The work centers on wearable joint health monitoring through acoustical sensing. It presents a miniaturized, fully digital sensing system designed for convenient attachment to the knee using adhesive. The system offers potential applications in streamlined data collection for monitoring athletes and individuals with joint disorders, as well as future prospects for decentralized digital clinical trials.
The paper was first authored by Ph.D. candidate Mohammad Nikbakht and senior authored by Inan.
“The KneeMS system that Mohammad has built is a noteworthy step forward in wearable health monitoring,” said Inan. “It not only signifies progress in monitoring joint health but also hints at potential shifts in how we conduct clinical trials and approach treatments and therapies.”
Nikbakht and Inan were presented the award at IEEE BSN 2023 on October 9 in Cambridge, Mass. IEEE BSN unites academia, industry, healthcare, and non-profit leaders and experts, offering a cross-disciplinary single-track forum for pioneering research on devices and sensors, as well as hardware and software system.
Top photo caption: Professor Omer Inan (left) and Ph.D. candidate Mohammad Nikbakht with the IEEE BSN 2023 Best Paper award.
