• 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.

• Journal of the Ergonomics Society of Korea
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• v.35 no.1
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• pp.39-52
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• 2016

Objective: This paper investigates gait changes according to different heel heights and speeds, and the interaction between the effects of the heel height and the speed during walking on stride parameters and joint angles. Furthermore, the relationship among heel height, speed and gait variables is investigated using linear regression. Background: Gait changes by heel height or speed have been studied respectively, but has not been reported whether there is an interaction effect between heel height and speed. It would be necessary to understand how gait changes when a person wears heels in different heights at various speeds, for example, high-heeled walking at fast speed, since it may cause unusual gait patterns and musculoskeletal disorders. Method: Ten females were asked to walk at five fixed cadences (94, 106, 118, 130 and 142 steps/min.) wearing three shoes with different heel heights (1, 5.4 and 9.8cm). Nineteen gait variables were analyzed for stride parameters and joint angles using two-way repeated measure analysis of variance and regression analysis. Results: Both heel height and speed affect movement of ankle, knee, spine and elbow joint, as well as stride length and Double/Single support time ratio. However, there is no significant interaction effect between heel height and speed. The regression result shows linear relationships of gait variables with heel height and speed. Conclusion: Heel height and speed independently affect stride parameters and joint angles without a significant interaction, so the gait variables are linearly amplified or diminished by the two factors. Application: Walking in high heels at fast speed should be careful for musculoskeletal disorders, since the amplified movement of knee and spine joint can lead to increased moment. Also, the result might give insight for animators or engineers to generate walking motion with high heels at various speeds.

• The Journal of the Society of Stroke on Korean Medicine
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• v.14 no.1
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• pp.90-101
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• 2013

■ Objectives The goal of this study was to observe the gait patterns from a patient with Parkinson disease under three different walking speeds. ■ Methods The patient walked on a treadmill and we measured gait parameters using a treadmill gait analysis system for 2 minutes. The Parkinson patients walked under three different conditions, first, at the preferred walking speed, second, at slower speed than the preferred walking speed, and, third, at faster speed than the preferred walking speed. ■ Results In terms of temporal gait parameters, as speed of treadmill increased, stance phase and total double support decreased, and swing phase increased. In terms of spatial parameters, as speed of treadmill increased, step and stride length increased. In terms of kinetic parameters, max pressure increased as speed of treadmill increased. ■ Conclusion According to different walking speeds, some gait parameters of spatiotemporal and kinetic was changed.

• Korean Journal of Applied Biomechanics
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• v.25 no.1
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• pp.123-130
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• 2015

Purpose : The purpose of this study was to investigate the reliability of 3D-inertia measurement unit (IMU) based shoes in gait analysis. This was done with respect to the results of the optical motion capturing system and to collect reference gait data of healthy subjects with this device. Methods : The Smart Balance$^{(R)}$ system of 3D-IMU based shoes and Osprey$^{(R)}$ motion capturing cameras were used to collect motion data simultaneously. Forty four healthy subjects consisting of individuals in 20s (N=20), 40s (N=13), and 60s (N=11) participated in this study voluntarily. They performed natural walking on a treadmill for one minute at 4 different target speeds (3, 4, 5, 6 km/h), respectively. Results : Cadence (ICC=.998), step length (ICC=.970), stance phase (ICC=.845), and double-support phase (ICC=.684) from 3D-IMU based shoes were in agreement with results of optical motion system. Gait data of healthy subjects according to different treadmill speeds and ages were matched to previous literature showing increased cadence and reduced step length for elderly subjects. Conclusion : Conclusively, 3D-IMU based shoes in gait analysis were a satisfactory alternative option in measuring linear gait parameters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.635-636
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• 2009

• Physical Therapy Korea
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• v.30 no.4
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• pp.268-274
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• 2023

Background: Ankle sprains occur frequently among humans who undertake various body movements. Diverse walking environments and dual tasks, that can affect ankle sprains, have been studied. However, there is a lack of research on inter-trial variability according to the changes in gait speed. Objects: The purpose of this study was to compare the adaptive ability of walking between the subjects with chronic ankle instability and healthy adults while performing a walking task with different walking speeds. Methods: In this study, 24 people in the chronic ankle instability group and 24 people in the healthy ankle group were selected as subjects. The length of the pre-measurement and the actual walking measurement were both set to 4.6 m. Once the subjects entered the measurement section, they changed their gait speed according to the randomly assigned speed change. Gait was measured twice and the average value was used for the analysis. Results: The coefficient of variation (CV) of cycle time in subjects with chronic ankle instability showed a significant difference in all cases except when the subjects changed their speed from preferred to slow and from slow to preferred. The CV of step length demonstrated a significant difference in all cases except for the change from slow to preferred and from preferred to fast. The cycle time and step length differential showed a significant difference only when the subjects changed the speed from slow to fast. Conclusion: The subjects with chronic ankle instability were found to have significantly reduced walking adaptability while performing inter-trial variability tasks with different gait speeds compared to healthy subjects.

