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Discovering differences in acoustic emission between healthy and osteoarthritic knees using a four-phase model of sit-stand-sit movements.

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Discovering differences in acoustic emission between healthy and osteoarthritic knees using a four-phase model of sit-stand-sit movements. / Shark, Lik Kwan; Chen, H; Goodacre, John.

In: Open Medical Informatics Journal, Vol. 4, 27.07.2010, p. 116-125.

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@article{a36b3c13126745e2b9b7beb65f1b5e84,
title = "Discovering differences in acoustic emission between healthy and osteoarthritic knees using a four-phase model of sit-stand-sit movements.",
abstract = "By performing repeated sit-stand-sit movements to create stress on knee joints, short transient bursts of high frequency acoustic emission (AE) released by the knee joints were acquired from two age matched groups consisting of healthy and osteoarthritic (OA) knees, and significant differences between these two groups were discovered from the signal analysis performed. The analysis is based on a four-phase model of sit-stand-sit movements and a two-feature descriptor of AE bursts. The four phases are derived from joint angle measurement during movement, and they consist of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descendingacceleration and descending-deceleration phases in the stand-to-sit movement. The two features are extracted from AE measurement during movement, and they consist of the peak magnitude value and average signal level of each AE burst. The proposed analysis method is shown to provide a high sensitivity for differentiation of the two age matched healthy and OA groups, with the most significant difference found to come from the peak magnitude value in the ascendingdeceleration phase, clear quantity and strength differences in the image based visual display of their AE feature profiles due to substantially more AE bursts from OA knee joints with higher peak magnitude values and higher average signal levels, and two well separated clusters in the space formed by the principal components. These results provide ample support for further development of AE as a novel tool to facilitate dynamic integrity assessment of knee joints in clinic and home settings.",
keywords = "acoustic emission, knee joint assessment",
author = "Shark, {Lik Kwan} and H Chen and John Goodacre",
year = "2010",
month = jul,
day = "27",
doi = "10.2174/1874431101004010116",
language = "English",
volume = "4",
pages = "116--125",
journal = "Open Medical Informatics Journal",
issn = "1874-4311",

}

RIS

TY - JOUR

T1 - Discovering differences in acoustic emission between healthy and osteoarthritic knees using a four-phase model of sit-stand-sit movements.

AU - Shark, Lik Kwan

AU - Chen, H

AU - Goodacre, John

PY - 2010/7/27

Y1 - 2010/7/27

N2 - By performing repeated sit-stand-sit movements to create stress on knee joints, short transient bursts of high frequency acoustic emission (AE) released by the knee joints were acquired from two age matched groups consisting of healthy and osteoarthritic (OA) knees, and significant differences between these two groups were discovered from the signal analysis performed. The analysis is based on a four-phase model of sit-stand-sit movements and a two-feature descriptor of AE bursts. The four phases are derived from joint angle measurement during movement, and they consist of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descendingacceleration and descending-deceleration phases in the stand-to-sit movement. The two features are extracted from AE measurement during movement, and they consist of the peak magnitude value and average signal level of each AE burst. The proposed analysis method is shown to provide a high sensitivity for differentiation of the two age matched healthy and OA groups, with the most significant difference found to come from the peak magnitude value in the ascendingdeceleration phase, clear quantity and strength differences in the image based visual display of their AE feature profiles due to substantially more AE bursts from OA knee joints with higher peak magnitude values and higher average signal levels, and two well separated clusters in the space formed by the principal components. These results provide ample support for further development of AE as a novel tool to facilitate dynamic integrity assessment of knee joints in clinic and home settings.

AB - By performing repeated sit-stand-sit movements to create stress on knee joints, short transient bursts of high frequency acoustic emission (AE) released by the knee joints were acquired from two age matched groups consisting of healthy and osteoarthritic (OA) knees, and significant differences between these two groups were discovered from the signal analysis performed. The analysis is based on a four-phase model of sit-stand-sit movements and a two-feature descriptor of AE bursts. The four phases are derived from joint angle measurement during movement, and they consist of the ascending-acceleration and ascending-deceleration phases in the sit-to-stand movement, followed by the descendingacceleration and descending-deceleration phases in the stand-to-sit movement. The two features are extracted from AE measurement during movement, and they consist of the peak magnitude value and average signal level of each AE burst. The proposed analysis method is shown to provide a high sensitivity for differentiation of the two age matched healthy and OA groups, with the most significant difference found to come from the peak magnitude value in the ascendingdeceleration phase, clear quantity and strength differences in the image based visual display of their AE feature profiles due to substantially more AE bursts from OA knee joints with higher peak magnitude values and higher average signal levels, and two well separated clusters in the space formed by the principal components. These results provide ample support for further development of AE as a novel tool to facilitate dynamic integrity assessment of knee joints in clinic and home settings.

KW - acoustic emission

KW - knee joint assessment

U2 - 10.2174/1874431101004010116

DO - 10.2174/1874431101004010116

M3 - Journal article

VL - 4

SP - 116

EP - 125

JO - Open Medical Informatics Journal

JF - Open Medical Informatics Journal

SN - 1874-4311

ER -