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International Journal of Science, Strategic Management and Technology

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ISSN: 3108-1762 (Online)
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WEARABLE IOT SYSTEM FOR MONITORING KNEE ANGLE AND PLANTAR FORCE FOR EARLY DETECTION OF KNEE OSTEOARTHRITIS

AUTHORS:
Ajith M , Balaji D , Gopinath S, Brintha K
Mentor
Affiliation
Department of Biomedical Engineering Kongunadu College of Engineering and Technology Tamil Nadu, India
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

Knee Osteoarthritis (KOA) is a progressive degenerative joint disorder that significantly affects mobility and quality of life. Early detection and continuous monitoring of knee joint movement are essential to prevent severe joint damage. Conventional diagnostic techniques such as X-ray and Magnetic Resonance Imaging (MRI) provide structural information but are expensive and not suitable for continuous monitoring. This paper proposes an Internet of Things (IoT)-based wearable system for monitoring knee angle and plantar force to support early detection of KOA.


The system integrates an ESP32 microcontroller, MPU6050 inertial measurement unit, and a plantar force sensor to measure knee movement and foot pressure during walking. Sensor data are transmitted via Wi-Fi to the Blynk IoT platform for real-time monitoring. Experimental results indicate that normal knee movement produces flexion angles between 53°–72°, while reduced angles of 20°–30° may indicate possible KOA conditions.


Keywords
IoT Knee Osteoarthritis ESP32 MPU6050 Plantar Force Sensor Wearable Healthcare Blynk IoT
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K, A. M. ,. B. D. ,. G. S. B. (2026). Wearable IOT System for Monitoring Knee Angle and Plantar Force for Early Detection of Knee Osteoarthritis. International Journal of Science, Strategic Management and Technology, 02(03). https://doi.org/10.55041/ijsmt.v2i3.062

K, Ajith. "Wearable IOT System for Monitoring Knee Angle and Plantar Force for Early Detection of Knee Osteoarthritis." International Journal of Science, Strategic Management and Technology, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i3.062.

K, Ajith. "Wearable IOT System for Monitoring Knee Angle and Plantar Force for Early Detection of Knee Osteoarthritis." International Journal of Science, Strategic Management and Technology 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i3.062.

References
1.D. Kobsar, Z. Masood, H. Khan, et al. “Wearable inertial sensors for gait analysis in adults with osteoarthritis: A scoping review,” Sensors, vol. 20, no. 24, pp. 1–18, 2020.

2.W. Tao, T. Liu, R. Zheng, and H. Feng, “Gait analysis using wearable sensors,” Sensors, vol. 12, no. 2, pp. 2255–2283, 2012.

3.R. J. Boekesteijn, J. van Gerven, A. Geurts, and K. Smulders, “Objective gait assessment in individuals with knee osteoarthritis using inertial sensors,” Gait & Posture, 2022.

4.H. Zhang et al., “Validation of an IMU-based wearable system for lower-extremity gait analysis,” Sensors, 2023.

5.J. Xie et al., “Functional monitoring of patients with knee osteoarthritis based on multidimensional wearable plantar pressure features,” JMIR Rehabilitation and Assistive Technologies, 2024.

6.S. J. Snyder et al., “Prediction of knee adduction moment using instrumented insoles and deep learning,” Medical Engineering & Physics, 2023.

7.U. Manupibul et al., “Integration of force and IMU sensors for a low-cost portable gait measurement system,” Scientific Reports, vol. 13, 2023.

8.J. S. Tan et al., “Human activity recognition for people with knee osteoarthritis using wearable IMU sensors,” Sensors, vol. 21, no. 10, 2021.

9.L. Forsyth et al., “Validity of wearable sensors for monitoring gait in knee arthroplasty patients,” Medical Engineering & Physics, 2024.

10.X. Liu et al., “Wearable devices for gait analysis in intelligent healthcare,” Frontiers in Computer Science, 2021.
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✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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