Detection of Amplitude Peak and Duration of QRS Electrocardiogram Waves Using Discrete Data

In each cycle of the Heart on the Electrocardiogram there are generally P waves as a presentation of Atrial Muscle Depolarization, QRS waves as a presentation of Ventricular Muscle Depolarization and T waves as a presentation of Ventricular Muscle Repolarization. Some types of electrocardiographs only represent wave morphology and some other types of electrocardiographs are equipped with duration and amplitude information but are limited. This limitation of information is calculated manually using small boxes on ecg paper measuring 40 ms for duration and 1 mV for amplitude. The consequences of this manual calculation will require time and accuracy of the calculation results. This study aims to obtain the QRS wave duration along with the amplitude value in each cycle of cardiac examination results. Discrete data from the sampling results of the ECG continuous signal in the maximum filter amplitude to get peak R values. The position of integer peak R with the next peak R is the duration of the cycle. PQRST algorithm is used to obtain peak Q and peak S, so the duration of QS can be obtained by subtracting the position of integer peak S with integer position Q. 10 samples of discrete ecg Sinus Rhythm data from Physionet and 5 samples from ECG-UWG were used in this study. The results showed that all sample data in 3 cycles had a value of QRS duration and peak amplitude values Q, R and S. Peak amplitude R max values and R min physionet sample records were obtained in record 16273 which was 3,485 mV and record 16795 was 0.805 mV. The QRS duration for Bradicardia and Tachicardia is shown in record 16483 which is 40 ms and record 17052 which is 144 ms.

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Geographic Information Systems Application to Drought Distribution Identification with Standardized Precipitation Index (SPI) Method in Trenggalek Regency

INTENSIF Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi ◽

10.29407/intensif.v5i2.15645 ◽

2021 ◽

Vol 5 (2) ◽

pp. 266-278

Author(s):

Aditya Utama ◽

Mohammad Pramono Hadi ◽

Emilya Nurjani

Keyword(s):

Standardized Precipitation Index ◽

Precipitation Index ◽

Analysis Method ◽

A Value ◽

Distance Weighted ◽

Calculation Results ◽

Negative Impacts ◽

The Standardized Precipitation Index ◽

Inverse Distance ◽

Rain Data

The widespread drought area in Trenggalek Regency in 2019 needs to be analyzed to reduce negative impacts and as a monitoring tool to anticipate future drought events. The Standardized Precipitation Index (SPI) is a drought analysis method by calculating the rainwater deficit at various time scales used to identify the distribution of drought in Trenggalek Regency. This study using rain data on 13 rain stations for the period 1990-2019 and agricultural production data for 2019. The calculation results show that the highest SPI value occurred in March at the highly wet level with a value of 2.11. The lowest SPI value occurred in May at the extremely dry level with a value of -2.31. The results are then mapped using ArcGIS with the Inverse Distance Weighted (IDW) method to identify the spatial distribution of drought.

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OPTIMIZATION OF B-SERIES PROPELLER DESIGN AS KCR 60 PROPULSOR TO ACHIEVE OPTIMAL PERFORMANCE USING MATHEMATICAL MODEL

JOURNAL ASRO ◽

10.37875/asro.v10i3.163 ◽

2019 ◽

Vol 10 (3) ◽

pp. 83

Author(s):

Akhmat Nuryadin ◽

Abdul Rahman ◽

Cahyanto Cahyanto

Keyword(s):

