Developing smart telehealth system in Indonesia: Progress and challenge

W. Jatmiko, M. A. Ma'sum, S. M. Isa, E. Imah, R. Rahmatullah, B. Wiweko
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引用次数: 21

Abstract

Indonesia is developing country with high population. There are more than 200 million residents living in the country. As a developing country, Indonesia has several health problems. First, Indonesia has a high value of mortality caused by heart and cardio vascular diseases. One of the major cause is the lack of medical checkup especially for heart monitoring. It is caused by limited number of medical instrumentation e.g. ECG in hospital and public health center. The supporting factor is the small number of cardiologist in Indonesia. There are 365 cardiologists across the country, which is a very small number compared to the 200 million of Indonesia population. Furthermore, they are not distributed evenly in all provinces, but only centered in Jakarta and other capital cities. Therefore, it is difficult for residents to get appropriate heart monitoring. Second, the mortality rate of mother and baby during delivery of the baby in Indonesia is also high. One way to solve this problem is to devise a system where the health clinics in rural areas can perform fetal biometry detection before consulting the results to the expert physicians from other areas. The proposed system will be equipped with algorithms for automatic fetal detection and biometry measurement. By the end of this development, we have several results, the first is a classifier to automatic heartbeat disease prediction with accuracy more than 95%, the second is compression method based on wavelet decompositon, and the third is detection and approximation a fetus in an ultrasound image with hit rate more than 93%.
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在印度尼西亚发展智能远程医疗系统:进展与挑战
印度尼西亚是一个人口众多的发展中国家。这个国家有超过2亿的居民。作为一个发展中国家,印度尼西亚存在若干健康问题。首先,印度尼西亚由心脏和心血管疾病引起的死亡率很高。其中一个主要原因是缺乏医疗检查,特别是心脏监测。这是由于医院和公共卫生中心的心电图等医疗仪器数量有限造成的。支持因素是印尼心脏病专家数量少。全国有365名心脏病专家,与印尼2亿人口相比,这是一个非常小的数字。此外,它们并非均匀分布在所有省份,而只是集中在雅加达和其他首都城市。因此,居民很难得到适当的心脏监测。第二,印度尼西亚产妇和婴儿在分娩期间的死亡率也很高。解决这一问题的一种方法是设计一个系统,使农村地区的卫生诊所可以在向其他地区的专家医生咨询结果之前进行胎儿生物测量检测。该系统将配备自动胎儿检测和生物测量算法。最后,我们取得了几个成果,第一是基于小波分解的分类器对心肌病的自动预测,准确率在95%以上;第二是基于小波分解的压缩方法;第三是超声图像中胎儿的检测和逼近,准确率在93%以上。
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