Using Knee Acoustical Emissions for Sensing Joint Health in Patients With Juvenile Idiopathic Arthritis: A Pilot Study

• Published in: IEEE sensors journal 2018-11, Vol.18 (22), p.9128-9136
• Main Authors: Semiz, Beren, Hersek, Sinan, Whittingslow, Daniel C., Ponder, Lori A., Prahalad, Sampath, Inan, Omer T.
• Format: Article
• Language: English
• Subjects: Accelerometers; Acoustic emission testing; Acoustics; Algorithms; Arthritis; Feature extraction; Knee; knee joint health; Monitoring; Patients; Pediatrics; Sensors; Wearable technologies
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2018.2869990

In this paper, we present a pilot study evaluating novel methods for assessing joint health in patients with Juvenile Idiopathic Arthritis (JIA) using wearable acoustical emission measurements from the knees. Measurements were taken from four control subjects with unknown knee injuries, and from four subjects with JIA, before and after treatment. Time and frequency domain features were extracted from the acoustical emission signals and used to compute a knee audio score. The score was used to separate out the two groups of subjects based solely on the sounds produced by their joints. It was created using a soft classifier based on gradient boosting trees. The knee audio scores ranged from 0-1 with 0 being a healthy knee and 1 being an involved joint with arthritis. Leave-one-subject-out cross-validation was used to validate the algorithm. The average of the right and left knee audio scores was 0.085±0.099 and 0.89±0.012 for the control group and group with JIA, respectively (p