TY - JOUR
T1 - Versatile clinical movement analysis using statistical parametric mapping in MovementRx
AU - Alhossary, Amr
AU - Pataky, Todd
AU - Ang, Wei Tech
AU - Chua, Karen Sui Geok
AU - Kwong, Wai Hang
AU - Donnelly, Cyril John
N1 - Funding Information:
We are thankful to Mr. Jia Wei YONG, for his help to make this work a reality. We are thankful to Dr. Matthew Tay Rong Jie, Dr. Ong Poo Lee, A/Prof. Wee Seng Kwee, and Mr. Phua Min Wee from Centre of Rehabilitation excellence,Tan Tock Seng Hospital Rehabilitation Centre; and to Mr. Binedell Trevor Brian, Mr. Tsurayuki Murakami Guanzhi, and Ms. Tabitha Quake Zhi Hui from Tan Tock Seng Hospital Foot and Limb Care Design Center, for their valuable inputs during the discussions towards the release of the software. We offer our sincere condolences to the family of the late Dr. Cyril John Donnelly who passed away before this manuscript had the chance to see the light.
Publisher Copyright:
© 2023, The Author(s).
PY - 2023/2/10
Y1 - 2023/2/10
N2 - Clinical gait analysis is an important biomechanics field that is often influenced by subjectivity in time-varying analysis leading to type I and II errors. Statistical Parametric Mapping can operate on all time-varying joint dynamics simultaneously, thereby overcoming subjectivity errors. We present MovementRx, the first gait analysis modelling application that correctly models the deviations of joints kinematics and kinetics both in 3 and 1 degrees of freedom; presented with easy-to-understand color maps for clinicians with limited statistical training. MovementRx is a python-based versatile GUI-enabled movement analysis decision support system, that provides a holistic view of all lower limb joints fundamental to the kinematic/kinetic chain related to functional gait. The user can cascade the view from single 3D multivariate result down to specific single joint individual 1D scalar movement component in a simple, coherent, objective, and visually intuitive manner. We highlight MovementRx benefit by presenting a case-study of a right knee osteoarthritis (OA) patient with otherwise undetected postintervention contralateral OA predisposition. MovementRx detected elevated frontal plane moments of the patient’s unaffected knee. The patient also revealed a surprising adverse compensation to the contralateral limb.
AB - Clinical gait analysis is an important biomechanics field that is often influenced by subjectivity in time-varying analysis leading to type I and II errors. Statistical Parametric Mapping can operate on all time-varying joint dynamics simultaneously, thereby overcoming subjectivity errors. We present MovementRx, the first gait analysis modelling application that correctly models the deviations of joints kinematics and kinetics both in 3 and 1 degrees of freedom; presented with easy-to-understand color maps for clinicians with limited statistical training. MovementRx is a python-based versatile GUI-enabled movement analysis decision support system, that provides a holistic view of all lower limb joints fundamental to the kinematic/kinetic chain related to functional gait. The user can cascade the view from single 3D multivariate result down to specific single joint individual 1D scalar movement component in a simple, coherent, objective, and visually intuitive manner. We highlight MovementRx benefit by presenting a case-study of a right knee osteoarthritis (OA) patient with otherwise undetected postintervention contralateral OA predisposition. MovementRx detected elevated frontal plane moments of the patient’s unaffected knee. The patient also revealed a surprising adverse compensation to the contralateral limb.
UR - http://www.scopus.com/inward/record.url?scp=85147894224&partnerID=8YFLogxK
U2 - 10.1038/s41598-023-29635-4
DO - 10.1038/s41598-023-29635-4
M3 - Journal article
C2 - 36765193
AN - SCOPUS:85147894224
SN - 2045-2322
VL - 13
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 2414
ER -