• Physical Therapy Rehabilitation Science
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• v.2 no.1
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• pp.39-43
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• 2013

Objective: The objective of this study is to investigate the effect of treadmill gait trainig on dynamic balance and gait functions in stroke patients. Design: Randomized, double-blind, controlled pilot study. Methods: Four subjects following first stroke participated in this study. They were divided randomly into the treadmill gait trainig group (TM group) (n=2) and the control group (n=2). Subjects in both groups received general training five times per week. Subjects in the TM group practiced an additional treadmill gait trainig program that consisted of 60 minutes, three times per week, during a period of four weeks. Timed up and go test (dynamic balance) and the GAITRite test (gait function) were evaluated before and after the intervention. Results: In dynamic balance (timed up and go test), the TM group (-14.235 sec) showed a greater decrease than the control group (-13.585 sec). In gait functions, the TM group showed a greater increase in gait speed (12.8 cm/s vs. 10.15 cm/s), step-length (5.825 cm vs. 3.735 cm), and stride-length (5.005 cm vs. 1.55 cm) than the control group. Conclusions: The treadmill gait trainig improved dynamic balance and gait functions. Further research is needed in order to confirm the generalization of these findings and to identify which stroke patients might benefit from treadmill gait trainig.

• Journal of the Korean Society of Physical Medicine
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• v.16 no.1
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• pp.17-22
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• 2021

PURPOSE: This study examined the correlations between gait, static balance, and pelvic inclination in patients with chronic stroke. METHODS: Twenty-two chronic stroke patients were included in this study. The subjects participated in gait, static balance, and pelvic inclination tests. In the gait measurement, the cadence and gait velocity were measured, and the average of three trials was calculated and recorded. The static balance was measured using a force platform. The data was captured for ten seconds, and five successful trials were recorded. Pelvic inclination in the sagittal plane was measured using a palpation meter. For data processing, a KolmogorovSmirnov test was used to determine the type of distribution for all variables. Pearson's correlation coefficient was used for correlation analysis. The correlations among the gait, static balance, and pelvic inclination was calculated. The level of significance was .05. RESULTS: Significant negative correlations were observed between the gait variables (cadence, velocity) and static balance variables (COP path length, COP average velocity, and 95% confidence ellipse area) (p < .05). On the other hand, there was no significant correlation between pelvic inclination and gait or between the pelvic inclination and static balance variables. CONCLUSION: Significant correlations were observed between the gait function and static balance. On the other hand, there were no significant correlations between the pelvic inclination and gait and static balance. These results suggest that the pelvic inclination is not an important consideration for increasing the gait function and static balance.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.674-682
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• 2009

The purpose of this study was to investigate the effect of aquatic gait training on plantar foot pressure, foot kinesiology and gait speed in right hemiplegic patients. The subject were 20 stroke patients who elapsed from 12 month to 24 month after stroke(aquatic gait training group(n=10), land gait training group(n=10)). This study measured plantar foot pressure, toe out angle, subtalar joint angle, gait speed from data of gate on 2m long measuring apparatus for RS-scan system(RS scan Ltd. German). This experiment performed in twice, before and after the aquatic gait training and land gait training. Collected data were statistically analyzed by SPSS Ver. 12.0 using descriptive statistics, paired t-test. Aquatic gait training group had more variety pressure area on their foot such as T1(Toe 1), HM(Heel medial), and HL(Heel lateral). But motion of subtalar joint flexibility and toe out angle decreased considerably and gate speed also increased. According to the result, aquatic gait training is considered as more effective way in foot stability and normal gait pattern than land gait training.

