• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.9
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• pp.1407-1412
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• 2013

The human gait pattern analysis shoes have been developed for our healthy lfe, which is largely dependent on a posture and a skeletal structure affected by daily lifestyle and gait pattern. There are generally 3 types of human gait, such as normal gait, intoeing gait, and outtoeing gait. We have analyzed one's gait pattern through walking put on the developed shoes.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.781-790
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• 2024

As modern people's interest in exercise and health increases, the demand for exercise-related information and devices is increasing, and exercising in the wrong posture can lead to body imbalance and injury. Therefore, in this study, the purpose of this study is to correct the posture for health promotion and injury prevention through the correct exercise posture of users. It was developed using Arduino Uno R3, a pressure sensor, and an acceleration sensor as the main memory device of the system. The pressure sensor was used to determine the squat posture, and the acceleration sensor was used to determine three types of gait: normal step, nasolabial step, and saddle step. Data is transmitted to a smartphone through a Bluetooth module and displayed on an app to guide the user in the correct exercise posture. The gait was determined based on the 20˚ angle at which the foot was opened, and the correct squat posture was compared with the ratio of the pressure sensor values of the forefoot and hindfoot based on the data of the skilled person. Therefore, based on an experiment with about 90% accuracy when determining gait and 95% accuracy based on a 7:3 ratio of pressure sensor values in squat posture, a system was established to guide users to exercise in the correct posture by checking in real time through a smartphone application and correcting exercise in the wrong posture.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.10 no.3
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• pp.199-206
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• 2016

Most Koreans walk having their toes in or out, because of their sedentary lifestyles. In addition, using smartphone while walking makes having a desirable walking posture even more difficult. The goal of this study is to make a simple system which easily analyze and inform any person his or her personal walking habit. To discriminate gait patterns, we developed a gait monitoring system using a 3-axis accelerometer and a foot pressure monitoring system. The developed system, with an accelerometer and a few pressure sensors, can acquire subject's foot pressure and how tilted his or her torso is. We analyzed the relationship between type of gate and sensor data using this information. As the result of analysis, we could find out that statistical parameters like standard deviation and root mean square are good for discriminating among torso postures, and k-nearest neighbor algorithm is good at clustering gait patterns. The developed system is expected to be applicable to medical or athletic fields at a low price.