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투입구 높이 및 내부 드럼 깊이를 고려한 펄세이터 세탁기 사용시 평균신장 사용자의 관절 토크 및 근력에 미치는 영향
김성국,조영근,이남기,유승현,임도형,김한성,고창용,Kim, Seong Guk,Cho, Young Kuen,Lee, Nam Gi,You, Joshua Sung Hyun,Lim, Dohyung,Kim, Han Sung,Ko, Chang-Yong 대한의용생체공학회 2012 의공학회지 Vol.33 No.4
Many studies have reported that housework done using household appliances may affect biomechanical characteristics of the musculoskeletal system. The purpose of this study was to investigate the effects of housework done using a pulsator washing machine on joints and muscles. We calculated joint torques and muscle strengths on the basis of an experimental/virtual three-dimensional motion analysis for six healthy females using the pulsator washing machine at different heights (H) and depths (D) of the inside drum (H (mm){\times}D (mm), Trial1: $962.5{\times}609.4$, Trial2: $962.5{\times}624.4$, Trial3: $982.5{\times}644.4$, Trial4: $995.5{\times}642.4$, Trial5: $1015.5{\times}677.4$). The joint torques and muscle strengths tended to be considerably different during torso flexion in the sagittal plane for all the trials. The maximum joint torques for the thoracic vertebra, left ankle, and right shoulder measured in Trial4 were significantly higher than those measured in the other trials (p < 0.05); in addition, those for the thoracic vertebra and both ankles measured in Trial5 were significantly higher than those measured in the other trials (p < 0.05). The maximum muscle strengths for the left trapezius muscle and both tibialis anterior muscles measured in Trial5 were significantly higher than those measured in the other trials (p < 0.05). These results indicate that housework done using a pulsator washing machine may affect joint torques and muscle strengths, and these effects are dependent on the height and/or depth of the inside drum of the pulsator washing machine.
뇌졸중으로 인한 편마비 환자의 보행평가를 위한 체중심 가속도센서 기반의 새로운 보 검출 알고리즘 개발
이효기,황성재,조성필,이동률,유승현,이경중,김영호,정하중,Lee, Hyo-Ki,Hwang, Sung-Jae,Cho, Sung-Pil,Lee, Dong-Ryul,You, Sung-Hyun,Lee, Kyoung-Joung,Kim, Young-Ho,Chung, Ha-Joong 대한의용생체공학회 2009 의공학회지 Vol.30 No.3
In this study, we have developed a novel step detection algorithm for gait evaluation of patients with hemiplegia based on trunk accelerometry device. For this, we have used a bandpass filter and a least square acceleration (LSA) filter which is characterized by emphasizing the peak or valley point of the acceleration signals for each 3-axis accelerometer signals. To evaluate the algorithm, the detected steps by developed algorithm and real steps by the motion analysis system were compared. As a result, we could obtain the sensitivity of 96.44%, the specificity of 99.94% and the accuracy of 99.90% for the patients' data sets and the sensitivity of 100%, the specificity of 99.93% and the accuracy of 99.93% for the normal data sets. In conclusion, the developed algorithm is useful for the step detection for patients with hemiplegia as well as normal subjects.