Sani M. Isa

3D SPIHT for multi-lead ECG compression

In this paper we proposed the implementation of 3D Set Partitioning In Hierarchical Trees (SPIHT) algorithm to a multi-lead ECG signal compression. The implementation of 3D SPIHT decorrelates three types of redundancy that commonly found on a multi-lead electrocardiogram (ECG) signal i.e. intra-beat, inter-beat, and inter-lead redundancies. To optimize overall compression performance we also proposed beat reordering and residual calculation technique. Beat reordering rearranges beat order in 2D ECG array based on the similarity between adjacent beats. This rearrangement reduces variances between adjacent beats so that the 2D ECG array contains less high frequency component. Residual calculation optimizes required storage usage further by minimizing amplitude variance of 2D ECG array. The experiments on selected records from St Petersburg INCART 12-lead Arrhythmia Database show that proposed method gives relatively low distortion at compression rate 8 and 16.

Beat reordering for optimal electrocardiogram signal compression using SPIHT

An effective electrocardiogram (ECG) signal compression method based on two-dimensional wavelet transform which employs set partitioning in hierarchical trees (SPIHT) and beat reordering technique is presented. This method utilizes the redundancy between adjacent samples and adjacent beats. Beat reordering rearranges beat order in 2D ECG array based on the similarity between adjacent beats. This rearrangement reduces variances between adjacent beats so that the 2D ECG array contains less high frequency component. The experiments on two datasets from MIT-BIH arrhythmia database revealed that the proposed method is more efficient for ECG signal compression in comparison with several previous proposed methods in literature. The experimental results show that the proposed method yields relatively low distortion at high compression rate.

Developing smart telehealth system in Indonesia: Progress and challenge

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%.

An ECG 12-lead hardware with SPIHT compressing scheme

A 12-lead ECG hardware device with compression scheme using set partitioning in hierarchical trees algorithm is reported. The compression algorithm is expanded with beat reordering technique in order to increase the regularity between signal in 2D ECG array, hence reduce the error while maintain to 1:8 compression ratio. Experimental results shows that the error of sorted compressed signal is less than the unsorted one. The result shows error in 1:8 compression ratio was corrected with nearly 4 percent difference.

Proposal for multispectral image compression methods

This paper has proposed two image compression and decompression schemes for multispectral images. Two issues were considered in the proposed methods. The first issue is the possibility of applying the compression process directly to a set of multispectral images, where the standard JPEG should be applied to each individual image. Considering this issue, a compression and decompression method is proposed based on a hybrid of lower bit suppression and Karhunen-Loeve transform and named as KLT Hybrid. The second issue is the possibility of obtaining a general codebook for a bulky of typical data such as a set of hyperspectral images. Considering this issue, another compression and decompression method is proposed based on vector quantization (VQ) where the general codebook is obtained by a proposed fair-share amount method. Four performance indicators were used to evaluate the results. The indicators include compression ratio, root mean square error, maximum absolute error, and signal to noise ratio. The experimental results have shown good performance indication of both methods.