NSF awards more than $1 million to interdisciplinary research team studying chronic low back pain

La Jolla, CA – A multidisciplinary team led by researchers from UC San Diego has received $1.2 million from the National Science Foundation (NSF) to develop a novel system to study and inform about the management of chronic low back pain develop. The work will involve a range of tools, including wearable sensors and machine learning, to improve physical therapy assessment and treatment.

“This research will support remote monitoring of patient posture and movement throughout the day, with the ultimate goal of enabling personalized physical therapy treatments and improving health outcomes,” said Emilia Farcas, the grant’s principal investigator and research associate at the Qualcomm Institute (QI ) at UC San Diego.

New technology for an old problem
Back pain affects up to 80% of people at some point in their lives, and the cost of treatment and lost wages due to disability exceeds $100 billion annually in the United States.

The NSF award funds four years of work to develop the Multi-Sensor Adaptive Data Analytics for Physical Therapy (MS-ADAPT) system, which uses wearable technology and smartphone-based applications to remotely measure lower back posture and movement monitor and provide physical care to support therapy and patient-reported pain. Study participants wear a Fitbit and wear a network of smart sensors made by integrating nanotechnology with over-the-counter kinesiology tapes. These “motion tape” sensors can measure skin stress, which is the stretching or change in skin texture during physical activity, as well as movement of the spine and the level of muscle stress or activity.

Researchers are also developing novel machine learning analytics to predict the impact of physical therapy on back pain for faster recovery, reduced healthcare costs and more personalized medicine.

The project exists at the intersection of several areas of study, including software engineering, wearable sensors, machine learning, precision medicine, spinal biomechanics and physical therapy.

“The highly collaborative environment and close partnership between all researchers has enabled us to pursue this highly multidisciplinary and important topic,” said Ken Loh, co-principal investigator of MS-ADAPT and professor of structural engineering at the UC San Diego Jacobs School of Mechanical engineering.

Other co-principal researchers are Sara Gombatto, professor in the Doctor of Physical Therapy Program at San Diego State University, and Arun Kumar and Qi (Rose) Yu, associate professor and assistant professor, respectively, in the Department of Computer Science and Engineering at the Jacobs School and the Halicioğlu Data Science Institute. Senior collaborators working on the project include Kevin Patrick, professor at the School of Public Health and researcher at QI, and Job Godino, associate research scientist at the School of Public Health and director of the Exercise and Physical Activity Resource Center (EPARC ) on the QI .

An adaptive platform
As part of the team’s long-term goals, researchers may one day use MS-ADAPT as a universal platform to study other health conditions such as limb loss, spinal cord injury and stroke. In the context of studying and treating chronic low back pain, the MS-ADAPT team hopes the new technology will be able to predict a person’s progress during treatment and assess the risk of re-injury.

In keeping with the multidisciplinary nature of the project, Farcas and colleagues plan to use this collaboration to train a new generation of researchers working across academic boundaries.

Cross-border research is a hallmark of working at QI. For more information on the effort led by QI researchers, visit https://qi.ucsd.edu/.