應用於無線身體感測節點之物件偵測與微控制器設計

VLSI Design of an Object-Detector and Micro Control Unit for Wireless Body Sensing Nodes

10.6840/cycu201700529

段閔鈞

無線身體感測網路 ； 自適應性區塊分割演算法 ； 物件偵測器 ； 非對稱性加密演算法 ； 微控制器 ； Wireless Body Sensor Networks (WBSNs) ； Adaptive Block Partition Decision Algorithm ； Object-Detector ； Asymmetric Encryption Algorithm ； Micro Control Unit

中原大學電子工程學系學位論文

2017年

博士

陳世綸

英文

本論文提出一個應用於無線身體感測節點之物件偵測與微控制器設計，加密功能的微控制器電路以及即時的物件偵測提供了無線身體感測網路節點更多更有效的解決方案，尤其是長期的遠距醫療的監控服務和個人隱私資料的保護上擁有更多的保障，此設計主要包含兩部份：自適應性區塊分割物件偵測器和多功能、非對稱性的微處理器設計，無線身體感測節點原理是從數位鏡頭取得視訊影像或是藉由特定感測器偵測人類生理訊號後，透過一個無線通訊協定傳送至遠端中央控制系統，無線身體感測網路就是由許多的感測節點所組成，為了提供相關專業人員高畫質影像和無失真的生理訊號進行即時的判斷，並同時滿足數位影像與生醫訊號處理的需求，一個創新架構的微控制器的設計被使用來實現應用於無線感測網路節點。 無線身體感測節點的應用包含視訊鏡頭感測節點，透過此感測節點可偵測遠端環境是否有物件進入，達到安全監控的應用，相較於之前的論文，本論文提出了一個較高表現、與較低複雜度的物件偵測器的電路，其架構是基於自適應性區塊分割演算法，由於傳統的區域差異演算法易造成物件鋸齒狀失真，所提出的創新區域分割決定演算法，將區域分為數個小區域進行細部的影像分析，最後將結果即時輸出至顯示螢幕上，透過適當的區塊分割，影像中的物件邊緣能夠有效的被抓取，藉以增強影像局部的細節和提高物件偵測精準度，並將超大型積體電路的設計應用導入物件偵測的領域，利用電路特有的管線設計與硬體共用技術，發展出一個能夠即時處理的物件檢測器，且此電路為多級管線與90奈米製程的設計，為了能夠達到即時進行物件偵測的需求，自適應性的區塊分割電演算法成功於硬體實現。 由於無線身體感測感測節點中的資料利用無線的方式傳輸至遠端中央控制系統，為了能夠有效節省系統頻寬及延長無線硬體裝置訊號紀錄使用時間，且同時能進行資料的即時處理和適當保護使用者的個人隱私資料，相比先前的微控制器設計，本論文所提出的創新架構的微控制器設計具有成本考量、多功能以及增強安全性的特點，此微控制器是由非同步介面、多通道感測電路控制器、暫存器緩衝區、硬體共享式濾波器、無失真壓縮器、加密編碼器、錯誤更正電路、通用非同步收發介面、電源管理狀態機和QRS複合波偵測器，此微控制器主要功能為:處理數位資料、生醫訊號與系統間的溝通平台，其中在硬體共享式濾波器被設計用於減少晶片面積，並提供三種類型的濾波器以獲得數位信號中的更多資訊;無失真壓縮器是為了減少誤診的可能性並降低傳輸功率，本論文開發了包括自適應趨勢預測器和可擴展混合熵編碼器;加密編碼器的非對稱架構，可以在無線傳輸期間充分保護個人資訊，此外，將QRS複合波檢測器的架構併入MCU設計中，能夠獲得更多生醫訊號的資訊，像是心跳等常見的生理訊號。 物件偵測器與微控制器的架構進行前瞻的90nm電路合成，在此製程中分別包含了6,990邏輯閘與7,910邏輯閘，相較於之前的物件偵測技術，本論文所提出的物件偵測器減少14.3%以上的面積，且操作頻率最高能達374.5 MHz，功率消耗僅為1.63 mW，由於在電路架構上使用了流水線設計，這樣的設計可以達到3840 × 2160的吞吐量，這是比先前設計所使用的各種不同的模擬平台還要更高速處理，這樣的高速率的積體電路設計非常適合應用在4K2K高畫質的即時影像處理中，本論文所提出的偵測器是有較高的操作頻率、較高的解析度以及較高速的偵測速率;本論文所提出之微控制器操作頻率最高為200 MHz其功率消耗為1.33 mW，相較於之前的微控制器技術，本論文所提出的微控制器至少增加了兩種功能，同時也具有更低的成本、更高的壓縮率、更多的功能、更高的安全性; 最後，高效能、低成本的影像處理器與創新架構的低功耗微控制器設計不僅非常適合無線身體感測節點之應用，也非常適合尺寸小、重量輕的穿戴式裝置科技。

This thesis presents an object-detector and a micro control unit (MCU) for wireless body sensing nodes. It includes an object detector of adaptive block partition decision and a high efficiency, multi-function and asymmetric MCU design. In wireless body sensing nodes solutions, the digital images are taken by image sensors or difference physical signals are captured by various analog sensors. These specified signals are process in digital format and then transmitted to the remote central control system by the wireless communication system. Wireless body sensor networks (WBSNs) is exactly consists by many sensing nodes. In order to provide high resolution images and lossless physical signals for medical expert diagnosing, a high efficiency image processor and a novel architecture of MCU design are proposed for the wireless body sensing nodes. The architecture of proposed object detector is based on adaptive block partition decision (ABPD) algorithm. Although block-based algorithm separates a frame into many blocks can promote the accuracy of the object detection, the edge information will be missed due to the blocking effect. Hence, this thesis develop an edge detection technique to enhance the object detection ability by divided the blocks into numerous sub-blocks. In addition, the liquid-crystal-display (LCD) panel can also display the detected objects by the human eyes to check the result visibly. In contrast to related works, it had the benefits of low complexity, local detail enhancement, and fewer block filter effects. Moreover, shapes in each block can be adjusted according to the predefined judgement conditions to increase the accuracy of the proposed ABPD algorithm. To be able to achieve objection detecting in real time, the proposed ABPD algorithm was realized by using a VLSI technique. The proposed object-detector design achieved the processing of 30 frame- per-second (fps) for 4K2K resolution in the video applications of displaying. Furthermore, this thesis proposed MCU design consists of an asynchronous interface, a multi-sensor 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 (UART) interface, a power management, and a QRS complex detector. A hardware-sharing technique was 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 usages of various body signals. The QRS complex detector was 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 VLSI architecture of the proposed object-detector design contains 6.99-K gate counts. Its power consumption is 1.63 mW and its operating frequency is to 374.5 MHz by using a 90 nm CMOS technology. Compared with previous object-detector designs, the proposed design not only achieves reduction of more silicon area, but also increase the processing throughput, and accuracy of objet-detection for real-time video display. In addition, the proposed MCU design in this thesis contained 7.61-K gate counts and consumed 1.33 mW when operating at 200 MHz by using a 90 nm CMOS process. Compared with previous MCU designs, this work has benefits of increasing the average compression rate by over 12% in ECG signal, providing body signals analysis, and enhancing security of the WBSNs. Finally, the high performance and low-cost VLSI architecture of an object detector and MCU design can not only favorable used in wireless sensing nodes, but also suitable for wearable technique and other fields to make more contribution for the world.

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