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Stress relaxation scaled model using EEG
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| Author:
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, MAHALAKSHMI.V, SASIKALA.G, SATHYASRI.B, JANANI.P
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| Abstract:
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Nowadays the innovation in human-machine communication is sought after, and a machine needs to comprehend human emotions and feelings. Feelings and articulations assume a significant job in our everyday life. It is the regular physiological reaction of the human body which can be perceived by the outward appearance and can be comprehended by text, vocal, verbal and outward appearances. Outward appearance recognition is a testing issue up till now due to numerous reasons. In addition, it comprises of three sub testing like face identification, facial component extraction and demeanor arrangement. Determining compelling facial agent highlights from face pictures is a crucial advance towards effective demeanor acknowledgment. The majority of the frameworks can perceive fundamental model feelings and articulations like sleep identification, eye flickering and yawning. There are many approaches to measure stress. This paper proposes a method where an embedded system with EEG (Electroencephalogram) sensor is used which would replace the most complex and costlier methods. The electrode placed on the head picks up the EEG signals and the data measured from the EEG sensor is sent to raspberry pi microcontroller which analyzes the EEG signal. Based on the analyzed data, the classifier plays the relevant video and audio so that the human can feel free from the stress.
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| Keyword:
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Human-machine communication, Stress, EEG sensor, Raspberry Pi, Classifier.
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| EOI:
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-
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| DOI:
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https://doi.org/10.31838/ijpr/2021.13.02.466
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| Download:
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