Objective Function ◽

Area Ratio ◽

Diameter Ratio ◽

Decision Variable ◽

Propeller Design ◽

A Value ◽

Decision Variables ◽

Blade Area ◽

Calculation Results ◽

Constraint Variable

The process of designing a propeller as a ship propulsor is an important step to produce a propeller that has the ability to achieve the desired target speed of the ship. Propeller optimization is an effort to produce a propeller design with optimal capabilities. This propeller design uses a B-series propeller where this propeller is commonly used as ship propulsor. Optimization steps to find the optimal propeller, namely: determining the objective function, determining the decision variable, and determining the constraint variable. The objective function of this optimization is to determine the Advanced-optimal (J-opt) coefficient value for the propeller. The J-opt coefficient must have a value greater than the J-Design coefficient (J-d) value and the smallest possible value (minimization function). For decision variables include picth diameter ratio (P / D) and Blade area ratio (Ae / Ao) and number of leaves (Z). While the constraint variables are: the pitch diameter ratio value of the B-series propeller (0.5≤P/D≤1.4), the blade area ratio B-series (0.3≤Ae/Ao≤1, 05) as well as the number of blade (2≤Z≤7). From the calculation results of the optimization of the B-series propeller design for the KCR 60, the optimum value is different for each blade. the propeller with the number of blade 2 (Z = 2) obtained the optimum propeller with the value of J-opt =0.77098733, Ae/Ao=0.3, P/D=1.13162337, KT = 0.165632781, 10KQ=0, 27546033 and efficiency=0.73198988. Popeller with number of blades 3 (Z=3) obtained optimum propeller with J-opt value=0.77755594, Ae/Ao=0.3, P/D=1.06370107, KT=0.168069763, 10KQ=0.28984068 and efficiency=0.70590799. Propeller with number of blades 4 (Z=4) obtained optimum propeller with J-opt value=0.78478688, Ae/Ao=0.45954773, P/D=1.03798312, Kt=0.172147709, 10Kq= 0.3091063 and efficiency=0.67797119. Propeller with blades number 5(Z=5) obtained optimum propeller with J-opt value=0.78575616, Ae/Ao=0.65607164, P/D=1.02716571, KT=0.174099168, 10KQ=0.31376705 and efficiency=0.67547177. Propeller with blades number 6 (z=6) obtained optimum propeller with J-opt value=0.78867357, Ae/Ao=0.71124343, P/D=1.0185055, KT=0.176525247, 10KQ=0.32215257 and efficiency =0.66705719. Propeller with number of blades 7 (Z=7) obtained optimum propeller with J-opt value=0.7949898, Ae/Ao=0.69772623, P/D=1.01780081, KT=0.181054792, KQ=0.34011349 , and efficiency =0.64804328.Keywords : KCR, Optimization,Wageningen B-series.

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Automated P-Wave Quality Assessment for Wearable Sensors

Proceedings ◽

10.3390/ecsa-5-05743 ◽

2018 ◽

Vol 4 (1) ◽

pp. 13

Author(s):

Diogo Tecelão ◽

Peter Charlton

Keyword(s):

At Risk ◽

Quality Assessment ◽

Wearable Sensors ◽

P Wave ◽

Sensor Data ◽

Wearable Sensor ◽

High Quality ◽

P Waves ◽

Ecg Signals ◽

Wave Morphology

Hospital patients recovering from major cardiac surgery are at risk of paroxysmal atrial fibrillation (AF), an arrhythmia which can be life-threatening. Wearable sensors are routinely used for electrocardiogram (ECG) monitoring in patients at risk of AF, providing real-time AF detection. However, wearable sensors could have greater impact if used to identify the subtle changes in P-wave morphology which precede AF. This would allow prophylactic treatment to be administered, potentially preventing AF. However, ECG signals acquired by wearable sensors are susceptible to artefact, making it difficult to distinguish between physiological changes in P-wave morphology, and changes due to noise. The aim of this study was to design and assess the performance of a novel automated P-wave quality assessment tool to identify high-quality P-waves, for AF prediction. We designed a two-stage algorithm which uses P-wave template-matching to assess quality. Its performance was assessed using the AFPDB, a database of wearable sensor ECG signals acquired from both healthy subjects and patients susceptible to AF. The algorithm’s quality assessments of 97,989 P-waves were compared to manual annotations. The algorithm identified high-quality P-waves with high sensitivity (93%) and good specificity (82%), indicating that it may have utility for identifying high-quality P-waves in wearable sensor data. Measurements of P-wave morphology derived from high-quality P-waves could be used to predict AF, improving patient outcomes, and reducing healthcare costs. Further studies assessing the clinical utility of the presented tool are warranted for validation.

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ANALYSIS OF SUSTAINABILITY INDEX USAHATANI CABAI IN BANGLI REGENCY

SOCA: Jurnal Sosial Ekonomi Pertanian ◽

10.24843/soca.2018.v12.i01.p08 ◽

2018 ◽

pp. 99

Author(s):

I Nyoman Gede Ustriyana ◽

Ni Wayan Putu Artini

Keyword(s):

Sustainable Development ◽

Agricultural Development ◽

Composite Index ◽

Sustainability Index ◽

A Value ◽

Index Analysis ◽

Index Measurement ◽

Calculation Results ◽

Index Calculation ◽

Structured Questionnaire

There are many experts who disagree on the meaning of the concept of sustainable development. Nevertheless sustainable agriculture has been known to be one of important factor in realizing sustainable development. It is therefore very relevant to conduct a research in order to measure the sustainability of agricultural development through sustainability index measurement. In this study analyzed thesustainability is using composite index calculation method. Methods of data collection was conducted through interviews using structured questionnaire survey conducted to total of 60 respondent of chili farmers in Bangli Regency. The calculation results of the sustainability index of 30 variables obtained shows that only 1 variables were categorized as “high”, 20 variables were in “medium” categoryand 9 variables were in “low” category. From the results obstained the composite index analysis showed a combined index categorized as “medium” with a value of 0.47.

