웨어러블 센서를 이용한 일상생활중 머리-목 자세 측정 시스템

이재현,지영준,배지은,김하선,김영훈,Lee, Jaehyun,Chee, Youngjoon,Bae, Jieun,Kim, Haseon,Kim, Younghoon 대한의용생체공학회 2016 의공학회지 Vol.37 No.3

The neck pain is fairly common occurance. Forward head posture and text neck are poor postures which may be related with neck pain but the evidence is not enough. We developed the wearable sensor which can assess the head & neck posture in daily life. Microprocessor, Bluetooth low energy, and 3-axis accelerometer, rechargeable battery and vibratior for reminding are used to implement the wearable sensor. Real-time algorithm to parameterize the posture for one epoch is implemented which classifies the posture in the epoch into three classed; dynamic, static_good posture, and static_poor posture. Also the algorithm makes reminding to its wearer to give them the prolonged poor posture is detected. The mean error of measurement was 1.2 degree. The correlation coefficient between neck angle and craniovertebral angle was 0.9 or higher in all cases. With the pilot study on text neck syndrome was also quatified. Average of neck angle were 74.3 degree during the listening in the classroom and 57.8 degree during the smartphoning. Using the wearable sensor suggested, the poor postures of forward head posture and neck neck can be detected in real-time which can remind the wearer according to his/her setting.

근전도 트리거 손목 재활 훈련 시스템 개발

김영훈,리두이콴,지영준,안경관,황창호,Kim, Younghoon,Le, DuyKhoa,Chee, Youngjoon,Ahn, Kyoungkwan,Hwang, Changho 대한의용생체공학회 2013 의공학회지 Vol.34 No.3

This study is about the development of the wrist rehabilitation system for the patient who has limited capability of movement after stroke. Electromyography triggered training system (ETTS) can play the role between complete passive training and patient activating training system. Surface EMG was measured on pronator teres muscle and biceps brachii muscle for wrist pronation and supination. Our system detects whether the subject makes muscular effort for pronation or supination or nothing in every 50 ms. When the effort level exceeds the preset percentage of maximal voluntary contraction, the motor rotates according to the direction of the intention of the subject. EMG triggers the motor rotation for the wrist rehabilitation training until the preset angle. To evaluate its performance, the maximum voluntary contraction level was measured for 4 subjects at first. With the audio-visual instruction to rotate the wrist (pronation or supination) the subjects made effort to follow the instruction. After calculating root mean square (RMS) for 50 ms, the controller determines whether there was muscular effort to rotate while holding the motor. When there was an effort to rotate, the controller rotates the motor 0.8 degree. By comparing the RMS values from two channels of EMG, the controller determines the rotational direction. The onset delay is $0.76{\pm}0.24$ s and offset delay is $0.65{\pm}0.22$ s for pronation. For supination the onset delay is $1.24{\pm}0.41$ s and offset delay is $0.77{\pm}0.22$ s. The system responded fast enough to be used for rehabilitation training. The controller perceived the direction of rotation 100% correctly for the pronation and 97.5% correctly for supination. ETTS was developed and the fundamental functions were validated for normal subjects. The clinical validation should be done with patients for real world application. With ETTS, the subjects can train voluntarily over the limitation of the range of motion which increases the effectiveness of the rehabilitation training.

흉부압박 피드백 기능이 포함된 기본소생술 앱 개발

송영탁,김민우,김진성,오재훈,지영준,Song, Yeongtak,Kim, Minwoo,Kim, Jinsung,Oh, Jaehoon,Chee, Youngjoon 대한의용생체공학회 2014 의공학회지 Vol.35 No.6

This study is to develop a basic life support (BLS) app using the android based smartphone and to evaluate the function of the app. Suggested app contains chest compression feedback function, the map of automated external defibrillator (AED), direct emergency call and the basic knowledge of BLS. Using the accelerometer of the smartphone, we implemented a real-time algorithm that estimates the chest compression depth and rate for high quality cardiopulmonary resuscitation (CPR). The accuracy of algorithm was evaluated by manikin experiment. We made contents which were easy to learn the BLS for the layperson and implemented a function that provides the AED location information based on the user's current location. From the manikin experiment, the chest compression depth and rate were no significant differences between the manikin data and the app's feedback data (p > 0.05). Developed BLS app was uploaded on Google Play Store and it was free to download. We expected that this app is useful to learn the BLS for the layperson.

에어셀을 이용한 손목 재활훈련 장치

이영진,정유진,구교인,지영준,Lee, Youngjin,Jeong, Yujin,Koo, Kyo-In,Chee, Youngjoon 대한의용생체공학회 2015 의공학회지 Vol.36 No.2

In this paper, we propose a wrist rehabilitation training device using pneumatic inflation and deflation of air cells. By alternating inflation and deflation of upper and lower air cells, the device makes the flexional and extensional movement for wrist rehabilitation. With the angular displacement sensor, it measures the flexion-extension angle of the wrist during the training and the bending angle is used for the automatic control of the device. Using the sensor output, the regression equation was obtained to measure the bending angle of the wrist from a wrist rehabilitation training device. The measurement error of the device was evaluated by comparing the measurement output with the angle from the photograph. The measurement error of wrist bending angle between the sensor and photo was $3.2^{\circ}$ in average. With additional test and improvement, the pneumatic wrist rehabilitation training device might be used for rehabilitation training.

