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008			201105t2 2 M a|||fram|| 000 0 eng d
020			_aTHE0008961(Local) _qhardback
040			_aUMP _beng _cUMP _erda
090			_aFKEE .H55 2020 r Thesis
100	1		_aHii, Kiew Hui, _eauthor.
245	1	0	_aECG noise reduction technique using antlion (ALO) algorithm for heart rate monitoring devices / _cHii Kiew Hui
264		1	_aKuantan, Pahang : _bUMP, _c2020
264		4	_c© 2020
300			_axi, 56 pages : _billustrations (some color) ; _c30 cm. + _e1 CD ROM
336			_atext _2rdacontent
336			_atext _2rdacontent
337			_aunmediated _2rdamedia
337			_acomputer _2rdamedia
338			_avolume _2rdacarrier
338			_acomputer disc _2rdacarrier
347			_atext file _bPDF _2rda
500			_aFaculty of Electrical and Electronics Engineering
502			_aThesis (Master of Engineering (Electronics)) -- Universiti Malaysia Pahang – 2020
504			_aIncludes bibliographical references
520	3		_aThere are more 6 billion people alive today, and the number is expected to reach until 9 billion in coming 30-40 years. As of the declining of the birth rate and booming aging population, it is suspected that number of elderly people will be more than young children in human history. Wearable technology may provide the solution for providing health care to the growth of the aging population. Based on World Health Organization (2016) report, it has been found out that Cardiovascular Diseases (CVD) is the world’s leading cause of death. Wearable technology solutions could ease the burden on healthcare personal and hospital space more emergent or responsive care at the same time. Since the electrocardiogram (ECG) noise is in the low frequency, it is very easy interrupt with the noise; especially noise from electrical and the intensity of physiological. It will lead to the problem on interruption the morphology and it will make doctors hard to identify what is the disease are. As a result, this is very important to obtain the clean and clear on the morphology of ECG. This is because the morphology of ECG supports in analyzing many information of the heart disorder. This thesis aims to research into an effective way to capture human critical physiological parameters - heart rate. One of the objectives of the research is to identify the morphology of electrocardiogram signal by using the median filter to reduce the high frequency noise for the ECG database. Second objective is to identify and optimize the cutoff frequency using the Antlion optimization (ALO) for FIR filter. The signal processing techniques - Antlion Optimizer (ALO) can help on finding the cutoff frequency automatically. By finding out the cutoff frequency, it will bring to the cancelling noise stage. The cutoff frequency is applied to a Finite Impulse filter (FIR) for getting an original and clean ECG signal. From the simulations, the optimized cutoff frequency is retrieved in higher than the conventional method’s signal to ratio (SNR). The proposed method’s cutoff frequency performance was with the conventional cutoff frequency of feature extraction of the signal. The ALO optimum cutoff frequencies’ result shows that the proposed method reduced more noise than the conventional method.
610	2	0	_aFaculty of Electrical and Electronics Engineering _xDissertations
650		0	_aUniversities and colleges _xDissertations
650		0	_aTheses
942			_2lcc _cTHESIS