Background: The conventional gait model (CGM) is commonly utilised within clinical motion analysis but has a number of inherent limitations. To overcome some of these limitations modifications have been made to the CGM and six-degrees of freedom models (6DoF) have been developed.
Research Question: How comparable are lower limb kinematics calculated using modified CGM and 6DoF models and what is the error associated with the output of each model during walking?
Methods: Ten healthy males attended two gait analysis sessions, in which they walked at a self-selected pace, while a 10-camera motion capture system recorded lower limb kinematics. Hip, knee and ankle joint kinematics in all three anatomical planes were calculated using a modified CGM, with medial anatomical markers and a three-dimensional foot added, and 6DoF. Mean absolute differences were calculated on a point-by-point basis over the walking gait cycle and interpreted relative to a 5° threshold to explore the comparability of model outputs. The standard error of the measurement (SEM) was also calculated on a point-by-point basis over the walking gait cycle for each model.
Results: Mean absolute differences above 5° were reported between the two model outputs in 58-86% of the walking gait cycle at the knee in the frontal plane, and over the entire walking gait cycle at the hip and knee in the transverse plane. SEM was typically larger for the modified CGM compared to the 6DoF, with the highest SEM values reported at the knee in the frontal plane, and the hip and the knee in the transverse plane.
Significance: Caution should be taken when looking to compare findings between studies utilising modified CGM and 6DoF outside of the sagittal plane, especially at the hip and knee. The reduced SEM associated with the 6DoF suggests this modelling approach may be preferable.
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http://dx.doi.org/10.1016/j.gaitpost.2021.06.016 | DOI Listing |
Adv Nutr
January 2025
Department of Nephrology, The Scarborough Health Network, Toronto, Ontario, Canada; Kidney Life Sciences Institute, Toronto, Ontario, Canada.
Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and other medical complications. Advances in technology that enable continuous biological data collection are transforming traditional management approaches. This review explores how multi-omics technologies and artificial intelligence (AI) are enhancing glucose management in this patient population.
View Article and Find Full Text PDFDiabetes Metab Syndr Obes
January 2025
Department of Endocrinology, Shanghai Pudong Hospital, Fudan University, Shanghai, 201399, People's Republic of China.
Background: Direct Observation of Procedural Skills (DOPS) is a clinical assessment tool that enables trainers to observe medical students' procedural abilities in real-time clinical settings. It assesses students' knowledge application, decision-making, and skill proficiency during clinical tasks.
Methods: This study modifies the DOPS to evaluate the operation of insulin pumps (PUMP) and continuous glucose monitoring systems (CGMS) in diabetes management.
Background: Insomnia is a modifiable risk factor for type 2 diabetes.
Objective: Describe the methodology for the Sleep for Health study, a randomized clinical trial examining the effectiveness of digital cognitive behavioral therapy for insomnia (dCBT-I) in reducing hyperglycemia in 300 people with both insomnia and prediabetes.
Outcomes: Primary outcome is glucose level 2 h after a 75-g glucose load.
Introduction: Hypophosphatasia is a rare inherited systemic metabolic disorder, with an estimated prevalence in the severe forms of the disease of 1/100.000-1/300.000, that affects the typical architecture of bone, leading to defective mineralization during growth and remodeling.
View Article and Find Full Text PDFAdv Sci (Weinh)
November 2024
College of Life Science and Technology, State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Huazhong University of Science and Technology, 1037 LuoYu Road, Wuhan, 430070, P. R. China.
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