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

doi:10.1109/JSEN.2020.2994552

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

Anesthesiology

Research output: Contribution to journal › Article › peer-review

53 Scopus citations

Abstract

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 language	English (US)
Article number	9093890
Pages (from-to)	10323-10334
Number of pages	12
Journal	IEEE Sensors Journal
Volume	20
Issue number	18
DOIs	https://doi.org/10.1109/JSEN.2020.2994552
State	Published - Sep 15 2020

Funding

Manuscript received April 10, 2020; accepted April 28, 2020. Date of publication May 14, 2020; date of current version August 14, 2020. This work was supported by the Defense Advanced Research Projects Agency (DARPA) Biological Technologies Office (BTO) ElectRx program through the Naval Information Warfare Center (NIWC) under Cooperative Agreement N66001-19-2-4002. The associate editor coordinating the review of this article and approving it for publication was Dr. Wan-Young Chung. (Corresponding author: Caitlin N. Teague.) Caitlin N. Teague and Samer Mabrouk are with the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30308 USA (e-mail: [email protected]).

Keywords

Embedded software
joint physiology
mHealth
rapid prototyping
wearable sensors

ASJC Scopus subject areas

Instrumentation
Electrical and Electronic Engineering

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10.1109/JSEN.2020.2994552

Cite this

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title = "A Wearable, Multimodal Sensing System to Monitor Knee Joint Health",

abstract = "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.",

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author = "Teague, {Caitlin N.} and Heller, {J. Alex} and Nevius, {Brandi N.} and Carek, {Andrew M.} and Samer Mabrouk and Florencia Garcia-Vicente and Inan, {Omer T.} and Mozziyar Etemadi",

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AU - Mabrouk, Samer

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AU - Inan, Omer T.

AU - Etemadi, Mozziyar

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N2 - 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.

AB - 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.

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A Wearable, Multimodal Sensing System to Monitor Knee Joint Health

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