A Wearable, Multimodal Sensing System to Monitor Knee Joint Health

Caitlin N. Teague*, J. Alex Heller, Brandi N. Nevius, Andrew M. Carek, Samer Mabrouk, Florencia Garcia-Vicente, Omer T. Inan, Mozziyar Etemadi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Scopus citations


Objective: We designed and validated a wearable, multimodal sensor brace for knee joint health assessment. Methods: An embedded-, two-microcontroller-based approach is used to sample high-throughput, multi-microphone joint acoustics (46.875 kHz) as well as lower-rate electrical bioimpedance (EBI) (1/46.17 s), inertial (100-250 Hz), and skin temperature (1 Hz) data, and these data are saved onto microSD cards. Additionally, a flexible, 3D-printed brace houses the custom circuit boards and sensors to enable wearable sensing. Results: The system achieves 9 hours of continuous joint sound recording, while the EBI, inertial, and temperature sensors can sample for 35 hours using 500 mAh batteries. Further, for the entirety of these continuous recordings, there were no dropped samples for any of the sensors. Lastly, proof-of-concept measurements were used to show the system's efficacy for recording joint sounds and swelling data. Conclusion: This is, to the best of our knowledge, the first, completely untethered wearable system for multimodal knee health monitoring. Significance: The proposed smart brace may facilitate in-clinic or at-home measurements for joint health assessment.

Original languageEnglish (US)
Article number9093890
Pages (from-to)10323-10334
Number of pages12
JournalIEEE Sensors Journal
Issue number18
StatePublished - Sep 15 2020


  • Embedded software
  • joint physiology
  • mHealth
  • rapid prototyping
  • wearable sensors

ASJC Scopus subject areas

  • Instrumentation
  • Electrical and Electronic Engineering


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