.
Medgadget: What data does SmokeBeat collect and share with users and their healthcare providers?
Ofir: SmokeBeat detects and collects the smokers’ hand gesture data and identifies and distinguishes smoking from other hand-to-mouth gestures. Smoking habits, such as when, where, how long, with whom, and frequency of smoking episodes are accurately tracked.
This massive amount of data (over half a million data records per person per day) is then analyzed in the cloud by Somatix’s advanced Machine Learning algorithms to generate and issue actionable insights and statistics to healthcare providers, via a customizable dashboard, and to the smokers, via their mobile app.
Important to note, SmokeBeat complies with HIPAA. Users need to provide their consent twice – first when SmokeBeat is collecting the data, and then when a third party, such as a clinician or employee benefits program requests access to their data.
Medgadget: There are many smoking cessation solutions on the market today. What is unique about SmokeBeat? Is it the only product that offers automatic monitoring?
Ofir: We have identified two types of competitors: Big Data analytics and solution-specific companies. Most of the latter are smoking cessation consumer apps. However, no other existing smoking cessation solution on the market offers all four of the following key components that SmokeBeat offers. In fact, most don’t even offer a combination of two.
a. Automatic monitoring: automatic gesture monitoring via wearable sensors
b. Big Data structuring & pattern recognition: precise recognition of behavior patterns associated with a range of physiological and emotional states
c. Analytical processing and insight generation: Machine Learning-based analysis and cross-referencing of user profile, location and activity history for generation of continuous and fine-tuned actionable insights
d. Real-time health intervention: Insights translated to CBT (Cognitive Behavior Therapy) recommendations, with a proprietary SERF™ (Social, Emotional, Rational and Financial) motivation engine delivering personalized incentives
Medgadget: What is the sensitivity and specificity of SmokeBeat in detecting smoking? Can a user continue to smoke, but avoid being detected by SmokeBeat?
Ofir: At any given time, a smoker can take off the smartwatch or smart band. However, built-in alerts will notify providers and users when the wearable is not functioning- whether it was taken off, not charged or was being worn incorrectly.
At the same time, SmokeBeat is designed to help smokers who are motivated to quit but need proper support. According to statistics, about 55.4% of American smokers have attempted to quit smoking of which only 7.4% reached permanent cessation. Smokers have the motivation but lack the tools to succeed. SmokeBeat’s mission is to supplement existing treatments by providing an additional support layer that cultivates and increases levels of motivation, effectively filling the current treatment gap.
Medgadget: What is SmokeBeat’s business model? In what countries is the product available and in what languages?
Ofir: We offer three operational business models:
1. Somatix provides the gesture detection platform and the SERF™ behavior modification engine (as a service).
2. Somatix provides the solution through a service provider who interfaces directly with the business customer and renders the related services.
3. Somatix as a one-stop-shop, providing the entire solution including software, hardware, and service
The SmokeBeat app currently supports English, Spanish, French, Chinese and Turkish. To date, SmokeBeat was put to work in the US, Canada, France, Turkey and Israel.
Medgadget: Is SmokeBeat specific for cigarette smoking, or can it recognize other types of smoking – such as smoking Hookahs or pipes?
Ofir: Our technology can learn to detect various hand gestures, including the smoking of Hookah or pipes. However, SmokeBeat’s focus is on cigarette smoking cessation, a massive global market, and one of the deadliest public health issues in the United States today, with nearly half a million Americans dying from smoking related illness every year.
Medgadget: Are there any studies to support the effectiveness of SmokeBeat?
Ofir: Recently, Prof. Reuven Dar of Tel Aviv University, published an article in Oxford University Press’s peer-reviewed journal, Nicotine and Tobacco Research, outlining the benefits of SmokeBeat and suggesting that the platform may significantly facilitate smoking reduction in motivated smokers. Additionally, we expect another two publications from North American academic centers to be published shortly.
Medgadget: Is there anything else that you would like readers to know about SmokeBeat?
Ofir: With the Somatix technology, it is the first time that clinicians can apply immediate intervention based on the context of the person’s activity. Specifically with SmokeBeat, for the first time, smokers will be offered a means to a) detect their habits without any active logging requirements and b) receive invaluable insight and motivation to help them kick the habit. Uniquely addressing long-standing problems associated with smoking cessation – namely, adherence and relapse – our technology has vast potential to impact smoking cessation program success.
Product page: SmokeBeat…