Jain Sanjeev Kumar, Bhaumik Basabi
Electrical Engineering Department , Indian Institute of Technology Delhi , Hauz Khas, New Delhi 110016 , India.
Healthc Technol Lett. 2016 Jan 26;3(1):77-84. doi: 10.1049/htl.2015.0030. eCollection 2016 Mar.
A novel algorithm based on forward search is developed for real-time electrocardiogram (ECG) signal processing and implemented in application specific integrated circuit (ASIC) for QRS complex related cardiovascular disease diagnosis. The authors have evaluated their algorithm using MIT-BIH database and achieve sensitivity of 99.86% and specificity of 99.93% for QRS complex peak detection. In this Letter, Physionet PTB diagnostic ECG database is used for QRS complex related disease detection. An ASIC for cardiovascular disease detection is fabricated using 130-nm CMOS high-speed process technology. The area of the ASIC is 0.5 mm(2). The power dissipation is 1.73 μW at the operating frequency of 1 kHz with a supply voltage of 0.6 V. The output from the ASIC is fed to their Android application that generates diagnostic report and can be sent to a cardiologist through email. Their ASIC result shows average failed detection rate of 0.16% for six leads data of 290 patients in PTB diagnostic ECG database. They also have implemented a low-leakage version of their ASIC. The ASIC dissipates only 45 pJ with a supply voltage of 0.9 V. Their proposed ASIC is most suitable for energy efficient telemetry cardiovascular disease detection system.
开发了一种基于前向搜索的新型算法,用于实时心电图(ECG)信号处理,并在专用集成电路(ASIC)中实现,用于与QRS波群相关的心血管疾病诊断。作者使用麻省理工学院-贝斯以色列女执事医疗中心(MIT-BIH)数据库对其算法进行了评估,在QRS波群峰值检测方面实现了99.86%的灵敏度和99.93%的特异性。在本信函中,使用生理网PTB诊断心电图数据库进行与QRS波群相关的疾病检测。采用130纳米CMOS高速工艺技术制造了一种用于心血管疾病检测的ASIC。该ASIC的面积为0.5平方毫米。在0.6伏电源电压和1千赫工作频率下,功耗为1.73微瓦。ASIC的输出被馈送到其安卓应用程序,该应用程序生成诊断报告,并可通过电子邮件发送给心脏病专家。他们的ASIC结果显示,在PTB诊断心电图数据库中,290名患者的六导联数据平均漏检率为0.16%。他们还实现了ASIC的低泄漏版本。该ASIC在0.9伏电源电压下仅消耗45皮焦。他们提出的ASIC最适合用于节能遥测心血管疾病检测系统。