Respiratory illnesses continue to be on the rise1-4, in particular, COPD alone impacts nearly 210 million globally 6. Metered Dose Inhaler (MDI) is the most common mechanism to deliver medicine, and is used by the patients for both maintenance and rescue medications. It is well established that regular use of the medications minimizes long-term damage to the lungs, and results in improved health outcomes for the patients 7. Unfortunately, nearly 70-90% of the patients do not display correct technique11-17 and nearly 50% do not take their medications regularly 8-10,13. The biggest challenge in correct use lies in the difficulty of using the inhaler. Correct inhaler is akin to shooting at a small target at the ight time i.e. patients have to point the inhaler towards the back of their throat and activate the inhaler at the correct time during their inhalation - a maneuver which turns out to be difficult fo most patients to master. To compound the problem, regular use of inhaler continues to be a challenge for chronic patients, largely due to forgetfulness in use of maintenance inhalers. Thus, despite the long-term availability of inhalers in the market, correct and regular inhaler use continues to be a major challenge for most COPD patients. In this one-year Phase I STTR project, we will design, develop and prototype a smart attachment, R3, for off-the-shelf MDIs. R3 is a recording, recommending and reminding attachment, with the purpose to promote both correct and regular use of the inhaler for COPD patients. At the heart of R3 is a new real-time recording method using multiple sensors to measure inhaler usage and contextual parameters, like location, time, orientation and patient's tidal volume in real-time. Combined with advanced signal processing algorithms, R3 becomes a coaching inhaler providing patients with real-time recommendations on all steps of inhaler maneuver, starting from proper shaking of the inhaler, correct timing in activating the inhaler and then continuing to inhale after activation. The coaching is both audio-based using the on-board speaker, and visual using the multi-colored LEDs. Finally, using the on-board location and time sensors on R3, and the patient's smartphone, the new smart attachment provides contextual reminders to the users to remember to carry the inhaler when going out, taking medication at the right time and acquiring a needed refill. The team consists of Cognita Labs (a Rice spinoff) and Rice researchers who have successfully collaborated for more than 3 years on past projects. Cognita Labs will develop the hardware prototypes and key algorithms, and Rice researchers will provide technical expertise to benchmark the prototypes. The team has also been working closely with COPD experts (Dr. Guntupalli) at Baylor College of Medicine for last 2 years, who will provide design guidance in Phase I, and partner for clinical trials in Phase II. The highly collaborative project has the potential to have a transformative effect on correct and regular use of inhaler use by COPD patients.
NIH ExPorter
NIH ExPorter