Literature DB >> 10721629

Vibration arthrometry in the patients with failed total knee replacement.

C C Jiang1, J H Lee, T T Yuan.   

Abstract

This is a preliminary research on the vibration arthrometry of artificial knee joint in vivo. Analyzing the vibration signals measured from the accelerometer on patella, there are two speed protocols in knee kinematics: 1) 2 degrees/s, the signal is called "physiological patellofemoral crepitus (PPC)", and 2) 67 degrees/s, the signal is called "vibration signal in rapid knee motion". The study has collected 14 patients who had revision total knee arthroplasty due to prosthetic wear or malalignment represent the failed total knee replacement (FTKR), and 12 patients who had just undergone the primary total knee arthroplasty in the past two to six months and have currently no knee pain represent the normal total knee replacement (NTKR). FTKR is clinically divided into three categories: metal wear, polyethylene wear of the patellar component, and no wear but with prosthesis malalignment. In PPC, the value of root mean square (rms) is used as a parameter; in vibration signals in rapid knee motion, autoregressive modeling is used for adaptive segmentation and extracting the dominant pole of each signal segment to calculate the spectral power ratios in f < 100 Hz and f > 500 Hz. It was found that in the case of metal wear, the rms value of PPC signal is far greater than a knee joint with polyethylene wear and without wear, i.e., PPC signal appears only in metal wear. As for vibration signals in rapid knee motion, prominent time-domain vibration signals could be found in the FTKR patients with either polyethylene or metal wear of the patellar component. We also found that for normal knee joint, the spectral power ratio of dominant poles has nearly 80% distribution in f < 100 Hz, is between 50% and 70% for knee with polyethylene wear and below 30% for metal wear, whereas in f > 500 Hz, spectral power ratio of dominant poles has over 30% distribution in metal wear but only nonsignificant distribution in polyethylene wear, no wear, and normal knee. The results show that vibration signals in rapid knee motion can be used for effectively detecting polyethylene wear of the patellar component in the early stage, while PPC signals can only be used to detect prosthetic metal wear in the late stage.

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Mesh:

Year:  2000        PMID: 10721629     DOI: 10.1109/10.821764

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

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Authors:  Chin-Shiuh Shieh; Chin-Dar Tseng; Li-Yun Chang; Wei-Chun Lin; Li-Fu Wu; Hung-Yu Wang; Pei-Ju Chao; Chien-Liang Chiu; Tsair-Fwu Lee
Journal:  BMC Res Notes       Date:  2016-07-19

2.  An acoustical evaluation of knee sound for non-invasive screening and early detection of articular pathology.

Authors:  Keo Sik Kim; Jeong Hwan Seo; Chul Gyu Song
Journal:  J Med Syst       Date:  2010-06-17       Impact factor: 4.460

3.  Screening of knee-joint vibroarthrographic signals using statistical parameters and radial basis functions.

Authors:  Rangaraj M Rangayyan; Y F Wu
Journal:  Med Biol Eng Comput       Date:  2007-10-25       Impact factor: 2.602

Review 4.  Altering the Course of Technologies to Monitor Loosening States of Endoprosthetic Implants.

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Journal:  Sensors (Basel)       Date:  2019-12-23       Impact factor: 3.576

5.  Multiscale Sensing of Bone-Implant Loosening for Multifunctional Smart Bone Implants: Using Capacitive Technologies for Precision Controllability.

Authors:  Inês Peres; Pedro Rolo; Jorge A F Ferreira; Susana C Pinto; Paula A A P Marques; António Ramos; Marco P Soares Dos Santos
Journal:  Sensors (Basel)       Date:  2022-03-25       Impact factor: 3.576

6.  Knee joint vibration signal analysis with matching pursuit decomposition and dynamic weighted classifier fusion.

Authors:  Suxian Cai; Shanshan Yang; Fang Zheng; Meng Lu; Yunfeng Wu; Sridhar Krishnan
Journal:  Comput Math Methods Med       Date:  2013-03-12       Impact factor: 2.238

  6 in total

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