Home » MedTech Features » Innovation Development Grant Awardees: Meet Paolo Bonato, Ph.D.

Innovation Development Grant Awardees: Meet Paolo Bonato, Ph.D.

KROMM_MedTechBoston2Award-winning innovation is around every corner in Boston. In March, Partners Healthcare announced the 20 recipients of the Innovation Development Grand Competition. Paolo Bonato is one of those winners. This innovator holds many titles, including director of the Motion Analysis Laboratory at Spaulding Rehabilitation Hospital in Boston, assistant professor in the Department of Physical Medicine and Rehabilitation at Harvard Medical School, and adjunct professor of biomedical engineering at the MGH Institute of Health Professions.

His lab, called the Motion Analysis Lab, is one of the 20 recipients of the 2013 Partners Healthcare Innovation Development Grant competition. The winning project is called KROMM, or “Knee Range of Motion Monitoring Device.” With award in hand, Bonato has three main goals for the future: 1) developing the next version of the KROMM system, 2) initiating a pilot clinical study focused on home-based monitoring knee function in patients with knee osteoarthritis, and 3) exploring commercialization opportunities.

Recently, Dr. Bonato and Mr. Yalgin Ozsecen, a research engineer at the Motion Analysis Laboratory in charge of the execution of the KROMM project, sat down with MedTech Boston to share more about the latest ideas that promote human health.


Briefly describe your project.

This project is about having a system to monitor knee range motion in the home setting. We want to have a knee brace that can detect and sense patients’ knee activities when they are outside of the hospital environment. This can provide a more quantitative analysis and allow clinicians to have better understanding of patients’ conditions and provide a personalized therapy suggestion. We envision this device to benefit patients with osteoarthritis [and] ACL-related surgeries, just to name a few.

There are three parts to the development of this device and a testing stage. Firstly, we would like to improve the usability of the sensor with an ergonomic design to better match wearers’ leg contour and blend in with their lifestyle. Secondly, we want to improve the activity detection capability. Together with the engineers in our team, we created an algorithm and incorporated it into the sensors that are attached onto the knee brace. These sensors help us understand and record types of activities of daily living (ADLs) such as walking, standing, or climbing stairs. Lastly, the sensor that is on the brace can sync with an app on a smart phone and detect patients’ knee activities. We want to improve the user interaction with a user-friendly interface and incorporate within the app to help patients to be aware of their exercise levels. Parallel to the device development, we are also setting up a human subject study in which we will be evaluating the next generation of the sensor in the home setting with patients who suffer from knee osteoarthritis.


How does this device improve the patient’s health?

Because the data is recorded, clinicians will get information that they currently do not have, such as range of motion during functional activities. This improves the objective measures that clinicians have to better analyze patients’ conditions. From the patients’ perspective, this device takes care of the questionnaires that need to be filled out and can inform what activities they should be doing and should refrain from doing during their home therapy. This brings new information and guidance to patients during their therapy.


Are there any existing devices that detect knee range motion? How does this device improve clinical impact over existing technology?

There are devices in the market to measure knee range of motion in the clinic. However, there is no existing knee brace capable of monitoring patients’ activities in long-term setting. We haven’t found anything that can alert clinicians or patients in this regard, so we decided to build it. KROMM would enable condition and joint specific data in a long-term setting, potentially for the benefit of patients, clinicians and researchers.


What are some of the potential challenges as this project is being developed?

The biggest challenge is usability. We currently don’t have that data yet. Patients may be sensitive to the pressure exerted from the device. We are planning on making the sensor low profile, aesthetic and user friendly, but this will all be part of the design integration process as we get more data from our clinical study.


What inspired you to develop your proposed project?

We wanted to monitor knee activity in a long-term setting, but couldn’t find any product that measured knee function when the patient is outside of the hospital seamlessly. We think it is important to have this measurement because we can personalize therapy with actual data and hopefully improve outcomes. We think that, by letting sensor collect the movement related data, we could eliminate recollection bias from subjects during visits.

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