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힘 센서와 MSP430 기반 수면 중 움직임 측정 시스템 개발
김재필(Jaepil Kim),박수지(Sooji Park),신항식(Hangsik Shin) 대한전기학회 2019 전기학회논문지 Vol.68 No.12
The purpose of this study is to develop a system that can measure the movement of the human body during sleep in a way that does not constrain the body. In this study, a measurement system was implemented using a strip-type force sensor placed on a mattress, under the user"s body, and an MSP430G2553 ultra-low-power processor. The strip sensor was fabricated using Polyvinylidene fluoride film. The signal obtained from the sensor was pre-processed and amplified through the developed analog front-end, and then converted to a digital signal through the ADC of MSP430. The MSP430 uses a timer interrupt and an ADC interrupt to minimize CPU operation time for low power operation. Through the comparison with the reference instrument, it was confirmed that the developed system can track the tossing, turning and breathing signals during sleep.
이준석(Jun Seok Lee),박수지(Sooji Park),신항식(Hangsik shin) 대한전기학회 2017 전기학회논문지 Vol.66 No.11
The study aims to distinguish hemiplegic gait and normal gait using simple wearable device and classification algorithm. Thus, we developed a wearable system equipped three axis accelerometer and three axis gyroscope. The developed wearable system was verified by clinical experiment. In experiment, twenty one normal subjects and twenty one patients undergoing stroke treatment were participated. Based on the measured inertial signal, a random forest algorithm was used to classify hemiplegic gait. Four-fold cross validation was applied to ensure the reliability of the results. To select optimal attributes, we applied the forward search algorithm with 10 times of repetition, then selected five most frequently attributes were chosen as a final attribute. The results of this study showed that 95.2% of accuracy in hemiplegic gait and normal gait classification and 77.4% of accuracy in hemiplegic-side and normal gait classification.