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Hybrid Emotion-aware Monitoring System based on Brainwaves for Internet of Medical Things
IEEE Internet of Things Journal ; 2021.
Article in English | Scopus | ID: covidwho-1238339
ABSTRACT
Driven by an increasing number of connected medical devices, Internet of Medical Things (IoMT), as an application of Internet of Things (IoT) in healthcare, is developed to help collect, analyze and transmit medical data. During the outbreak of pandemic like COVID-19, IoMT can be useful to monitor the status of patients and detect main symptoms remotely, by using various smart sensors. However, due to the lack of emotional care in current IoMT, it is still a challenge to reach an efficient medical process. Especially under COVID-19, there is a need to monitor emotion status among particular people like elderly. In this work, we propose an emotion-aware healthcare monitoring system in IoMT, based on brainwaves. With the fast development of EEG (electroencephalography) sensors in current headsets and some devices, brainwave-based emotion detection becomes feasible. The IoMT devices are used to capture the brainwaves of a patient in a scenario of smart home. Also, our system involves the analysis of touch behavior as the second layer to enhance the brainwave-based emotion recognition. In the user study with 60 participants, the results indicate the viability and effectiveness of our approach in detecting emotion like comfortable and uncomfortable, which can complement existing emotion-aware healthcare applications and mechanisms. IEEE

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Internet of Things Journal Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: IEEE Internet of Things Journal Year: 2021 Document Type: Article