• Journal of Biomedical Engineering Research
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• v.28 no.2
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• pp.218-228
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• 2007

Modem concepts of gait rehabilitation after stroke favor a task-specific repetitive approach. In practice, the required physical effort of the therapists limits the realization of this approach. Therefore, a mechanized gait trainer enabling nonambulatory patients to have the repetitive practice of a gait-like movement without overstraining therapists was constructed. In this study, we developed an active gait training system for patients with gait disorder. This system provides joint movements to patients who cannot carry out an independent gait. It provides a normal stance-swing ratio of 60:40 using an eccentric configuration of two gears. Joint motions of the knee and the ankle were evaluated with using the 3D motion analysis system and compared with the results from the multi-body dynamics simulation. In addition, clinical investigations were also performed for low stroke patients during the 6-week gait training. Results from the dynamics simulation showed that joint movements of the knee and the ankle were affected by the gear size, the step length and the length of the foot plate, except the radius of curvature of the foot guide plate. Also, the 6-week gait training revealed relevant improvements of the gait ability in all low subjects. Functional ambulation category levels of subjects after training were 2 in three patients and 1 in a patient. The developed active gait trainer seems feasible as an adjunctive tool in gait rehabilitation after stroke.

• Physical Therapy Rehabilitation Science
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• v.4 no.2
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• pp.94-102
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• 2015

Objective: The purpose of this study is to investigate the effect of treadmill gait training with patellar taping on gait abilities in chronic stroke patients. Design: Randomized controlled trial. Methods: Thirty chronic stroke patients who have been diagnosed at least six months or before were recruited in Gyeongin Rehabilitation Center Hospital, located in Incheon. Patients who were enrolled in this study were randomized to experimental group (n=15) or control group (n=15). Treadmill with patella taping training group patients were applied with patellar taping when they were being trained on a treadmill. Control group patients were being trained on a treadmill without any kind of taping. Gait parameters were measured with a GAITRite$^{(R)}$ system which evaluated gait performances. Gait trainings were done for 30 min/day, 5 days/week, for 4 weeks. Results: After treadmill training, treadmill with patella taping training group showed a significant improvement in gait abilities, including velocity, cadence, paretic and non-paretic step length, and double support period (p<0.05). However, in general treadmill group, there were no significant differences in gait parameters except velocity and cadence. There was a significant difference in gait performance in the experimental group compared with the control group, except for the gait symmetry ratio (p<0.05). Conclusions: According to this result of this study, it seems that application of patellar taping in treadmill gait training for chronic stroke patients significantly improved gait abilities of these patients. Also, we can conclude that patella taping is thought to be useful in real clinical settings where there are many chronic patients who are in need of improvement in their gait abilities.

• PNF and Movement
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• v.18 no.2
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• pp.287-296
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• 2020

Purpose: The study aims were to develop a wearable inertial sensor-based gait analysis device that uses machine learning algorithms, and to validate this novel device using temporal gait parameters. Methods: Thirty-four healthy young participants (22 male, 12 female, aged 25.76 years) with no musculoskeletal disorders were asked to walk at three different speeds. As they walked, data were simultaneously collected by a motion capture system and inertial measurement units (Reseed®). The data were sent to a machine learning algorithm adapted to the wearable inertial sensor-based gait analysis device. The validity of the newly developed instrument was assessed by comparing it to data from the motion capture system. Results: At normal speeds, intra-class correlation coefficients (ICC) for the temporal gait parameters were excellent (ICC [2, 1], 0.99~0.99), and coefficient of variation (CV) error values were insignificant for all gait parameters (0.31~1.08%). At slow speeds, ICCs for the temporal gait parameters were excellent (ICC [2, 1], 0.98~0.99), and CV error values were very small for all gait parameters (0.33~1.24%). At the fastest speeds, ICCs for temporal gait parameters were excellent (ICC [2, 1], 0.86~0.99) but less impressive than for the other speeds. CV error values were small for all gait parameters (0.17~5.58%). Conclusion: These results confirm that both the wearable inertial sensor-based gait analysis device and the machine learning algorithms have strong concurrent validity for temporal variables. On that basis, this novel wearable device is likely to prove useful for establishing temporal gait parameters while assessing gait.

