• 전기학회논문지
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• 제66권12호
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• pp.1810-1814
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• 2017

This paper develops an approach to the algorithm of Gait pattern Analysis and step measurement with Multi-Pressure Sensors. The process of gait consists of 8 steps including stance and swing phase. As 3 parts of foot is supporting most of human weight, multiple pressure sensors are attached on the parts of foot: forefoot, big toe, heel. As 3 parts of foot is supporting most of human weight, multiple pressure sensors are attached on the parts of foot: forefoot, big toe, heel. normal gait proceed from heel, forefoot and big toe over time. While normal gait proceeds, values of heel, forefoot and big toe can be changed over time. So Each values of pressure sensors over time could discriminate whether it is normal or abnormal gait. Measuring Device consists of non-inverting amplifiers and low pass filter. Through timetable of values, normal gait pattern can be analyzed, because of supported weight of foot. Also, the peak value of pressure can judge whether it is walking or running. While people are running, insole of shoes is floating in the air on moment. Using this algorithm, gait analysis and step count can be measured.

• 한국정밀공학회지
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• 제32권12호
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• pp.1065-1072
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• 2015

This paper is about the development of an insole sensor system that can determine the model of an exoskeleton robot for lower limb that is a multi-degree of freedom system. First, the study analyzed the kinematic model of an exoskeleton robot for the lower limb that changes according to the gait phase detection of a human. Based on the ground reaction force (GRF), which is generated when walking, to proceed with insole sensor development, the sensing type, location, and the number of sensors were selected. The center of pressure (COP) of the human foot was understood first, prior to the development of algorithm. Using the COP, an algorithm was developed that is capable of detecting the gait phase with small number of sensors. An experiment at 3 km/h speed was conducted on the developed sensor system to evaluate the developed insole sensor system and the gait phase detection algorithm.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 춘계학술대회논문집
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• pp.882-887
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• 2003

This paper presented a design and control of a new RGO(reciprocating gait orthosis)and its simulation. The new RGO was distinguished from the other one by which had a very light-weight and a new RGO(reciprocating gait orthosis) system. The vibration evaluation of the hip joint system on the new RGO(reciprocating gait orthosis)was used to access by the 3-axis accelerometer with a low frequency vibration of less than 30 ㎐. The gait of the new RGO depended on the constrains of mechanical kinematics and the initial posture. The stability of dynamic walking was investigated by analyzing the ZMP (zero moment point) of the new RGO. It was designed according to the human wear type and was able to accomodate itself to the environments of S.C.I. Patients. The joints of each leg were adopted with a good kinematic characteristics. To analyse joint kinematic properties, we made the hip joint system of FEM and the hip joint system by 1-axis and 3-axis Accelerometers.

• 대한임베디드공학회논문지
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• 제18권2호
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2690-2701
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• 2013

Humans are able to recognize small number of people they know well by the way they walk. This ability represents basic motivation for using human gait as the means for biometric identification. Such biometric can be captured at public places from a distance without subject's collaboration, awareness or even consent. Although current approaches give encouraging results, we are still far from effective use in practical applications. In general, methods set various constraints to circumvent the influence factors like changes of view, walking speed, capture environment, clothing, footwear, object carrying, that have negative impact on recognition results. In this paper we investigate the influence of walking speed variation to different visual based gait recognition approaches and propose normalization based on geometric transformations, which mitigates its influence on recognition results. With the evaluation on MoBo gait dataset we demonstrate the benefits of using such normalization in combination with different types of gait recognition approaches.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.398-402
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• 1996

