Ensemble classifiers for medical diagnosis of knee osteoarthritis using gait data

2006-12-16
Koktas, Nigar Sen
Yalabik, Nese
Yavuzer, Gunes
Automated or semi-automated gait analysis systems are important in assisting physicians for diagnosis of various diseases. The objective of this study is to discuss ensemble methods for gait classification as a part of preliminary studies of designing a semi-automated diagnosis system. For this purpose gait data is collected from 110 sick subjects (having knee Osteoarthritis (OA)) and 91 age-matched normal subjects. A set of Multilayer Perceptrons (MLPs) is trained by using joint angle and time-distance parameters of gait as features. Large dimensional feature vector is decomposed into feature subsets and the ones selected by gait expert are used to categorize subjects into two classes; healthy and patient. Ensemble of MLPs is built using these distinct feature subsets and diversification of classifiers is analyzed by cross-validation approach and confusion matrices. High diversifications observed in the confusion matrices suggested that using combining methods would help. Indeed when a proper combining rule is applied to decomposed sets, more accurate results are obtained The result suggests that ensemble of MLPs could be applied in the automated diagnosis of gait disorders in a clinical context.

Suggestions

Combining neural networks for gait classification
Sen Koktas, Nigar; Yalabik, Nese; Yavuzer, Gunes (2006-01-01)
Gait analysis can be defined as the numerical and graphical representation of the mechanical measurements of human walking patterns and is used for two main purposes: human identification, where it is usually applied to security issues, and clinical applications, where it is used for the non-automated and automated diagnosis of various abnormalities and diseases. Automated or semi-automated systems are important in assisting physicians for diagnosis of various diseases. In this study, a semi-automated gait ...
Estimation of Ground Reaction Forces Using Low-Cost Instrumented Forearm Crutches
Seylan, Çağlar; Saranlı, Uluç (2018-06-01)
Instrumented crutches are useful for many rehabilitation tasks, including monitoring the correctness of crutch use, analyzing gait properties for patients with lower-limb impairments, as well as providing sensory data for controlling lower-body robotic orthoses. In this paper, we describe the design and analysis of an instrumented crutch system equipped with low-cost accelerometer and pressure sensors to estimate all components of the ground reaction force (GRF), providing a well-defined and physically mean...
A systematic review of the reliability of objective structured clinical examination scores
Brannick, Michael T.; Erol-Korkmaz, H. Tugba; Prewett, Matthew (2011-12-01)
CONTEXT The objective structured clinical examination (OSCE) is comprised of a series of simulations used to assess the skill of medical practitioners in the diagnosis and treatment of patients. It is often used in high-stakes examinations and therefore it is important to assess its reliability and validity.
Numerical aspects of anisotropic failure in soft biological tissues favor energy-based criteria: A rate-dependent anisotropic crack phase-field model
Gueltekin, Osman; Dal, Hüsnü; Holzapfel, Gerhard A. (2018-04-01)
A deeper understanding to predict fracture in soft biological tissues is of crucial importance to better guide and improve medical monitoring, planning of surgical interventions and risk assessment of diseases such as aortic dissection, aneurysms, atherosclerosis and tears in tendons and ligaments. In our previous contribution (Gultekin et al., 2016) we have addressed the rupture of aortic tissue by applying a holistic geometrical approach to fracture, namely the crack phase-field approach emanating from va...
Voxel-MARS: a method for early detection of Alzheimer's disease by classification of structural brain MRI
Cevik, Alper; Weber, Gerhard-Wilhelm; Eyüboğlu, Behçet Murat; Oguz, Kader Karli (2017-11-01)
Neuroscience is of emerging importance along with the contributions of Operational Research to the practices of diagnosing neurodegenerative diseases with computer-aided systems based on brain image analysis. Although multiple biomarkers derived from Magnetic Resonance Imaging (MRI) data have proven to be effective in diagnosing Alzheimer's disease (AD) and mild cognitive impairment (MCI), no specific system has yet been a part of routine clinical practice. This paper aims to introduce a fully-automated vox...
Citation Formats
N. S. Koktas, N. Yalabik, and G. Yavuzer, “Ensemble classifiers for medical diagnosis of knee osteoarthritis using gait data,” 2006, p. 225, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66703.