Journal of Life Support Engineering
Online ISSN : 1884-5827
Print ISSN : 1341-9455
ISSN-L : 1341-9455
Volume 33, Issue 2
Displaying 1-4 of 4 articles from this issue
Preface
Research Papers
  • Aoi Fukaya, Yasuyuki Shiraishi, Akihiro Yamada, Genta Sahara, Yusuke I ...
    2021 Volume 33 Issue 2 Pages 52-58
    Published: June 30, 2021
    Released on J-STAGE: July 04, 2022
    JOURNAL FREE ACCESS

    Roller pumps are widely used as one of the cardiopulmonary bypasses during open-heart surgery. Hemolysis may cause acute kidney injury due to the changes in the tubing gap by the occlusion of roller pumps. In this study, we achieved the 3-D evaluation of the roller pump tubing gap for the first time by our originally developed visualization analysis. We examined the leak rate and the hemolysis under the 240-min circulatory support condition in a mock flow tester, and compared the tubing gap dimensions. As a result, the primary leak rate around 0.8 mL/min against 1 mH2O afterload significantly decreased after 60-min circulation, and there was no leak rate detected for 10 minutes measurement afterwards. The 3-D tubing gaps indicated that the subsidiary opening width at the short-axis edge decreased by more flattening shapes. Moreover, plasma free hemoglobin levels showed a remarkable increase at 60-min after the pump start, although there was no discernible difference in the incremental ratio of hemolysis following 240-min support. Therefore, our findings suggest that the leak rate and hemolysis are to be considered by the primary occlusion settings as well as the time-varying gap deformation for longer use of roller pumps.

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  • Masahiro Oshima, Masaki Kyoso
    2021 Volume 33 Issue 2 Pages 59-66
    Published: June 30, 2021
    Released on J-STAGE: July 04, 2022
    JOURNAL FREE ACCESS

    Sleep is an important rest for life support, and it is known that chronic sleep deprivation adversely affects physical and mental health. Therefore, it is considered that it contributes to the maintenance and promotion of physical and mental health by evaluating daily sleep quality and promoting the improvement of sleep habits. In recent years, polysomnography performed at medical institutions is difficult to perform daily at home. In this study, we developed a wristwatch-type wearable device for the purpose of evaluating daily sleep quality and attempted to estimate sleep stage. As a result, accuracy of HMM was 68.1% when the HMM was trained with time-dependent transition probability and outputs of RNN was trained with wrist acceleration and photoplethysmography. In addition, there was a correlation between sleep variables of PSG such as sleep efficiency and sleep latency and the OSA-MA overall score which assesses subjective sleep quality. In the binary evaluation of sleep quality using the standardized average score as a threshold, accuracy of the wearable device and PSG were similar and exceeded 90%. This suggests that it is possible to evaluate sleep quality by measuring daily sleep with the wearable device.

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  • Yuta Furudate, Kaori Chiba, Yuji Ishida, Sadayoshi Mikami
    2021 Volume 33 Issue 2 Pages 67-76
    Published: June 30, 2021
    Released on J-STAGE: July 04, 2022
    JOURNAL FREE ACCESS

    A home medical supporting technology is quite required in aging society in Japan. The robotics technology can contribute to home medical field. The rehabilitation of the hemiplegia by using a rehabilitation supporting robot exists as one of the fields robotics technology can contribute to. Hemiplegia has the character which the paralysis of finger is difficult to recover. Due to this tendency, a patient must rehabilitate after discharge. However, a patient cannot rehabilitate at home because most devices such as exoskeleton type and glove type tend to be high cost. In this study, we develop finger rehabilitation device for a patient who leaves a hospital, aiming at low cost, simple mechanism, ease to introduce to home. In this paper, we describe the automated evaluation system of motor function of finger by using the finger rehabilitation device. The device requires the pinch task and grasp task. During the task, all finger movements are measured by pressure sensors as time-series signal. After measuring, the feature of motor function is extracted by calculating the dissimilarity with health subject’s signal. As a result, we can show that the feature corresponds to the recovery of the paralysis and the automated evaluation system is realized.

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