Masume Saljuqi; Peyvand Ghaderyan
Volume 15, Issue 1 , May 2021, , Pages 59-71
Abstract
In the recent years, the diagnosis of Neurodegenerative Diseases (NDDs) has been one of the most challenging problems in the medical fields. Amyotrophic Lateral Sclerosis (ALS), Parkinson's Disease (PD) and Huntington's Disease (HD) are a group of neurological disorders affecting the quality of patient’s ...
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In the recent years, the diagnosis of Neurodegenerative Diseases (NDDs) has been one of the most challenging problems in the medical fields. Amyotrophic Lateral Sclerosis (ALS), Parkinson's Disease (PD) and Huntington's Disease (HD) are a group of neurological disorders affecting the quality of patient’s life. Occurrence of these diseases is due to the deterioration of motor neurons, causing human gait disturbance and asymmetry between the right and left limbs. For this purpose, in this paper various gait signals namely stride, swing, and stance intervals (from both legs) have been decomposed using a Matching Pursuit (MP) algorithm. Then, two sets of differential and dynamic features have been extracted from the MP coefficients in order to quantify the amount of divergence between both limbs. Finally, the principal components of these features have been fed as an input to sparse Non-Negative Least Squares (NNLS) classifier. The proposed algorithm has been evaluated using the gait signals of 16 healthy control subjects, 13 patients with Amyotrophic Lateral Sclerosis (ALS), 15 patients with Parkinson’s Disease (PD) and 20 patients with Huntington’s Disease (HD). The results showed that the proposed method has achieved high average accuracy rates of 84.10%, 86.67%, and 91.43% for ALS, PD, and HD detection, respectively.
Gait Analysis
Maryam Hajizade; Alireza Hashemi Oskouei; Farzan Ghalichi; Farhad Tabatabai Ghomshe; Mohammad Razi; Gisela Solo
Volume 9, Issue 1 , April 2015, , Pages 17-31
Abstract
Patients with ACL deficiency (ACLD) have to use different compensatory mechanisms to maintain their stability during daily activities. The aim of this study is to determine the differences in 3D kinematics and peak ground reaction forces (GRF) between ACL deficient legs and healthy contralateral legs ...
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Patients with ACL deficiency (ACLD) have to use different compensatory mechanisms to maintain their stability during daily activities. The aim of this study is to determine the differences in 3D kinematics and peak ground reaction forces (GRF) between ACL deficient legs and healthy contralateral legs during stair ascent. Eight subjects with unilateral ACL deficiency participated in this study. Healthy contralateral legs were considered as control group for further comparisons to ACL deficient legs. A six camera VICON motion analysis system and 2 portable force plates were used to record the locomotion while walking up custom-made stairs with two different step heights. Advanced OSSCA technique was used to assess tibiofemoral knee kinematics, a combination of symmetrical axis of rotation (SARA), symmetrical center of rotation estimation (SCoRE) and optimal common shape technique (OCST). The results of this study show that participants with ACLD experienced different kinematics and peak GRFs in different step heights (p<0.05). During ascending stairs with 17cm height, legs with ACLD exhibited less varus, more external rotation and less impact peak in pre-swing stance and early swing phase compared to contralateral healthy leg (p<0.05). The other stair height, 20 cm, resulted in more extension, more valgus and more external tibia rotation in injured leg compared to contralateral leg during terminal extension of stance phase (p<0.05). In both step heights, injured leg reached it maximum extension peak at an earlier time. The results of this study imply that participants with ACLD make use of different 3D rotational tiobiofemoral kinematics and different GRF compared to healthy contralateral leg. These compensatory mechanisms would finally bring about different knee joint loading, which provides the potential of cartilage degeneration and early osteoarthritis.
Rehabilitation Engineering
Ziba Gandomkar; Fariba Bahrami
Volume 7, Issue 1 , June 2013, , Pages 21-37
Abstract
Changes in gait pattern are early symptoms in many disorders such as balance and control problems resulted in fall among elderlies. This paper aims at proposing a new set of features extracted from Gait Frieze Pattern (GFP) in order to classify seniors to fallers and non-fallers. For indicating the effectiveness ...
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Changes in gait pattern are early symptoms in many disorders such as balance and control problems resulted in fall among elderlies. This paper aims at proposing a new set of features extracted from Gait Frieze Pattern (GFP) in order to classify seniors to fallers and non-fallers. For indicating the effectiveness of the presented method, the algorithm is used for recognition of different type of abnormal gaits. The introduced method consists of three main steps: extracting the subject from background, generating GFP and aligning them, and building the proposed image from GFP by thresholding followed by morphological operations. For evaluation of the proposed features, video sequences are collected from 8 elderly fallers, 8 non-fallers, and 8 youth while performing standard Timed Up and Go (TUG) test. In addition to TUG test youths are asked to walk fast and pretend to walk with 6 different types of abnormalities (limping, waddling, anterior- posterior sway, lateral sway, dragging, steppage gait). For finding correct classification rate, each time one data is considered as test and others as train and label of train data with the most similarity with test one on the score of normalized cross correlation is assigned to test data. Comparing to conventional TUG test, correct classification data is improved around 20% for faller detection. In addition, correct classification rate for detecting of different abnormalities in gait is approximately 90%.