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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Significant acoustic emissions occur at similar joint angles for repeated exercises, suggesting reliability of audio sounds for knee activities.
“The significant acoustic emissions were found to occur at similar joint angles for repeated exercises, suggesting the reliability of the audio sounds for knee activities.”
From Human-centred artificial intelligence for mobile health sensing: challenges and opportunities (2023) · cites this paper as [65]
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BackgroundWearable Sensors for Vital Signs: A Review of 20 Years and Future Directions
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Vibration Stimulation as a Non-Invasive Approach to Monitor the Severity of Meniscus Tears
Safaei, M., Bolus, N. B., Whittingslow, D. C., Jeong, H. K., Ertürk, A., & Inan, O. T. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3050439 · Cited by 4 · see citing works
“from healthy ones in both ex vivo and in vivo studies [13], [14].”
BackgroundSelf-citationBalancing Sampling Frequencies for Multi-modality IoT Systems: Smart Shoe as an Example
Deng, W., Chen, K., Ying, Q., & Cheng, J. (2022) · IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS) · doi:10.1109/iemtronics55184.2022.9795785 · Cited by 3 · see citing works
Cui, W., Fang, M., 安俊贤, Shen, Y., Hang, H., Zhou, Y., Zhu, H., & Huang, J. (2026) · Langmuir · doi:10.1021/acs.langmuir.5c06906 · Cited by 2 · see citing works
A four-bar knee joint measurement walking system for prosthesis design
Zhang, Y., Cao, W., Yu, H., Meng, Q., & Lv, J. (2021) · Technology and Health Care · doi:10.3233/thc-202667 · Cited by 2 · see citing works
“Researchers also leveraged inertial sensors to measure knee joint kinematics [4] and dynamic knee valgus and risk of knee injury during the single leg squat [5].”
Freeborn, T. J., Critcher, S., & Hooper, G. L. (2024) · Frontiers in Electronics · doi:10.3389/felec.2024.1238967 · Cited by 1 · see citing works
Design and Evaluation of a Wrist Wearable Joint Acoustic Emission Monitoring System
Hochman, D. M., Ozmen, G. C., Ponder, L. A., Prahalad, S., & Inan, O. T. (2021) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn51625.2021.9507015 · Cited by 1 · see citing works
Self-citationBPLMSBT: Blockchain-Based Permission List for Mitigating the Sensor-Based Threats on Smartphones
Manimaran, S., Sastry, V. N., & Gopalan, N. P. (2022) · IEEE Sensors Journal · doi:10.1109/jsen.2022.3167893 · Cited by 1 · see citing works
Textile Game Controller: Smart knee pads for Therapeutic Exercising
Zahn, E. F., Fischer, H. F., Gleiß, C., Avramidis, E., & Joost, G. (2023) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3544549.3583899 · Cited by 1 · see citing works
Machine Learning Amplified Control System for HASEL Actuator Soft Robot System
Dong, Y. (2022) · Journal of Physics Conference Series · doi:10.1088/1742-6596/2405/1/012026
“[21] Teague C, Heller J, Nevius B, et al.”
BackgroundDesign and Implementation of Knee Angle Recovery Companion Kit: A Knee Flex Rehab Aid System
Ram Nivas., D., Krishnaraj, R., Kathirvelu, M., & Niranjana, M. I. (2024) · International Conference on Science Technology Engineering and Mathematics (ICONSTEM) · doi:10.1109/iconstem60960.2024.10568887
“[3] This research employs Internet of Things (IoT) technology to enable the automated monitoring of plants and the implementation of smart gardening practices.”
MethodNon-Invasive Monitoring of Knee Osteoarthritis Severity Using Vibration Stimulation
Tokoshima, T., Kazunori, H. A. S. E., Gong, R., & Yoshida, M. (2025) · Proceedings of Engineering and Technology Innovation · doi:10.46604/peti.2024.14079
“Additionally, recent studies have shown that certain knee injuries, such as meniscal tears, can be distinguished from healthy knees by analyzing the acoustic emissions produced by the joint [8-9].”
