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  • Novel Flexible Material-Bas...
    Chen, Chen; Wang, Zeyu; Li, Wei; Chen, Hongyu; Mei, Zhenning; Yuan, Wei; Tao, Linkai; Zhao, Yuting; Huang, Gaoshan; Mei, Yongfeng; Cao, Zherui; Wang, Ranran; Chen, Wei

    IEEE sensors journal, 10/2019, Letnik: 19, Številka: 19
    Journal Article

    The increased prevalence of chronic disease in aging population entails health risks and imposes significant economic and social burden. It is essential to provide comfortable, cost-effective, and easy-to-use unobtrusive and wearable systems for personal well-being and healthcare. Novel flexible material-based non-invasive and wearable sensors offer an efficient and cost-effective solution, which enables the continuous and real-time monitoring of important physiological signs of the human beings, the assessment of personal health conditions and that provides feedback from remote and home monitoring. In this paper, novel flexible material-based wearable sensors, devised into body sensor networks to capture and monitor vital bio-signals, including electroencephalography (EEG), electrocardiography (ECG) and respiratory, are proposed. Silver nanowires (Ag NWs) and polydimethylsiloxane composite material, carbon foam, and graphene-based fiber are used to sense the EEG, ECG, and respiratory, respectively. With different flexible materials, the smart hat and smart jacket are designed to affix the sensors, which enable long-term health monitoring of vital signals seamlessly. Meanwhile, the corresponding acquisition circuits are developed and mounted with the proposed electrodes on the garments. More importantly, a comprehensive protocol is designed to validate the performance of the proposed system, while some standard sensors and commercial devices are used for comparison. The evaluation results demonstrate the proposed system represents a comparable performance with the existing system. In summary, the proposed sensing system offers an unobtrusive, detachable, expandable, user-friendly, and comfortable solution for physiological signal monitoring. It can be expected to use for the remote healthcare monitoring and provide personalized information of health, fitness, and diseases.