This paper addresses the design and the gait control of quadruped walking robot. First, we concern the mechanical and electronical(control system) hardware of walking robot, and the second is the results of experiments. The walking robot is the most suitable form to substitute fot human being. So walking robot is worthy of research. The quadruped walking robot and control system is the simplest type of walking robot, therefore we designed a small seale robot for realization of static gait. The robot is designed commpactly and its legs are constructed parallel link type and able to move freely in space. Control system consists of one upper level controller and four lower level controllers. The upper level controller plans the walking path and commands the low level controllers to follow the planned path. The main function of low level cotrollers is control of motors. Total number of motors is twealve and they operate four legs. And robot is ordered to walk and realize static wave gait.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권2호
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• pp.124-132
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• 2013

This study investigated the feasibility of gait recognition using points on the body in three-dimensional (3D) space based on comparisons of four different feature vectors. To obtain the point trajectories on the body in 3D, gait motion data were captured from 10 participants using a 3D motion capture system, and four shoes with different heel heights were used to study the effects of heel height on gait recognition. Finally, the recognition rates were compared using four methods and different heel heights.

• 한국산업융합학회 논문집
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• 제22권4호
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• pp.459-465
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• 2019

There is an increasing interest in health and research on methods for measuring human body information. The importance of continuously observing information such as the step change and the walking speed is increasing. At a person's gait, information about the disease and the currently weakened area can be known. In this paper, gait is measured using wearable walking module built in shoes. We want to make continuous measurement possible by simplifying gait measurement method. This module is designed to receive information of gyro sensor and acceleration sensor. The designed module is capable of WiFi communication and the collected walking information is stored in the server. The information stored in the server is corrected by integrating the acceleration sensor and the gyro sensor value. A band-pass filter was used to reduce the error. This data is categorized by the Gait Finder into walking and waiting states. When walking, each step is divided and stored separately for analysis.

• PNF and Movement
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• 제16권2호
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• pp.179-185
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• 2018

Purpose: This study aimed to analyze the visual and spatial elements of the gait of a stroke patient who had diverse ankle weight loads applied, according to weight changes. Methods: The subject was a 57-year-old stroke patient diagnosed and hospitalized with a left intracerebral hemorrhage. A weight equivalent to 0%, 1%, and 2% of his body weight was applied to the area 5cm upward from the ankle using a Velcro strap. He was then trained on a treadmill, receiving a six-minute walk test to evaluate his gait ability. A gait analyzer was used to collect visual and spatial elements, such as gait distance, gait velocity, cadence, step length, stride length, and swing phase, according to a weight load equivalent to 0%, 1%, and 2% of his body weight. Results: According to the results of applying 0%, 1%, and 2% of his body weight on the ankle, except for gait velocity, his gait distance, cadence, step length, stride length, and swing phase were higher when 1% of his body weight was applied compared to 0% or 2% of his body weight. Conclusion: Applying a weight equivalent to 1% of the body weight to the ankle positively affected the visual and spatial element of the gait and heightened the efficiency of exercise during treadmill training, a gait-training tool generally used for stroke patients. However, the result is difficult to generalize because the number of subjects was small with only one subject.

• Journal of Information Processing Systems
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• 제14권4호
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• pp.892-903
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• 2018

The paper proposes a novel gait recognition algorithm based on feature fusion of gait energy image (GEI) dynamic region and Gabor, which consists of four steps. First, the gait contour images are extracted through the object detection, binarization and morphological process. Secondly, features of GEI at different angles and Gabor features with multiple orientations are extracted from the dynamic part of GEI, respectively. Then averaging method is adopted to fuse features of GEI dynamic region with features of Gabor wavelets on feature layer and the feature space dimension is reduced by an improved Kernel Principal Component Analysis (KPCA). Finally, the vectors of feature fusion are input into the support vector machine (SVM) based on multi classification to realize the classification and recognition of gait. The primary contributions of the paper are: a novel gait recognition algorithm based on based on feature fusion of GEI and Gabor is proposed; an improved KPCA method is used to reduce the feature matrix dimension; a SVM is employed to identify the gait sequences. The experimental results suggest that the proposed algorithm yields over 90% of correct classification rate, which testify that the method can identify better different human gait and get better recognized effect than other existing algorithms.