Transmission of ECG data with the patch-type ECG sensor system using Bluetooth Low Energy

Author(s):  
Young-jin Park ◽  
Hui-sup Cho
Author(s):  
Jordan Frith

The phrase the Internet of things was originally coined in a 1999 presentation about attaching radio frequency identification (RFID) tags to individual objects. These tags would make the objects machine-readable, uniquely identifiable, and, most importantly, wirelessly communicative with infrastructure. This chapter evaluates RFID as a piece of mobile communicative infrastructure, and it examines two emerging forms: near-field communication (NFC) and Bluetooth low-energy beacons. The chapter shows how NFC and Bluetooth low-energy beacons may soon move some types of RFID to smartphones, in this way evolving the use of RFID in payment and transportation and enabling new practices of post-purchasing behaviors.


Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3976
Author(s):  
Sun Jin Kim ◽  
Myeong-Lok Seol ◽  
Byun-Young Chung ◽  
Dae-Sic Jang ◽  
Jonghwan Kim ◽  
...  

Self-powered wireless sensor systems have emerged as an important topic for condition monitoring in nuclear power plants. However, commercial wireless sensor systems still cannot be fully self-sustainable due to the high power consumption caused by excessive signal processing in a mini-electronic computing system. In this sense, it is essential not only to integrate the sensor system with energy-harvesting devices but also to develop simple data processing methods for low power schemes. In this paper, we report a patch-type vibration visualization (PVV) sensor system based on the triboelectric effect and a visualization technique for self-sustainable operation. The PVV sensor system composed of a polyethylene terephthalate (PET)/Al/LCD screen directly converts the triboelectric signal into an informative black pattern on the LCD screen without excessive signal processing, enabling extremely low power operation. In addition, a proposed image processing method reconverts the black patterns to frequency and acceleration values through a remote-control camera. With these simple signal-to-pattern conversion and pattern-to-data reconversion techniques, a vibration visualization sensor network has successfully been demonstrated.


2020 ◽  
Vol 1631 ◽  
pp. 012162
Author(s):  
Yan Long ◽  
Yongli Chen ◽  
Deyong Xiao ◽  
Zheng Li ◽  
Tianpeng Hou ◽  
...  

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