• Physical Therapy Rehabilitation Science
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• v.3 no.1
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• pp.55-62
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• 2014

Objective: To study the effects of gait training with additional weight and gait training with non-additional weight on balance ability and gait ability in patients with chronic stroke through comparative analysis. Design: Randomized controlled trials. Methods: The subjects were divided randomly into two groups: additional weight group (AWG, n=12), and non-additional weight group (NAWG, n=10). Both groups received general physical therapy for 30 min in 1 session, 5 sessions per week during 6 months. The AWG practiced gait training with additional weight of 0.1 and 0.5 kg for 20 min a day, 3 days per week for 6 months and the NAWG practiced gait training with non-additional weight for 20 min a day, 3 days per week for 6 months. Patients in both groups were instructed to walk as fast as they could along a 35 m long track (straight for 20 m and curved for 15 m). Patients walked with their hemiplegic side on the inside of the track while a physical therapist followed along to instruct patients to maintain a straight posture. Balance ability was tested with the Functional Reach Test, the Timed Up and Go test, and the Berg Balance Scale, and gait ability was tested with GAITRite. The results of balance and gait ability were analyzed before and after interventions. Results: A significant increase in FRT, TUG, BBS was seen in both groups after intervention (p<0.05). A significant increase in gait ability was seen in the AWG after intervention (p<0.05). For balance and gait ability, the results from the AWG was significantly improved compared with the NAWG (p<0.05). Conclusions: Gait training with additional weight improves balance ability and gait ability in stroke patients, this gait training method is effective and suitable for stroke patients to increase the ability of functional performance.

• PNF and Movement
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• v.19 no.3
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• pp.435-440
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• 2021

Purpose: The purpose of this study is to investigate the effects of older adult's head-turn gait on gait parameters by comparing with head oriented forward gait and to provide criteria for their risk of falling compared to young adult. Methods: The subjects were 19 young adults in their 20s and 18 older adults in their 60s or above residing in Daegu or Gyeongsangbuk-do. To evaluate their gait parameters, spatiotemporal gait parameters were measured using a gait analysis tool (Legsys, BioSensics, USA) under two conditions: 1) walking while keeping one's eyes forward and 2) walking while turning the head. The measurement for each test was performed after one practice session, and the mean value of three measurements was analyzed. The collected data were statistically processed using a two-way analysis of variance (ANOVA) to compare any differences in gait parameters between the two groups under the two conditions. The statistical significance level was set at α=0.05. Results: According to the comparison of gait parameters in young adult and older adult between the head oriented forward gait and head-turn gait, statistically significant differences were observed in two parameters: stride length according to the height ratio and stride speed obtained by dividing the stride length according to the height ratio by time (p<0.05). Conclusion: The results of this study indicate that the head-turn gait causes greater differences in stride length and speed among older adult than in young adult and therefore can act as a cause of falling.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.644-649
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• 2012

This paper proposes the gait phase classifier using backpropagation neural networks method which uses the angle of lower body's joints and ground reaction force as input signals. The classification of a gait phase is useful to understand the gait characteristics of pathologic gait and to control the gait rehabilitation systems. The classifier categorizes a gait cycle as 7 phases which are commonly used to classify the sub-phases of the gait in the literature. We verify the efficiency of the proposed method through experiments.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.927-939
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• 2020

Gait recognition can identify people's identity from a long distance, which is very important for improving the intelligence of the monitoring system. Among many human features, gait features have the advantages of being remotely available, robust, and secure. Traditional gait feature extraction, affected by the development of behavior recognition, can only rely on manual feature extraction, which cannot meet the needs of fine gait recognition. The emergence of deep convolutional neural networks has made researchers get rid of complex feature design engineering, and can automatically learn available features through data, which has been widely used. In this paper,conduct feature metric learning in the three-dimensional space by combining the three-dimensional convolution features of the gait sequence and the Siamese structure. This method can capture the information of spatial dimension and time dimension from the continuous periodic gait sequence, and further improve the accuracy and practicability of gait recognition.