• The Journal of Korean Physical Therapy
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• v.17 no.1
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• pp.96-107
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• 2005

Objective: The purpose of this study were to investigate the standing balance, dynamic activity in hemiplegic patients according to the types of ankle-foot orthosis(AFO) and to determine the most effective type of AFO for gait training. Method: A prospective study was performed for 16 patients with hemiplegia who was able to walk independently. Static balance and dynamic activity were compared in two condition : 1) barefoot and SPAFO, 2) barefoot and HPAFO. Static balance and dynamic activity characteristics were evaluated by Active Balance while they were standing with in two condition AFO and barefoot. Results: There were significant difference in standing balance between barefoot and wearing SPAFO and HPAFO(p<0.05). There were significant difference in dynamic activity balance between barefoot and wearing SPAFO and HPAFO(p<0.05). There were significant difference in gait speed between barefoot and wearing SPAFO and HPAFO(p<0.05). Conclusion: This study showed that wearing SPAFO and HPAFO gave fair amount of improvement to balance and gait ability of hemiplegic patients.

• International journal of advanced smart convergence
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• v.9 no.4
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• pp.139-148
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• 2020

Walking is one of the most natural and repetitive actions we do in our daily lives. However, many modern people have problems with shoulders, back and spine due to incorrect walking habits. Therefore, it is becoming important to diagnose and correct wrong walking habits, for example, in-toeing, out-toeing, etc. early, which can be a precursor to various diseases. In this study, we developed the system to diagnose and prevent incorrect gait by grasping and analyzing the angle and muscle activity of the foot according to the typical wrong gait type through MPU 6050 acceleration sensor and the surface EMG sensor. Through a smartphone, numerical and visualization screens based on walking can be used to represent the angle of the feet, real-time EMG values, and even the number of steps. The correction effect was enhanced by improving the cognitive ability through a system that allows individuals to easily diagnose gait through smart devices and improve them according to their own problems.

• The Journal of the Korea Contents Association
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• v.12 no.1
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• pp.318-328
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• 2012

The purpose of present study was to determine effects of a PNF combination pattern training on muscle activity of lower extremities and gait ability in hemiparetic subjects. Twenty chronic stroke patients participated. Participants were randomly divided into either control group and experimental group. Experimental group received PNF combination pattern training, four times per a week for six weeks and control group received general exercise training. For the lower limbs muscle activity, RMS of action potential were analyzed and gait ability tests was conducted with 10MWT, DGI and F8WT. For the significance test of control and experimental group for measuring time by exercise application method, two-way repeated measure ANOVA. As the result, muscle activity of RF(p<.05), VM, TA, LH, LG was significantly increased between measurement period(p<.001), In VM, TA, LH, LG, there were interactions each measurement time and between group. 10MWT, DGI, F8WT in gait ability was significantly improved between measurement periods(p<.001) and In 10MWT, DGI, F8W, there were interaction each measurement time and between group. In conclusion, the PNF combination pattern application will be effective strategy to increasing the muscle activity and improving gait ability in the rehabilitation of stroke patients.

• Physical Therapy Korea
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• v.13 no.2
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• pp.35-42
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• 2006

The walker provides stability for walking for people whose lower extremities are disabled. It is important to measure and determine the appropriate height of a walker to conserve energy and to improve function. The purposes of this study were to examine effects of walker height and gait velocity on triceps, latissimus dorsi muscle activation, and energy expenditure index (EEI) during ambulation with a walker. Fifteen healthy subjects participated in this study. Each subject was assigned a walker with one of three heights (high, standard, lower height) and of two gait velocities (comfortable gait velocity or fast gait velocity). Electromyographic data were collected from triceps and latissimus dorsi, and EEI was determined from each condition. Two-way repeated analysis of variance (ANOVA) was used to determine the statistical significance. Post hoc comparison was performed with the Bonferroni test. The results of this study were summarized as follows: 1. There was a significant difference in the %MVIC of triceps among different walker height factors. Post hoc comparison revealed that %MVIC of dominant triceps brachii was more significantly increased in patients who used the higher walker than those who used the lower walker (p<.05). 2. There were significant differences in the %MVIC of the latissimus dorsi among different walker height factors and gait velocity factors. Post hoc comparison revealed that the %MVIC of dominant latissimus dorsi was also more significantly increased in patients who used the higher walker than those who used the lower walker (p<.05) and in those who used the faster gait velocity than those who used the slower gait velocity (p<.05). 3. There were significant differences in the EEI among different walker height factors and gait velocity factors. Post hoc comparison revealed that the EEI was significantly increased among those who used higher and lower walkers compared with the standard walker. The EEI was also more significantly increased among those who used the fast gait velocity than those who used the slower gait velocity (p<.05). It has been concluded that increased muscle activation in triceps and latissimus dorsi was required when the walker height increased and that more energy was exp ended when the gait velocity increased. Therefore, from the findings of this study, it is recommended that walker height be adjusted according to the purposes of gait training and that healthy subjects conserve energy when ambulating with standard walkers in a comfortable gait velocity.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2627-2642
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• 2023

