I-Corps: Remote monitoring and assessment tool for spinal care patients

Johns Hopkins University, Baltimore MD

Investigators

Abstract

The broader impact/commercial potential of this I-Corps project is the development of a system to measure musculoskeletal function and monitor patient movements throughout the day. Lower back pain is the leading cause of global disability and up to 80% of Americans will experience lower back pain in their life. The diagnosis and treatment pathways for these patients are complex, expensive (ranging between $10,815 to $87,000 for non-surgical and surgical interventions), and often ambiguous. For the 1.62 million Americans who undergo fusion procedures each year, their treatment is plagued with complication rates as high as 50% and revision rates upwards of 36%. Despite this, rates of these procedures are growing. Between 1998 and 2008, cervical, thoracic, and lumbar fusions rose by 90%, 61%, and 141%. Recent studies have found that up to 17% of spine fusions performed were on patients who should not have been recommended surgeries. The proposed technology may allow for longitudinal tracking and functional quantitative assessment of musculoskeletal disorders and provide personalized care and decreased complications. In addition, the proposed technology may be applied to pain management, the orthopedic extremity market, and sports training. This I-Corps project is based on the development of a remote monitoring and assessment tool to provide dynamic metrics and guide personalized treatment for spine care patients. The proposed technology uses a three-part system that consists of a wearable array, a motion analysis and calibration algorithm that models the spine in 3D, and a clinical report that translates recorded data into clinical metrics. The goal is to analyze dynamic movement, muscular compensation, and pain over a 48-hour window, providing spine surgeons and pain management practitioners with objective measurements of their patients outside of the clinic. The technology builds on recent studies that show that the average spinal curvature may drastically differ from standing radiographic images, which can lead to significant errors in surgical planning when not considered. The proposed sensing array will be placed on the patient in a controlled environment at the end of a standard consultation. Developed sensor calibration methods will be used to increase accuracy and reduces placement error, providing a predictive pose estimation system. Advancements in this field may enable previously uncaptured functional assessments of patients in a natural environment and lead to substantial improvements in remote monitoring. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.