IC Design and Fabrication Centre, Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata 700032, India.
J Med Syst. 2009 Dec;33(6):447-65. doi: 10.1007/s10916-008-9206-0.
The paper proposes to develop a field programmable gate array (FPGA) based low cost, low power and high speed novel diagnostic system that can detect in absence of the physician the approaching critical condition of a patient at an early stage and is thus suitable for diagnosis of patients in the rural areas of developing countries where availability of physicians and availability of power is really scarce. The diagnostic system could be installed in health care centres of rural areas where patients can register themselves for periodic diagnoses and thereby detect potential health hazards at an early stage. Multiple pathophysiological parameters with different weights are involved in diagnosing a particular disease. A novel variation of particle swarm optimization called as adaptive perceptive particle swarm optimization has been proposed to determine the optimal weights of these pathophysiological parameters for a more accurate diagnosis. The FPGA based smart system has been applied for early detection of renal criticality of patients. For renal diagnosis, body mass index, glucose, urea, creatinine, systolic and diastolic blood pressures have been considered as pathophysiological parameters. The detection of approaching critical condition of a patient by the instrument has also been validated with the standard Cockford Gault Equation to verify whether the patient is really approaching a critical condition or not. Using Bayesian analysis on the population of 80 patients under study an accuracy of up to 97.5% in renal diagnosis has been obtained.
本文提出开发一种基于现场可编程门阵列（FPGA）的低成本、低功耗、高速的新型诊断系统，该系统能够在没有医生的情况下早期检测到患者的危急情况，因此适用于发展中国家农村地区的患者诊断，在这些地区，医生和电力资源都非常稀缺。诊断系统可以安装在农村地区的医疗中心，患者可以在那里定期进行自我诊断，从而在早期发现潜在的健康危害。诊断特定疾病涉及到多个具有不同权重的病理生理参数。本文提出了一种称为自适应感知粒子群优化的粒子群优化的新变体，用于确定这些病理生理参数的最优权重，以实现更准确的诊断。基于 FPGA 的智能系统已应用于患者肾脏危急情况的早期检测。对于肾脏诊断，体重指数、血糖、尿素、肌酐、收缩压和舒张压被视为病理生理参数。该仪器通过标准 Cockford Gault 方程验证了对患者危急情况的检测，以验证患者是否真的处于危急情况。对 80 名研究对象的人群进行贝叶斯分析，肾脏诊断的准确率高达 97.5%。
