Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis

SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of Move...

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Main Authors: Alhossary, Amr, Ang, Wei Tech, Chua, Karen Sui Geok, Tay, Matthew Rong Jie, Ong, Poo Lee, Murakami, Tsurayuki, Quake, Tabitha, Binedell, Trevor, Wee, Seng Kwee, Phua, Min Wee, Wei, Yong Jia, Donnelly, Cyril John
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/164726
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1647262023-02-13T02:24:49Z Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis Alhossary, Amr Ang, Wei Tech Chua, Karen Sui Geok Tay, Matthew Rong Jie Ong, Poo Lee Murakami, Tsurayuki Quake, Tabitha Binedell, Trevor Wee, Seng Kwee Phua, Min Wee Wei, Yong Jia Donnelly, Cyril John School of Mechanical and Aerospace Engineering Rehabilitation Research Institute of Singapore, NTU Engineering::Bioengineering Engineering::Mechanical engineering Statistical Parametric Mapping Transtibial Amputation SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of MovementRx in the prediction of increased joint forces with the possibility to predispose to osteoarthritis in a sample of post-surgical Transtibial Amputation (TTA) patients who were ambulant in the community. We captured the three-dimensional movement profile of 12 males with TTA and studied them using MovementRx, employing the SPM1D Python library to quantify the deviation(s) they have from our corresponding reference data, using "Hotelling 2" and "T test 2" statistics for the 3D movement vectors of the 3 main lower limb joints (hip, knee, and ankle) and their nine respective components (3 joints × 3 dimensions), respectively. MovementRx results visually demonstrated a clear distinction in the biomechanical recordings between TTA patients and a reference set of normal people (ABILITY data project), and variability within the TTA patients' group enabled identification of those with an increased risk of developing osteoarthritis in the future. We conclude that MovementRx is a potential tool to detect increased specific joint forces with the ability to identify TTA survivors who may be at risk for osteoarthritis. Agency for Science, Technology and Research (A*STAR) Nanyang Technological University Published version The Rehabilitation Research Institute of Singapore (RRIS) is funded by tripartite funding: The Agency for Science, Technology and Research (A-STAR), the National Healthcare Group (NHG, Singapore), and the Nanyang Technological University (NTU Singapore). This work is part of the Ability data project in RRIS (www.ntu.edu.sg/rris/research-focus/ability-data (accessed on 1 June 2022)). 2023-02-13T02:24:49Z 2023-02-13T02:24:49Z 2022 Journal Article Alhossary, A., Ang, W. T., Chua, K. S. G., Tay, M. R. J., Ong, P. L., Murakami, T., Quake, T., Binedell, T., Wee, S. K., Phua, M. W., Wei, Y. J. & Donnelly, C. J. (2022). Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis. Bioengineering, 9(7), 9070293-. https://dx.doi.org/10.3390/bioengineering9070293 2306-5354 https://hdl.handle.net/10356/164726 10.3390/bioengineering9070293 35877344 2-s2.0-85133526576 7 9 9070293 en Bioengineering © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Bioengineering
Engineering::Mechanical engineering
Statistical Parametric Mapping
Transtibial Amputation
spellingShingle Engineering::Bioengineering
Engineering::Mechanical engineering
Statistical Parametric Mapping
Transtibial Amputation
Alhossary, Amr
Ang, Wei Tech
Chua, Karen Sui Geok
Tay, Matthew Rong Jie
Ong, Poo Lee
Murakami, Tsurayuki
Quake, Tabitha
Binedell, Trevor
Wee, Seng Kwee
Phua, Min Wee
Wei, Yong Jia
Donnelly, Cyril John
Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis
description SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of MovementRx in the prediction of increased joint forces with the possibility to predispose to osteoarthritis in a sample of post-surgical Transtibial Amputation (TTA) patients who were ambulant in the community. We captured the three-dimensional movement profile of 12 males with TTA and studied them using MovementRx, employing the SPM1D Python library to quantify the deviation(s) they have from our corresponding reference data, using "Hotelling 2" and "T test 2" statistics for the 3D movement vectors of the 3 main lower limb joints (hip, knee, and ankle) and their nine respective components (3 joints × 3 dimensions), respectively. MovementRx results visually demonstrated a clear distinction in the biomechanical recordings between TTA patients and a reference set of normal people (ABILITY data project), and variability within the TTA patients' group enabled identification of those with an increased risk of developing osteoarthritis in the future. We conclude that MovementRx is a potential tool to detect increased specific joint forces with the ability to identify TTA survivors who may be at risk for osteoarthritis.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Alhossary, Amr
Ang, Wei Tech
Chua, Karen Sui Geok
Tay, Matthew Rong Jie
Ong, Poo Lee
Murakami, Tsurayuki
Quake, Tabitha
Binedell, Trevor
Wee, Seng Kwee
Phua, Min Wee
Wei, Yong Jia
Donnelly, Cyril John
format Article
author Alhossary, Amr
Ang, Wei Tech
Chua, Karen Sui Geok
Tay, Matthew Rong Jie
Ong, Poo Lee
Murakami, Tsurayuki
Quake, Tabitha
Binedell, Trevor
Wee, Seng Kwee
Phua, Min Wee
Wei, Yong Jia
Donnelly, Cyril John
author_sort Alhossary, Amr
title Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis
title_short Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis
title_full Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis
title_fullStr Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis
title_full_unstemmed Identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using SPM1D analysis
title_sort identification of secondary biomechanical abnormalities in the lower limb joints after chronic transtibial amputation: a proof-of-concept study using spm1d analysis
publishDate 2023
url https://hdl.handle.net/10356/164726
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