• Journal of Biomedical Engineering Research
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• v.30 no.6
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• pp.516-520
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• 2009

The purpose of this study is to determine optimal filtering condition and threshold for the detection of gait-cycles for various walkway slopes as well as gait velocities. Ten young healthy subjects with accelerometer system on thigh and ankle walked on a treadmill at 9 conditions (three speeds and three slopes) for 5 minutes. Two direction signals, i.e. anterior-posterior (AP) and superior-inferior (SI) directions, of each sensor (four sensor orientations) were used to detect specific events of gait cycle. Variation of the threshold (from -1G to 1G) and lowpass cutoff frequency (fc) were applied to the event detection and their performance was evaluated according to the error index (EI), which was defined as the combination of the accuracy and false positive rate. Optimal fc and threshold were determined for each slope in terms of the EI. The optimal fc, threshold and their corresponding EI depended much on the walkway slope so that their coefficients of variation (CV) ranged 19~120%. When all data for 3 slopes were used in the identification of optimal conditions for each sensor, the best error indices for all sensor orientations were comparable ranging 1.43~1.76%, but the optimal fc and threshold depended much on the sensor position. The result indicates that the gait-cycle detection robust to walkway slope is possible by threshold method with well-defined filtering condition and threshold.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.41-50
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• 2020

The consequences of wearing high heels can be different according to the heel height, gait speed, shoe design, heel base area, and shoe size. This study aimed to focus on the knee extension and flexion range of motion (ROM) during gait, which were challenged by wearing five different shoe heel types and two different self-selected gait speeds (comfortable and fast) as experimental conditions. Measurement standards of knee extension and flexion ROM were individually calibrated at the time of heel strike, mid-stance, toe-off, and stance phase based on the 2-minute video recordings of each gait condition. Seven healthy young women (20.7 ± 0.8 years) participated and they were asked to walk on a treadmill wearing the five given shoes at a self-selected comfortable speed (average of 2.4 ± 0.3 km/h) and a fast speed (average of 5.1 ± 0.2 km/h) in a random order. All of the shoes were in size 23.5 cm. Three of the given shoes were 9.0 cm in height, the other two were flat shoes and sneakers. A motion capture software (Kinovea 0.8.27) was used to measure the kinematic data; changes in the knee angles during each gait. During fast speed gait, the knee extension angles at heel strike and mid-stance were significantly decreased in all of the 3 high heels (p<0.05). The results revealed that fast gait speed causes knee flexion angle to significantly increase at toe-off in all five types of shoes. However, there was a significant difference in both the knee flexion and extension angles when the gait in stiletto heels and flat shoes were compared in fast gait condition (p<0.05). This showed that walking fast in high heels leads to abnormal knee ROM and thus can cause damages to the knee joints. The findings in this preliminary study can be a basis for future studies on the kinematic changes in the lower extremity during gait and for the analysis of causes and preventive methods for musculoskeletal injuries related to wearing high heels.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.3
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• pp.19-25
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• 2018

PURPOSE: Most gait assessment tools are expensive and require controlled laboratory environments. Tri-axial accelerometers have been used in gait analysis as an alternative to laboratory assessments. Many smartphones have added an accelerometer, making it possible to assess spatio-temporal gait parameters. This study was conducted to confirm the reliability and validity of a smartphone-based accelerometer at quantifying spatio-temporal gait parameters of stroke patients when attached to the body. METHODS: We measured gait parameters using a smartphone accelerometer and gait parameters through the GAITRite analysis system and the reliability and validity of the smartphone-based accelerometer for quantifying spatio-temporal gait parameters for stroke patients were then evaluated. Thirty stroke patients were asked to walk at self-selected comfortable speeds over a 10 m walkway, during which time gait velocity, cadence and step length were computed from smartphone-based accelerometers and validated with a GAITRite analysis system. RESULTS: Smartphone data was found to have excellent reliability ($ICC2,1{\geq}.98$) for measuring the tested parameters, with a high correlation being observed between smartphone-based gait parameters and GAITRite analysis system-based gait parameters (r = .99, .97, .41 for gait velocity, cadence, step length, respectively). CONCLUSION: The results suggest that specific opportunities exist for smartphone-based gait assessment as an alternative to conventional gait assessment. Moreover, smartphone-based gait assessment can provide objective information about changes in the spatio-temporal gait parameters of stroke subjects.

• Korean Journal of Applied Biomechanics
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• v.12 no.1
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• pp.155-171
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• 2002

The purpose of this study was to provide basic data for a form of gait by comparing and analyzing gait motions on different grades and speeds. In order to accomplish the purpose, 6 university students, whose ages between 20 - 25, were selected. They have gaited on 3Km/h, 4Km/h, 5Km/h of speed and 4 video cameras were used to film them. The speed of filming was 60 frame / seconds. The special variations of kinematics in gait were fixed with ankle joint angle, knee joint angle, hip joint angle, ankle angular velocity, knee angular velocity and hip angular velocity. In this study, the SPSS 10.0 for windows statistical package was used to operate on significant level of .05 for statistical management. From the result of this study, we have succeeded to obtain following conclusions; 1. As the speed increased, the value of ankle joint angle increased. Also the value of ankle joint angle was larger on decline than on incline. 2. As the speed increased, the value of knee joint angle was increased. 3. As the speed increased, the value of hip joint angle was decreased. 4. As the speed increased, the value of ankle angular velocity increased. And the value of ankle angular velocity became higher on decline than on incline. 5. The value of knee angular velocity showed higher on decline than on incline. 6. As the speed increased, the value of hip angular velocity was increased. Also the value of hip angular velocity became higher on incline than on decline.