Parkinson's disease (PD) is a typical, chronic neurodegenerative disease involving the concentration of dopamine, which can disrupt motor activity and cause different degrees of gait disturbance relevant to PD severity in patients. As current clinical PD diagnosis is a complex, time-consuming, and challenging task that relays on physicians' subjective evaluation of visual observations, gait disturbance has been extensively explored to make automatic detection of PD diagnosis and severity rating and provides auxiliary information for physicians' decisions using gait data from various acquisition devices. Among them, wearable sensors have the advantage of flexibility since they do not limit the wearers' activity sphere in this application scenario. In this paper, an attention-based temporal network (ATN) is designed for the time series structure of gait data (vertical ground reaction force signals) from foot sensor systems, to learn the discriminative differences related to PD severity levels hidden in sequential data. The structure of the proposed method is illuminated by Transformer Network for its success in excavating temporal information, containing three modules: a preprocessing module to map intra-moment features, a feature extractor computing complicated gait characteristic of the whole signal sequence in the temporal dimension, and a classifier for the final decision-making about PD severity assessment. The experiment is conducted on the public dataset PDgait of VGRF signals to verify the proposed model's validity and show promising classification performance compared with several existing methods.

• Korean Journal of Applied Biomechanics
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• v.22 no.3
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• pp.365-371
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• 2012

We aimed to analyze the muscle activity of adolescent patients with idiopathic scoliosis during gait and develop the wearing of musculo-skeletal functional garment by applying the principle of sports taping based on the result of the analysis. We selected 20 male students between the ages of 13 and 18 and divided them into 2 groups: one group consisted of 10 patients with idiopathic scoliosis <20 degrees of Cobb's Angle: the other group had 10 normal students. Using, we measured and analyzed the muscle activity of 8 different regions: left and right latissimus dorsi, left and right thoracolumbar fascia, left and right gluteus medius, and left and right biceps femoris during gait. Our results can be summarized as follows: Firstly, in patients with idiopathic scoliosis, the gait showed a significantly low activity of the right latissimus dorsi muscle when the left foot was supported on the ground(p<.05). Secondly, in the overall gait cycle, the patients showed a higher activity of the right thoracolumbar fascia and right gluteus medius than that seen in the normal students: however, this difference was not statistically significant. Thirdly, by applying sports taping on the bisis of the results, this study developed the wearing of musculo-skeletal functional garment that could maximize the stimuli of the right latissimus dorsi and alleviate muscle contraction of the right thoracolumbar fascia and right gluteus medius, while expanding the spinal line upward and downward, by focusing on the difference between left and right muscular strength of the muscle activity of the bright latissimus dorsi. Overall, we expect that by wearing of musculo-skeletal functional garment, the muscular functions in adolescents with idiopathic scoliosis.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1778-1785
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• 2010

This paper proposes a new video-based method of analyzing human gait which is a highly variable dynamic process. It captures a human gait of varying directions as a trajectory in the phase space. The proposed method includes two options of a stochastic process model and a self-organizing feature map as the tool of feature space representation and analysis. Test results show that the model is highly intuitive and we believe it can contribute to our understanding of human activity as well as gait behavior.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.78-84
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• 2009

The purpose of this study was to compare gait patterns during pregnancy. Because of the changes in hormone levels and anatomical changes such as body mass, body-mass distribution, joint laxity, and musculotendinous strength that result from pregnancy, it was possible that there would be certain gait deviations associated with these changes. Three-dimensional gait analyses were performed from a self-selected pace, and six subjects(height : $163{\pm}5.3cm$, mass : $61.3{\pm}3.80kg$, $65.3{\pm}5.14kg$, $70.2{\pm}4.98kg$) participated in the three times(the early, middle and last years). 7 cameras(Proreflex MCU-240, Qualisys) and 2 force plates (Type 9286AA, Kistler) were used to acquire raw data. The parameters were calculated and analyzed with Visual-3D and Joint moments computed using inverse dynamics. In conclusion, pregnant women's gait patterns were changed during pregnancy period because pregnancy makes them physical changes. The main changes were joint moments and kinematic factors during pregnancy period. The pregnancy transformed normal gait pattern Into toe out position. Therefore, exercise programs to improve muscle activity were necessary where joint moments were small. The development of simulator should be studied for pregnant women's tailored shoes and accessories in future.

• Physical Therapy Korea
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• v.22 no.2
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• pp.30-40
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• 2015

Robot-assisted rehabilitation therapy has been used to increase physical function in post-stroke patients. The aim of this meta-analysis was to identify whether robot-assisted gait training can improve patients' functional abilities. A comprehensive search was performed of PubMed, Cochrane Central Register of Controlled Trials (CENTRAL), Physiotherapy Evidence Database (PEDro), Academic Search Premier (ASP), ScienceDirect, Korean Studies Information Service System (KISS), Research Information Sharing Service (RISS), Korea National Library, and the Korean Medical Database up to April, 2014. Fifteen eligible studies researched the effects of robot-assisted gait training to a control group. All outcome measures were classified by International Classification of Functioning, Disability, and Health (ICF) domains (body function and structures, activity, and participation) and were pooled for calculating the effect size. The overall effect size of the robot-assisted gait training was .356 [95% confidence interval (CI): .186~.526]. When the effect was compared by the type of electromechanical robot, Gait Trainer (GT) (.471, 95% CI: .320~.621) showed more effective than Lokomat (.169, 95% CI: .063~.275). In addition, acute stroke patients showed more improvement than others. Although robot-assisted gait training may improve function, but there is no scientific evidence about the appropriate treatment time for one session or the appropriate duration of treatment. Additional researchers are needed to include more well-designed trials in order to resolve these uncertainties.