Smokers using a smoking cessation monitoring solution called SmokeBeat were able to reduce their number of cigarettes smoked, according to a pilot study in Nicotine and Tobacco Research.
The study outlines how SmokeBeat, a novel app powered by a data analytics software platform, processes information from the sensors embedded in wearables. This novel software platform relies on an original algorithm to identify in real-time hand-to-mouth gestures that characterize smoking a cigarette. Researchers examined whether monitoring and notifying smokers about smoking episodes immediately via the SmokeBeat app would lead to a reduction in smoking.
“We were impressed with the results,” said Prof. Dar. “The SmokeBeat algorithm detected correctly more than 80% of the smoking episodes and produced very few false alarms. According to both self-report and detection of smoking episodes by the SmokeBeat system, smokers in the experimental condition showed a significant decline in their smoking rate while there was no change in the smoking rate of the control group. These results suggest that the SmokeBeat real-time automatic monitoring and notification feature may facilitate smoking reduction in smokers motivated to make life-improving changes.”
The pilot study included 40 smokers – nine women and 31 men – who expressed a goal to reduce or quit smoking. Each was assigned randomly the SmokeBeat app for 30 days or to a wait-list control group. All participants completed questionnaires at baseline and at the end of the study, including their level of smoking during the test period. Smokers in the experimental group were notified whenever the SmokeBeat system detected a smoking episode and were asked to confirm or deny it.
SmokeBeat can leverage real-time CBT (Cognitive Behavior Therapy) principle-based intervention, providing smokers with personally tailored support information – reminders, probes, coping tactics – at just the right time. It also performs ongoing e?ectiveness assessment for treatments tailored specifically to individual smokers.
“The academic validation of our products, and collaboration with Prof. Dar, is enormously important to Somatix as it coincides with the launch of our smoking tracking and monitoring solution. It is our belief that SmokeBeat will improve user compliance and adherence with prescribed cessation therapies for optimal treatment efficacy,” said Eran Ofir, CEO of Somatix. “Peer-review publication of these findings is a significant affirmation as the Oxford University Press Journal, Nicotine and Tobacco Research, elected to publish Prof. Dar’s research results.”
SmokeBeat leverages Big Data analysis for correlating smoking episodes with other analytics, to assess smoking patterns. The platform offers a set of key features such as automated smoking detection so that smokers do not have to record manually their smoking habits. It provides physicians, clinics and other health-service providers, as well as payors (health insurance companies) and the smokers themselves complete, ongoing information regarding treatment success in relation to predefined goals.
