재활환자 모의보행 패턴분석을 이용한 하지 편측 장애자의 정량적 재활상태 모니터링

문동준,김주영,노시철,최흥호,Moon, Dong-Jun,Kim, Ju-Young,Noh, Si-Cheol,Choi, Heung-Ho 대한의용생체공학회 2014 의공학회지 Vol.35 No.6

In this paper, to quantitatively evaluate the degree of rehabilitation for the disabled of unilateral lower extremity, we compared the EMG pattern of normal and simulated abnormal gait. The EMG signal was measured at a rate of 1 kHz on the quadriceps and biceps femoris, the pressure sensor was attached to the sole in order to distinguish the gait cycle. Integrated EMG (IEMG) was obtained by the gait cycle, and classified four patterns that were the normal gait pattern, amplitude decrease pattern, reversed pattern, and irregular pattern. For comparison of the patterns, a curve fitting was performed using the trigonometric functions. The result of curve fitting, the method using a variable A that corresponds to the amplitude of the regression curve was able to distinguish the reverse pattern and remaining pattern. The coefficient of determination ($R^2$) representing coincidence of the pattern of the regression curve and EMG was confirmed the biggest value at the normal gait. Therefore, the degree of normal gait can be confirmed using the coefficient of determination. This results show that it is possible to quantitatively confirm the degree of unilateral lower extremity disabled rehabilitation, and it will be contributed to the study of efficient rehabilitation methods by objective analysis.

Gait Pattern Generation for Robotic Gait Rehabilitation System on Treadmill

Kap-Ho Seo,Yongsik Park,Sungjo Yun,Sungho Park,Kwang-Woo Jeon,Jungsoo Jun,Dae Hee Kim 제어로봇시스템학회 2014 제어로봇시스템학회 국제학술대회 논문집 Vol.2014 No.10

Robotic gait rehabilitation devices enable efficient and convenient gait rehabilitation by mimicking the functions of physical theraphists. In manual gait rehabilitation training, physical theraphists have patients practice and memorize normal gait patterns by applying assistive torque to the patient’s joint once the patient’s gait deviates from the normal gait. Thus, one of the most important factors in robotic gait rehabilitation devices is to determine the assistive torque to the patient’s joint during rehabilitation training. In order to calculate the assistive torque, the desired gait trajectory for affected leg should be determined. This reference trajectory is obtained from his healthy leg. The obtained signal has many noisy factors. Therefore, after conditioning the signal, the suitable pattern is applied to the developed system. This procedure is called ”gait pattern generation” in this paper. It is described and discussed in detail.

보행운동 기간과 경사도에 의한 편마비 환자의 보행특성 변화

김유신(You Sin Kim),김은정(Eun Jung Kim) 한국사회체육학회 2011 한국사회체육학회지 Vol.0 No.46

The purpose of this study was to compare the effect of 14-week treadmill gait exercise on gait patterns of lower extremities in hemiplegic patients who had a stroke previously. In this study, ten subjects randomly divided into two treadmill exercise groups (i.e., either incline and decline exercise condition; five subjects for each group) and the exercise program had three stages (i.e., training, detraining, and retraining; 6, 4, and 4 weeks, respectively). To explore the changes in gait patterns, kinematic variables such as step length, stride length, time spent in stance and swing phases, total stride time, the angles of ankle joint, knee joint, and hip joint were measured. The present study showed that the gait abilities of hemiplegic patients was improved through a 14-week treadmill gait exercise and the decline treadmill exercise program had positive influences in improving gait patterns. During the detraining session, the effects of gait patterns were decreased. Therefore, the patients need a steady gait exercise program. In conclusion the decline treadmill gait exercise was better than the incline treadmill gait exercise in improving gait ability of hemiplegic patients.

Clinical Criteria to Perform the Step through Step Gait with a Cane in Chronic Stroke Patients

( Won Bok Kim ),( Jung Ho Lee ) 대한물리의학회 2014 대한물리의학회지 Vol.9 No.3

Purpose:The purpose of this study was to propose clinical criteria to differentiate patients who are able to perform the step-through-step gait pattern in chronic stroke patients. Methods:Sixty patients with chronic stroke patients participated this study. To differentiate patients who could perform the step-through-step gait pattern, age, gender, and causes of stroke were noted, a Chedoke-McMaster (CM) damage list, Fugl-Meyer (FM) assessment scales and the Berg Balance Scale (BBS) were determined. A 10 meter gait test and Timed Up and Go (TUG) test were conducted to determine the differences in gait speed and dynamic balance between patients walking with or without canes in the step-through-step gait pattern group. Results: There was no significant statistical difference in age, gender, and stroke type between all subjects. There were significant differences in the CM scale for postural and lower extremities, and FM scale for lower extremities and BBS. The dynamic balance ability and gait speed showed significant differences between the subjects in the step-through-step gait pattern with or without a cane during gait. Conclusion: CM and FM scales for the lower extremities and postural control, as well as BBS scales, can be used as criteria to differentiate patients who are able to perform the step-through-step gait pattern. These results can also be used to provide beneficial information to patients that are walking with canes.

