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Design and Implementation of Low-power Neuromodulation S/W based on MSP430

MSP430 기반 저전력 뇌 신경자극기 S/W 설계 및 구현

  • Hong, Sangpyo (Dept. of Electronic Engineering, Inha University) ;
  • Quan, Cheng-Hao (Institute for Information and Electronics Research, Inha University) ;
  • Shim, Hyun-Min (Dept. of Digital Electronics, Dong Seoul University) ;
  • Lee, Sangmin (Dept. of Electronic Engineering, Inha University)
  • 홍상표 (인하대학교 전자공학과) ;
  • 권성호 (인하대학교 정보전자공동연구소) ;
  • 심현민 (동서울대학교 디지털전자과) ;
  • 이상민 (인하대학교 전자공학과)
  • Received : 2016.01.20
  • Accepted : 2016.06.29
  • Published : 2016.07.25

Abstract

A power-efficient neuromodulator is needed for implantable systems. In spite of their stimulation signal's simplicity of wave shape and waiting time of MCU(micro controller unit) much longer than execution time, there is no consideration for low-power design. In this paper, we propose a novel of low-power algorithm based on the characteristics of stimulation signals. Then, we designed and implement a neuromodulation software that we call NMS(neuro modulation simulation). In order to implement low-power algorithm, first, we analyze running time of every function in existing NMS. Then, we calculate execution time and waiting time for these functions. Subsequently, we estimate the transition time between active mode (AM) and low-power mode (LPM). By using these results, we redesign the architecture of NMS in the proposed low-power algorithm: a stimulation signal divided into a number of segments by using characteristics of the signal from which AM or LPM segments are defined for determining the MCU power reduces to turn off or not. Our experimental results indicate that NMS with low-power algorithm reducing current consumption of MCU by 76.31 percent compared to NMS without low-power algorithm.

인체 삽입형 뇌 신경자극기는 소비전력에 있어서 효율적인 구조로 설계되어야 한다. 이들 자극신호는 파형이 단순하고, MCU(micro controller unit)의 대기시간은 실행시간보다 훨씬 긴 특성을 가짐에도 불구하고, 이러한 특성을 고려한 저전력 설계가 되어 있지 않다. 본 논문에서는 자극신호 특성에 기반하는 저전력 알고리즘을 제안한다. 또한 뇌 신경자극기 S/W, NMS(neuro modulation simulation)의 설계 및 구현 결과도 제시한다. 저전력 알고리즘 구현을 위해, 기존 뇌 신경자극기 프로그램의 함수별 수행(running) 시간을 분석하여, 실행(execution) 시간과 대기(waiting) 시간을 도출하였다. 그리고 AM-LPM(active mode-low power mode) 전환시간을 추정하여 저전력 알고리즘 구현에 반영하였다. 본 논문에서 제안하는 저전력 알고리즘은 자극신호의 특성을 이용하여 출력을 다수의 구간으로 분할하고, MCU를 구간별 AM 또는 LPM으로 운용한다. 제안하는 알고리즘의 검증을 위해, 외부 제어프로그램을 개발하여 알고리즘의 동작상태를 확인하였고, 오실로스코프를 이용하여 출력신호의 정확성을 확인하였다. 검증 결과, 제안하는 저전력 알고리즘을 적용할 경우, 기존 뇌 신경자극기 대비 소모전류를 76.31% 감소시킴을 확인 할 수 있었다.

Keywords

References

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