BackgroundVolatile organic compounds (VOCs) emitted from exhaled breath from human bodies have been proven to be a useful source of information for early lung cancer diagnosis. To date, there are still arguable information on the production and origin of significant VOCs of cancer cells. Thus, this study aims to conduct in-vitro experiments involving related cell lines to verify the capability of VOCs in providing information of the cells.MethodThe performances of e-nose technology with different statistical methods to determine the best classifier were conducted and discussed. The gas sensor study has been complemented using solid phase micro-extraction-gas chromatography mass spectrometry. For this purpose, the lung cancer cells (A549 and Calu-3) and control cell lines, breast cancer cell (MCF7) and non-cancerous lung cell (WI38VA13) were cultured in growth medium.ResultsThis study successfully provided a list of possible volatile organic compounds that can be specific biomarkers for lung cancer, even at the 24th hour of cell growth. Also, the Linear Discriminant Analysis-based One versus All-Support Vector Machine classifier, is able to produce high performance in distinguishing lung cancer from breast cancer cells and normal lung cells.ConclusionThe findings in this work conclude that the specific VOC released from the cancer cells can act as the odour signature and potentially to be used as non-invasive screening of lung cancer using gas array sensor devices.

Hospital nurse regularly bring her instrument to the patient using cart. They need to push or pull the cart to the patient bed and bring it back many times in a day. This can be tiresome for nurses because they need to treat many patients in the hospital. This research is mainly to solve this problem by constructing a mobile robot for nurses that is able to follow and carry the medical equipment and at the same time perform obstacle avoidance. The designed robot has ability to move in and out at constricted space and is able to avoid any obstacles either static or dynamic. This robot can carry a load of 20 kg and used dc geared motor to move. The mobile platform is able to rotate at axial axis with the construction of special wheel and the placement of the motor. A suitable ultrasonic sensor bank is selected so that robot can detect obstacle around the mobile platform and avoid the obstacle. The robot control and obstacle avoidance system is designed by adopting the facilities of Basic ATOM microcontroller for better performance.

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