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Advanced VLSI Design of MCU with Sensors

V. Sundaramoorthy

Subject area: Science,Engineering and Technology  ·  Area of research: Applied Electronics

Abstract

The paper is to design of micron control unit (MCU) for wireless body sensor networks (WBSNs) using advanced very large-scale integration (VLSI) circuit design in cost-intention. The proposed MCU design consists of an asynchronous interface, a multisensory controller, a register bank, a hardware-shared filter, a lossless compressor, an encryption encoder, an error correct coding (ECC) circuit, a universal asynchronous receiver/transmitter interface, a power management, and a QRS complex detector. A hardware-sharing technique is added to reduce the silicon area of a hardware-shared filter and provided functions in terms of high-pass, low-pass, and band-pass filters according to the uses of various body signals. The QRS complex detector is designed for calculating QRS information of the ECG signals. In addition, the QRS information is helpful to obtain the heart beats. The lossless compressor consists of an adaptive trending predictor and an extensible hybrid entropy encoder, which provides various methods to compress the different characteristics of body signals adaptively. Furthermore, an encryption encoder based on an asymmetric cryptography technique was designed to protect the private physical information during wireless transmission. The proposed MCU design here contained more than 7 k gate counts and might consume around 1.5 mW when operating at 200 MHz by using a 90-nm CMOS process. Compared with previous designs, this design has the benefits of increasing the average compression rate by over 10% in ECG signal, providing body signals analysis, and enhancing security of the WBSNs.

References

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How to cite this paper

V. Sundaramoorthy "Advanced VLSI Design of MCU with Sensors" Iconic Research And Engineering Journals Volume 2 Issue 11 2019 Page 333-346
V. Sundaramoorthy "Advanced VLSI Design of MCU with Sensors" Iconic Research And Engineering Journals, vol. 2, no. 11, May. 2019
V. Sundaramoorthy (2019). Advanced VLSI Design of MCU with Sensors. Iconic Research And Engineering Journals, 2(11).
V. Sundaramoorthy "Advanced VLSI Design of MCU with Sensors" Iconic Research And Engineering Journals, vol. 2, no. 11, May. 2019.
@article{1702605,
      author = {V. Sundaramoorthy},
      title = {Advanced VLSI Design of MCU with Sensors},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {2},
      number = {11},
      pages = {333-346},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1702605.pdf},
      abstract = {The paper is to design of micron control unit (MCU) for wireless body sensor networks (WBSNs) using advanced very large-scale integration (VLSI) circuit design in cost-intention. The proposed MCU design consists of an asynchronous interface, a multisensory controller, a register bank, a hardware-shared filter, a lossless compressor, an encryption encoder, an error correct coding (ECC) circuit, a universal asynchronous receiver/transmitter interface, a power management, and a QRS complex detector. A hardware-sharing technique is added to reduce the silicon area of a hardware-shared filter and provided functions in terms of high-pass, low-pass, and band-pass filters according to the uses of various body signals. The QRS complex detector is designed for calculating QRS information of the ECG signals. In addition, the QRS information is helpful to obtain the heart beats. The lossless compressor consists of an adaptive trending predictor and an extensible hybrid entropy encoder, which provides various methods to compress the different characteristics of body signals adaptively. Furthermore, an encryption encoder based on an asymmetric cryptography technique was designed to protect the private physical information during wireless transmission. The proposed MCU design here contained more than 7 k gate counts and might consume around 1.5 mW when operating at 200 MHz by using a 90-nm CMOS process. Compared with previous designs, this design has the benefits of increasing the average compression rate by over 10% in ECG signal, providing body signals analysis, and enhancing security of the WBSNs.},
      month = {May},
  }