전극 개수에 따른 근전도 기반 휴먼-컴퓨터 인터페이스의 정확도에 대한 연구

이슬비(Seulbi Lee),지영준(Youngjoon Chee) 한국HCI학회 2015 한국HCI학회 논문지 Vol.10 No.2

NUI(Natural User Interface)는 사용자의 자연스러운 동작이나 동작 시 발생하는 생체 신호를 해석하여 기계에 명령을 내리는 것을 말한다. 물리적인 변화가 있어야 사용이 가능한 가속도 센서나 영상 기반의 NUI와는 달리 특정 동작과 관련된 근육의 표면 근전도(surface Electromyogram, sEMG)를 측정하면 실제 움직임이 발생하지 않아도(isometric contraction) 동작 의도를 예측할 수 있다. 본 연구에서는 근전도 기반으로 손목 동작 의도를 분류할때 전극 개수에 따른 정확도를 확인하고, 키보드 등에 적용 가능한 인터페이스 기술을 제안한다. 손목의 동작 중 신전(extension, up), 굴곡(flexion, down), 외전(abduction, right), 내전(adduction, left)의 네 가지 동작 의도를 분류하는 실험을 진행하였다. 50ms 간격으로 계산된 제곱평균제곱근(Root Mean Square, RMS)을 특징으로 사용하였고, 동작 의도 인식을 위해 역전파 알고리즘으로 학습한 다층 퍼셉트론 분류기를 사용하였다. 전극 쌍의 개수를 네개(91.9%), 세 개(87.0%), 두 개(78.9%)로 줄여가며 정확도를 확인했다. 전극 쌍의 개수가 네 개에서 두 개로 줄었을 때 정확도는 약 13% 감소하였다. 두 쌍의 전극만 사용하는 경우의 분류 정확도를 높이기 위하여 직전의 RMS를 특징에 추가하였다. 150 ms 이전까지의 정보를 사용하였을 때, 분류 정확도가 78.9%에서 83.6%로 4.6% 증가하였다. 전극 쌍의 개수가 감소함에 따라 정확도는 감소하였지만, 이전 데이터를 함께 사용한 경우 부분적으로 증가 시킬 수 있음을 확인하였다. NUI (Natural User Interface) system interprets the user’s natural movement or the signals from human body to the machine. sEMG (surface electromyogram) can be observed when there is any effort in muscle even without actual movement, which is impossible with camera and accelerometer based NUI system. In sEMG based movement recognition system, the minimal number of electrodes is preferred to minimize the inconvenience. We analyzed the decrease in recognition accuracy as decreasing the number of electrodes. For the four kinds of movement intention without movement, extension (up), flexion (down), abduction (right), and adduction (left), the multilayer perceptron classifier was used with the features of RMS (Root Mean Square) from sEMG. The classification accuracy was 91.9% in four channels, 87.0% in three channels, and 78.9% in two channels. To increase the accuracy in two channels of sEMG, RMSs from previous time epoch (50-200 ms) were used in addition. With the RMSs from 150 ms, the accuracy was increased from 78.9% to 83.6%. The decrease in accuracy with minimal number of electrodes could be compensated partly by utilizing more features in previous RMSs.

자동혈압계 성능평가를 위한 인체혈압 시뮬레이터 개발

도일,임현균,안봉영,지영준,이종실,오재훈,Doh, Il,Lim, Hyun Kyoon,Ahn, Bongyoung,Chee, Youngjoon,Lee, Jongshill,OH, Jae Hoon 대한의용생체공학회 2017 의공학회지 Vol.38 No.3

Blood pressure is one of the important vital signs for monitoring the medical condition of a patient. Automated NIBP(non-invasive blood pressure) monitoring devices calculate systolic and diastolic blood pressures from the oscillation in cuff pressure caused by a pulsation of an artery. To validate the NIBP devices, we developed a simulator to supply the oscillometric waveforms obtained from human subjects. The simulator provided pressure pulses to device-under-test and device readings were compared to the auscultatory references. Fully automated simulation system including OCR(optical character recognition) were developed and used for NIBP monitoring devices. The validation results using the simulator agreed well with previous clinical validation. More validation studies using the standardized oscillometric waveforms would be required for the replacement of clinical trials to validate a new automated NIBP monitoring device.

관성센서를 사용한 발의 움직임 추정용 평활기

서영수(Young Soo Suh),지영준(Youngjoon Chee) 제어로봇시스템학회 2012 제어·로봇·시스템학회 논문지 Vol.18 No.5

A foot motion is estimated using an inertial sensor unit, which is installed on a shoe. The inertial sensor unit consists of 3 axis accelerometer and 3 axis gyroscopes. Attitude and position of a foot are estimated using an inertial navigation algorithm. To increase estimation performance, a smoother is used, where the smoother employs a forward and backward filter structure. An indirect Kalman filter is used as a forward filter and backward filter. A new combining algorithm for the smoother is proposed to combine a forward indirect Kalman filter and a backward indirect Kalman filter. Through experiments, the estimation performance of the proposed smoother is verified.

디스포저블 관절경 수술기의 개발

윤재웅(Jae-Woong Youn),지영준(Youngjoon Chee),임찬양(Chanyang Lim) Korean Society for Precision Engineering 2005 한국정밀공학회지 Vol.22 No.10