Automatic Ambu bag design and implementation using IOT
Ganesan, A., Ariyumuthu, A., Ponnusamy, S., Murugesan, B., & Khairunizam, W. (2025) · AIP conference proceedings · doi:10.1063/5.0269959
Doğu, E., Jones, J. M., Alomainy, A., & Rajab, K. Z. (2026) · IEEE Internet of Things Journal · doi:10.1109/jiot.2026.3680222
A Wearable Knee Brace System For Real-Time Gait Monitoring And Abnormality Detection
S, J. L. L., Chethan, N., & Soundararajan, A. (2025) · International Conference on Biomedical Engineering and Sustainable Healthcare (ICBMESH) · doi:10.1109/icbmesh66209.2025.11182180
“In peripheral mode, the ESP32 advertises its services to a central BLE-enabled device, in this example a smartphone running an application built with Flutter [29] [30].”
A Preliminary Approach to Segmentation-Based Extraction of Vibroarthrographic Signals
Tjakrawinata, K. G., Jian, Y.-L., Lee, T.-F., & Lin, J. (2025) · IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan) · doi:10.1109/icce-taiwan66881.2025.11207775
“These vibroarthrographic (VAG) signals originate from the "stick and slip" phenomenon occurring in the patellofemoral joint [2].”
Kilic, O. S., Emirdagi, A. R., Nichols, C. J., Goossens, Q., Ewart, D. T., & Inan, O. T. (2026) · npj Biomedical Innovations. · doi:10.1038/s44385-025-00064-4
“This study used a wearable acoustic sensing device design previously developed by Teague et al. 41 .”
Self-citationZawawi, M. A., & M., S. G. (2026) · Journal of Instrumentation · doi:10.1088/1748-0221/21/02/p02021
“The detailed statistical analysis, revealing the sensor’s efficacy in identifying inconsistent and asymmetrical knee joint movements, demonstrates its potential as a diagnostic and rehabilitative tool [12].”
Hemalatha, J., & S, B. T. (2026) · International Conference on Electronics and Renewable Systems (ICEARS) · doi:10.1109/icears67481.2026.11416710
“Teague et al. [28] introduced a multimodal knee health monitoring wearable integrating with IMU, EMG, and acoustic sensing to assess knee joint function designed for everyday activities.”
OctaKnee: A Smart Knee Health Monitoring System
Gupta, P., Patil, K. P., Shivakumar, P., Aekbote, P. G., & J., S. M. (2026) · International Conference on Information Technology · doi:10.1109/it67293.2026.11435770
“As the field matured, researchers shifted toward multimodal sensing to obtain a more holistic representation of joint health, incorporating motion, thermal, and pressure-related indicators [16] [17].”
Huang, Z., Yan, L., Gu, W., Xing, W., & Lyu, L. (2026) · IEEE International Symposium on Circuits and Systems proceedings · doi:10.1109/iscas66217.2026.11562659
“[7], [8] have explored reconfigurable systems that integrate multiple sensing modalities within a unified platform, yet most existing implementations remain relatively large and power demanding.”
Karpiński, R., & Syta, A. (2026) · Applied Computer Science · doi:10.35784/acs_10230
“Wearable systems have already been developed to simultaneously record joint acoustics, bioimpedance, inertial data, and temperature (Teague et al., 2020).”
- Authors
- Teague, C. N., Heller, J. A., Nevius, B. N., Carek, A. M., Mabrouk, S., Garcia-Vicente, F., Inan, O. T., & Etemadi, M.
- Affiliations
- Georgia Institute of Technology (US)
- Northwestern University (US)
- ORCID
- Venue
- IEEE Sensors Journal
- Published
- 2020-09-15
- Volume
- 20
- Issue
- 18
- Pages
- 10323-10334
- ISSN
- 1530-437X (ISSN-L)
- 1558-1748
- 2379-9153
- OpenAlex
- W3025531568
- Cited by
- 66
- References
- 37
- Citations by year
- 2026: 8 · 2025: 7 · 2024: 7 · 2023: 8 · 2022: 18 · 2021: 17 · 2020: 1
- FWCI
- 3.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Sensors Journal (publishedVersion)
- Funders
- Defense Advanced Research Projects Agency (DARPA) Biological Technologies Office (BTO) ElectRx program through the Naval InformationWarfare Center (N66001-19-2-4002)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Biomedical Engineering › Advanced Sensor and Energy Harvesting Materials
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Keywords
- wearable sensors, multimodal sensing, bioimpedance, inertial sensors, skin temperature, microcontroller data acquisition, knee swelling, home monitoring
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