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Knee Joint

Knee Joint

The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
A total of seven ligaments support the knee joint. The patellar ligament, which is also attached to the quadriceps femoris...

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Related Experiment Video

Updated: Sep 24, 2025

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Engineering Platform and Experimental Protocol for Design and Evaluation of a Neurally-controlled Powered Transfemoral Prosthesis

Published on: July 22, 2014

Self-Powered Load Sensing Circuitry for Total Knee Replacement.

Manav Jain¹, Nabid Aunjum Hossain², Shahrzad Towfighian²

¹Stony Brook University (SUNY), Stony Brook, NY, USA.

IEEE Sensors Journal

|May 9, 2022

Summary

This study designed a smart knee implant using triboelectric energy harvesting to monitor knee load. This technology offers a promising, self-powered solution for tracking implant performance and patient knee health.

Keywords:

PCB prototype frontend electronics harvester smart knee implant total knee replacement (TKR)triboelectric voltage processing

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Published on: May 8, 2014

Area of Science:

Biomedical Engineering
Materials Science
Energy Harvesting

Background:

Increasing prevalence of total knee replacement (TKR) surgeries necessitates improved implant monitoring.
Optimal knee load monitoring is crucial for enhancing the reliability of knee implants.
Existing monitoring methods lack self-powering capabilities for long-term in-vivo application.

Purpose of the Study:

To design and demonstrate a smart knee implant system capable of self-monitoring knee load.
To integrate a triboelectric energy harvester with a frontend electronic system for signal processing.
To validate the feasibility of using harvested energy for both powering and data acquisition within the implant.

Main Methods:

Development of a triboelectric energy harvester integrated into a knee implant prototype.
Design and fabrication of a printed circuit board (PCB) frontend electronic system.
Characterization of the system's performance under varying cyclic knee loads, including voltage processing, rectification, and signal digitization.

Main Results:

The triboelectric harvester generated AC signals with peak voltages from 10 V to 150 V.
The frontend system successfully converted AC signals to a stabilized DC voltage for powering an analog-to-digital converter (ADC).
The proposed system demonstrated low power consumption (approx. 5.35 μW) and feasibility for self-monitoring knee load.

Conclusions:

Triboelectric energy harvesting is a viable and promising technique for self-powered, in-situ load monitoring in knee implants.
The developed smart knee implant system offers a novel approach for enhancing implant reliability and patient care.
Further improvements to the frontend circuitry can accommodate a wider range of cyclic loads, expanding clinical applicability.