• Journal of Biomedical Engineering Research
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• v.40 no.5
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• pp.171-178
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• 2019

This study was conducted to observe the differences in perspective of medical device adverse events and report exchange for domestic stakeholders. The post-market surveillance of medical device not only improves the usability and functionality of the device but also identifies new or growing risks caused by the device. APEC (Asia-Pacific Economic Cooperation) have established and operated post-market surveillance systems for medical devices based on IMDRF (International Medical Device Regulators Forum) and GHTF (Global Harmonization Task Force) guidelines. However, there are significant gaps in many aspects. It is essential to apply harmonized guidelines internationally but also to interpret and apply the guidelines consistently to report and exchange medical device adverse event in domestic. This study retrospectively analyzed the results of surveys conducted by providing examples of the adverse events and guidelines for post-market surveillance. The results of the study showed that there was a considerable difference in the judgment on the phase of using medical device for patient. In the case of medical device adverse event, different opinions shown according to knowledge and experience. Education and training are needed to have a harmonized perspective on the reporting and exchanging international guidelines of the adverse event for domestic stakeholders.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.315-323
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• 1997

Driving is a complex vigilance task that includes improper lookout, excessive speed and inattention. The primary objective of this research is to detect driver drowsiness so that the driver can be alerted to an impending traffic accident in performance. We developed the automatic detection and warning system during drowsy driving. A drowsiness detection system must be able to monitor driver status and detect the detrimental changes of a driver performance. Eyeblink has been found to be a reliable factor of drowsiness detection in earlier studies. As an additional parameter, we also considered the yawning which often occurs in a low vigilance state and predicts the drowsy state. We used a computer vision method to extract the eyeblink and yawning in the face image sequences. When the drowsy state was detected, the driver was refreshed by alarming device and menthol scent generator after deciding the warning level by fuzzy logic. For the evaluation of our system, we measured the physiological parameters such as EOG and EEG. The results indicated that it is possible to detect and alert the driver drowsiness temporarily or continuously by using our system.