2017英特爾ISEF獲獎作品摘要 機器人與智能機器（人工智能） Intel Finalist Abstract Robotics and Intelligent Machines (AI)

獲獎作品基本信息

年份	2017
學科	機器人與智能機器 Robotics and Intelligent Machines
國家/州	United States of America

獲獎作品名稱

An Early Myocardial Infarction Detection System Using Complex Artificial Intelligence

獲獎作品摘要

Myocardial Infarctions are major cardiovascular emergencies that can severely weaken the heart or even cause heart failure if they are not treated in a timely manner. Myocardial Infarctions are also very difficult to diagnose due to the silent symptoms that can occur. As of now, there are no existing solutions that can diagnose Myocardial Infarctions (MI) in a portable setting while keeping a high level of accuracy. The goal of the project was to create a portable system that was both accurate and low cost to detect an early MI. To achieve both accuracy and portability, a wearable ECG system was developed. All heartbeats are not alike and are varied person to person. To counteract this variability while keeping a high level of accuracy, an Artificial Neural Network (ANN) was developed and trained to detect abnormal heartbeats that could signify an MI. This ANN was adjusted for overfitting and pruned so that it could be ported to a Raspberry Pi. This Linux based computer runs python scripts that collect the ECG data, apply pre-processing algorithms including an FFT and classify each heartbeat using the local neural network. This system was heavily optimized using multithreading and other software techniques to reduce the total run time from collection to classification of each heartbeat on the Raspberry Pi. The training of the ANN occurs on the cloud therefore the training resources did not affect the local classification system on the Raspberry Pi. The entire system was trained and tested using the PTB diagnostic ECG database within Physionet which includes real ECG data from MI patients. After training and testing, the portable system achieved an average 92% accuracy while remaining low cost. This system can be applied to the detection and prevention of other diseases.

---

高中生科研 英特爾 Intel ISEF
資訊 · 課程 · 全程指導(dǎo)
請掃碼添加微信好友

[vc_btn title="聯(lián)系電話：(021) 63526628" color="black" align="center" css_animation="fadeIn" link="url:tel%3A02163526628||target:%20_blank|rel:nofollow"]

---

高中生科研學術(shù)活動 英特爾 Intel ISEF 簡介

英特爾國際科學與工程大獎賽，簡稱 "ISEF"，由美國 Society for Science and the Public（科學和公共服務(wù)協(xié)會）主辦，英特爾公司冠名贊助，是全球規(guī)模最大、等級最高的中學生的科研科創(chuàng)賽事。ISEF 的學術(shù)活動學科包括了所有數(shù)學、自然科學、工程的全部領(lǐng)域和部分社會科學。ISEF 素有全球青少年科學學術(shù)活動的“世界杯”之美譽，旨在鼓勵學生團隊協(xié)作，開拓創(chuàng)新，長期專一深入地研究自己感興趣的課題。

>>> 實用鏈接匯總 <<<

英特爾 ISEF 學術(shù)活動詳細介紹

英特爾 ISEF 全程指導(dǎo)方案

· 數(shù)學 · 物理 · 化學 · 生物 · 計算機 · 工程 ·

學科簡介：機器人與智能機器 Robotics and Intelligent Machines

Studies in which the use of machine intelligence is paramount to reducing the reliance on human intervention.

Subcategories:

Biomechanics?(BIE):?Studies and apparatus which mimic the role of mechanics in biological systems.

Cognitive Systems?(COG):?Studies/apparatus that operate similarly to the ways humans think and process information. Systems that provide for increased interaction of people and machines to more naturally extend and magnify human expertise, activity, and cognition.

Control Theory?(CON):?Studies that explore the behavior of dynamical systems with inputs, and how their behavior is modified by feedback. ?This includes new theoretical results and the applications of new and established control methods, system modelling, identification and simulation, the analysis and design of control systems (including computer-aided design), and practical implementation.

Machine Learning?(MAC):?Construction and/or study of algorithms that can learn from data.

Robot Kinematics?(KIN):?The study of movement in robotic systems.

Other?(OTH):?Studies that cannot be assigned to one of the above subcategories.?If the project involves multiple subcategories, the principal subcategory should be chosen instead of Other.