보행 시 스마트폰 사용이 보행 패턴에 미치는 영향

전현주,이연섭 한국엔터테인먼트산업학회 2022 한국엔터테인먼트산업학회논문지 Vol.16 No.8

The purpose of this study is to study the effect of smartphone use on gait patterns while walking. The study subjects included 13 healthy adult women. The research method was studied on the effect of smartphone use on gait patterns while gait. The research procedure was designed to analyze the gait pattern by classifying it into a non-task group and a task-performing group. As a research tool, Stride Time, Stride Length, Cadence, Swing, Stance, and Double Support were measured when walking with a gait analyzer (Legsys, BioSensics, USA). Gait analysis was performed on both ankles 5 cm above the ankle. After one measurer performed each task, and after sufficient rest, the next task was performed to analyze the gait pattern. All measured data collection was processed through a computer equipped with Bluetooth. In order to analyze the group between the non-task group and the task-performing group, an independent t-test was used. The statistical significance level was set to 0.05. A significant difference was confirmed in the use of smartphone during walking compared to normal gait. These results are thought to have a negative effect on walking due to reduced attention and limited field of view due to smartphone use.

Semantic Key Pre-Distribution Protocol For Multi-Phase Wireless Sensor Networks

Carlos Ramos,Zita Maria Almeida do Vale 사단법인 인문사회과학기술융합학회 2011 예술인문사회융합멀티미디어논문지 Vol.1 No.1

Gait is a new biometric aimed to recognize a subject by the manner in which they walk. Gait has several advantages over other biometrics, most notably that it is a non-invasive and perceivable at a distance when other biometrics are obscured. We present a new area based metric, called gait masks, which provides statistical data intimately related to the gait of the subject. Early results are promising with a recognition rate of 90% on a small database of human subjects. In addition to this, we show how gait masks can also be used on subjects other than humans to provide information about the gait cycle of the subject. In this paper, we propose a novel temporal template, called Chrono-Gait Image (CGI), to describe the spatio-temporal walking pattern for human identification by gait. The CGI temporal template encodes the temporal information among gait frames via color mapping to improve the recognition performance. Our method starts with the extraction of the contour in each gait image, followed by utilizing a color mapping function to encode each of gait contour images in the same gait sequence and compositing them to a single CGI. We also obtain the CGI-based real templates by generating CGI for each period of one gait sequence and utilize contour distortion to generate the CGI-based synthetic templates. In addition to independent recognition using either of individual templates, we combine the real and synthetic temporal templates for refining the performance of human recognition. Extensive experiments on the USF HumanID database indicate that compared with the recently published gait recognition approaches, our CGI-based approach attains better performance in gait recognition with considerable robustness to gait period detection.

뇌졸중환자의 보행분석방법과 보행특성

한진태,배성수,Han, Jin-Tae,Bae, Sung-Soo 대한고유수용성신경근촉진법학회 2007 PNF and Movement Vol.5 No.1

Objective : A large proportion of stroke survivors have to deal with problems in gait. Proper evaluation of gait must be undertaken to understand the sensorimotor impairment underlying locomotor disorders post stroke. Methods : The characteristics of gait pattern with post stroke are reviewed in this paper. In particular, temporal distance parameters, kimematics, kinetics, as well as energy cost, EMG are focused. Results : The technology for gait analysis is moving rapidly. The techniques of 3D kinematic and kinetic analysis can provide a detailed biomechanical description of normal and pathological gait. This article reviews gait analysis method and characteristics of post stroke. Finally current method of gait analysis can provide further insight to understand paretic gait and therapeutic direction.

