Vital signs monitoring wearable technologies

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DyMo Technology Corp (DyMoTech) is a Vancouver engineering firm specialized in developing Health**Monitoring systems for heavy-duty machines to provide a maintenance schedule and prevent potential failures.**The company is active in mining Industry and through the close connection with the mining companies.**DyMoTech's team of specialists has acquired in-depth knowledge of this industry's requirement and points of**pain. The company is currently engaged in an R&D project to create a wearable intelligent drowsiness**prognosis System. Based on company's years of experiences there is a need in the mining industry for staff**fatigue and vital health signs monitoring systems. The lack of drowsiness monitoring and prognosis system in**mining industry can cause irrecoverable losses. Integrated intelligent prognosis system can be utilized in the**mining industry in order to save the operators life and expensive mining instruments. This Engage Plus**proposal is an extension of an earlier Engage Grant that was completed recently where we have conducted a**preliminary study to define the functionality of a wearable drowsiness prognosis hardware for this application.**A wearable cap with dry EEG sensors and related hardware which is used for collecting and transferring EEG**data to drowsiness detection algorithm is developed. A preliminary drowsiness detection idea with EEG signal**processing that included innovative a patentable concept was presented to the company. DyMoTech identified**significant added benefits to drowsiness prognosis system.**In the earlier Engage grant, the focus was on coming up with the functionally and features of a proper wearable**drowsiness prognosis hardware. So far, we have developed a proof of concept. The next task is to develop a**drowsiness detection algorithm to process this data and to arrive at a sensitive, accurate, with better response**time in comparison to the available drowsiness monitoring systems. Our ultimate aim of this study is, therefore,**to design a non-invasive and cost-effective wearable EEG system, which can measure brain activity and**provide drowsiness prognosis using the chaos theory methods.