The obligation for comprehensive fetal heart rate investigation had driven to improve the passive and non-invasive diagnostic instruments despite the USG or CTG method. Fetal phonocardiography (f-PCG) utilizing the auscultation method met the above criteria, but its interpretation frequently disturbed by the presence of noise. For instance, maternal heart and body organ sounds, fetal movements noise, and ambient noise from the environment where it is recording are the noise that corrupted the f-PCG signal. In this work, the use of discrete wavelet transforms (DWT) to eliminate noise in the f-PCG signal with SNR as the performance parameters observed. It was observing the effect of changes in wavelet type and threshold type on the SNR value. The test was carried out on f-PCG data taken from physio.net. Initial SNR values ranged from -26.7 dB to -4.4 dB; after application of DWT procedure to f-PCG, SNR increased significantly. Based on the test results obtained, wavelet type coif1 with the soft threshold gave the best result with 11.69 dB in SNR value. The coif1 had a superior result than other mother wavelets that use in this work, so the fPCG signal analysis for fetal heart rate investigation suggested to use it.

No abstract

The development of communication services in remote rural areas is difficult to use cable-based systems such as Digital Subscriber Line (DSL) and FTTx. One solution to solve this problem is to use a wireless system such as radio communication. Free Space Optic (FSO) communication system is a better choice compared to radio communication because of the flexibility of frequency usage. One of the problems of the FSO communication system is the range not too far. The range of the FSO can be increased by using the space diversity method. This study compared FSO systems that not use space diversity and FSO systems that use space diversity in three weather conditions, namely clear, haze, and fog. In taking data results using Kim model propagation with variations in the range between 100 – 2000 meters. The modulation used in this study is external modulation. The result of the analysis of FSO performance after adding space diversity, the range of FSO increases as far as 1200 meters when the condition is clear. During the haze condition, the FSO range increase as far as 800 meters. During the fog condition, the FSO range has increased as far as 300 meters. By adding space diversity, the Q-factor value has increased, and BER (Bit Error Rate) has decreased.

No abstract

The development of bionic aids for paralyzed patients leads to the Brain-Computer Interface (BCI) implementation with various obstacles, especially in interpreting brain signals as triggers for the bionic organ. The reading of electrical signal activity in the brain in the BCI system uses electroencephalography (EEG) signal, which comes from many electrodes in the head area and is non-stationary. The measured EEG signal contains much information, including information for the hands and feet motor imagery, so a classification system is needed to separate the information to be processed, such as hand and foot movements. This research aims to develop an imagery motor classification system for the hands and feet so that signals can be classified correctly. The system design is made through several stages of the signal processing process consisting of the pre-processing stage using centering, the feature extraction stage with wavelet packet decomposition (WPD), and multilayer perceptron back-propagation (MLP-BP) as the classifier. Based on the result, this study got the highest accuracy value, about 26.8% at level three, and gain above 0.02. This small accuracy is due to the large error due to under fitting.