인간의 COG 궤적의 분석을 통한 5-link 이족 로봇의 보행 패턴 생성

김병현(Byounghyun Kim),한영준(Youngjoon Han),한헌수(Hernsoo Hahn) 한국정보과학회 2009 정보과학회논문지 : 소프트웨어 및 응용 Vol.36 No.2

인간이 최소 에너지를 소비하면서 자연스럽고 안정된 상태로 보행한다는 것에 착안하여, 본 논문은 인간 보행의 COG 궤적을 분석함으로써 인간형 이족로봇의 자연스러운 보행에 관한 연구를 수행한다. 이를 위해서 본 논문은 sagittal plane과 frontal plane상의 보행 영상으로부터 계측된 COG 궤적을 고려함으로써 안정적이고 에너지를 최소화하는 자연스러운 이족로봇의 보행 패턴을 생성한다. 인간과 이족로봇은 기구학적인 형태는 유사하지만 자유도에 있어 많은 차이를 보이기 때문에 추출된 인간 관절의 회전력을 이족로봇에 바로 적용할 수 없다. 본 논문에서는 인간의 보행패턴으로부터 계측된 각 관절의 회전력과 인간의 COG 궤적으로부터 계산된 ZMP을 이용하는 적응적 보행 패턴 생성 GA 알고리즘을 통해 5-link 이족로봇 모델의 보행패턴을 생성한다. 제안된 알고리즘은 인간의 각 관절의 회전력과 ZMP 궤적을 고려하기 때문에 인간과 같이 유연하고 에너지 소비를 최소화하는 인간형 이족로봇의 보행패턴을 생성한다. 본 논문은 역기구학을 이용한 일반적인 방법과 제안하는 방법에 의해 생성된 보행 패턴을 각각 5-link 이족로봇 모델에 적용하여 시각적인 측면과 에너지 효율측면에서 평가함으로써 제안하는 알고리즘의 우수성을 입증하였다. Based on the fact that a human being walks naturally and stably with consuming a minimum energy, this paper proposes a new method of generating a natural gait of 5-link biped robot like human by analyzing a COG(Center Of Gravity) trajectory of human's gait. In order to generate a natural gait pattern for 5-link biped robot, it considers the COG trajectory measured from human's gait images on the sagittal and frontal plane. Although the human and 5-link biped robot are similar in the side of the kinematical structure, numbers of their DOFs(Degree Of Freedom) are different. Therefore, torques of the human's joints cannot are applied to robot's ones directly. In this paper, the proposed method generates the gait pattern of the 5-link biped robot from the GA algorithm which utilize human's ZMP trajectory and torques of all joints. Since the gait pattern of the 5-link biped robot model is generated from human's ones, the proposed method creates the natural gait pattern of the biped robot that minimizes an energy consumption like human. In the side of visuality and energy efficiency, the superiority of the proposed method have been improved by comparative experiments with a general method that uses a inverse kinematics.

New Wearable Exoskeleton for Gait Rehabilitation Assistance Integrated with Mobility System

고창용,고주원,김형주,임도형 한국정밀공학회 2016 International Journal of Precision Engineering and Vol.17 No.7

Gait and mobility in patients with gait impairment are important in maintaining and improving their physical and psychological health and to return to society. Thus, the aims of the current study were to develop and evaluate a new wearable exoskeleton for gait rehabilitation assistance integrated with a mobility system (RehabWheel) for patients with gait impairment. A wearable exoskeleton was controlled by artificial pneumatic muscles to mimic joint movement; appropriate gait training was then undertaken. In total, 13 healthy males participated in evaluating RehabWheel by comparing joint angle kinematics and muscle activation patterns during walking over ground with RehabWheel and normal gaits. The joint angle kinematics of the hip and knee joints with RehabWheel were similar to those of normal gait despite differences in their magnitude. Additionally, muscle activations in the hip and knee joints were less during RehabWheel gait than normal gait and were associated with joint kinematics. These findings indicate that RehabWheel may have potential for incorporation into gait rehabilitative training assistance combined with a wheelchair platform for movement. This study is valuable for the initial identification of the practical feasibility of this new mobility system with both mobility and gait rehabilitation functions.

Depth video-based gait recognition for smart home using local directional pattern features and hidden Markov model

Uddin, Md. Zia,Kim, Jeong Tai,Kim, Tae-Seong SAGE Publications 2014 Indoor and Built Environment Vol.23 No.1

<P>Gait recognition at smart home is considered as a primary function of the smart system nowadays. The significance of gait recognition is high especially for the elderly as gait is one of the basic activities to promote and preserve their health. In this work, a novel method was proposed for human gait recognition by processing depth videos from a depth camera. The gait recognition method utilizes local directional patterns (LDPs) for local feature extraction from depth silhouettes and hidden Markov models (HMMs) for recognition. The LDP features were first extracted from the depth silhouettes of a human body from each frame of a video containing human gait. The dimension of the LDP features was reduced by principal component analysis. Then, each HMM was trained using the LDP features. Finally, the recognition was done with a maximum likelihood calculation of the trained HMMs of different gaits. We focused on training and recognizing two kinds of gaits here, namely, normal and abnormal. The proposed approach shows superior recognition performance over other traditional methods of gait recognition.</P>