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Kecerdasan Emosional Serta Dampaknya Untuk Kinerja Pegawai Dinas Pekerjaan Umum Dan Penataan Ruang Kota Pematangsiantar

Jurnal Manajemen ◽

10.32832/jm-uika.v11i1.3049 ◽

2020 ◽

Vol 11 (2) ◽

pp. 152

Author(s):

Sudung Simatupang ◽

Efendi Efendi

Keyword(s):

Emotional Intelligence ◽

Employee Performance ◽

Main Task ◽

Font Size ◽

Significance Level ◽

The Public ◽

A Value ◽

Calculation Results ◽

The Individual ◽

Positive Effect

Form of service to the public. is the main task of the citizens of all citizens, because the form of service can be done well, good performance is also needed. Factors that influence performance Then, emotional intelligence can be agreed to control the individual within yourself. The results found that the variable does not require emotional intelligence and the variable called normal distribution with the provisions of the two-way test value> Sig 0.05, which means all variables are normally distributed. Furthermore, the results of the calculation of the path of positive calculation results with a value of Y = 9.885 + 0.805, which means the influence of emotional intelligence increases positive effect on employee performance, as well as the results of tests to answer the hypothesis (t test) shows the tcount data with a value of 10.898 for the variable emotional intelligence> with the results of ttable degree of trust received 1.99773 and the significance level of 0.000 <0.05, the conclusion of this study received an answer from the hypothesis<pre id="tw-target-text" class="tw-data-text tw-text-large XcVN5d tw-ta" style="unicode-bidi: isolate; font-size: 28px; line-height: 36px; background-color: #f8f9fa; border: none; padding: 2px 0.14em 2px 0px; position: relative; margin: -2px 0px; resize: none; font-family: inherit; overflow: hidden; width: 277px; white-space: pre-wrap; overflow-wrap: break-word; color: #222222;" dir="ltr" data-placeholder="Terjemahan"> </pre>

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The Comparison of Data Mining Methods Using C4.5 Algorithm and Naive Bayes in Predicting Heart Disease

Tech-E ◽

10.31253/te.v4i2.543 ◽

2021 ◽

Vol 4 (2) ◽

pp. 44

Author(s):

Rino Rino

Keyword(s):

Data Mining ◽

Heart Disease ◽

Naive Bayes ◽

Naïve Bayes ◽

Data Set ◽

A Value ◽

C4.5 Algorithm ◽

Calculation Results ◽

Mining Methods ◽

Bayes Algorithm

Heart disease is a condition of the presence of fatty deposits in the coronary arteries in the heart which changes the role and shape of the arteries so that blood flow to the heart is obstructed. Data mining methods can predict this disease, some of the methods are C4.5 Algorithm and Naive Bayes which are often used in research.The data set in this research was obtained from the uci machine learning repository site, where the dataset has 3546 records and 13 attributes.The accuracy value of the Naïve Bayes algorithm has a high value of 81.40% compared to the C4.5 algorithm which only has an accuracy value of 79.07%. Based on the calculation results, it can be concluded that the Naïve Bayes Algorithm is a very good clarification because it has a value between 0.709 - 1.00.From conclusion above, the Naïve Bayes algorithm has a higher accuracy value than the C4.5 algorithm so the researchers decided to use the Naïve Bayes algorithm in predicting heart disease.

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PREDIKSI PELUANG KEMATIAN DAN KELAHIRAN MURNI PENDUDUK KABUPATEN MERAUKE MENGGUNAKAN METODE BIRTH AND DEATH PROCESS

BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN ◽

10.30598/barekengvol15iss1pp095-102 ◽

2021 ◽

Vol 15 (1) ◽

pp. 095-102

Author(s):

Minuk Riyana ◽

Marius Agustinus Welliken K.

Keyword(s):

Population Data ◽

The Elderly ◽

Death Process ◽

Initial Time ◽

Time Interval ◽

Birth And Death Process ◽

Female Sex ◽

A Value ◽

Calculation Results ◽

Process Method

This study aims to estimate the probability of birth and death purely based on gender and population data of Merauke City. The chance of birth and death will be used to estimate the life table of the elderly in a population of the City of Merauke. The method used in this research is the birth and process method. The Birth and death process method which is a Poisson distribution is used to predict the chances of birth and death at time t. If the birth and death process fulfills the linearity requirements, then the processes are called the Yule-Furry process. This research discusses the stochastic process of pure birth-death with two sexes in the Yule-Furry Process. From the data on the population of Merauke district which is divided based on the sex of men and women using the pure birth and death model, the calculation results show that the probability value at the time interval 0 ≤ t <1 hour, at the initial time t = 0, the chance of individual birth at female sex is stationary at a value of 0.1762, while the chance of individual death for female sex is stationary at a value of 0.00154. The odds of birth and death in male individuals are stationary at a value of 0.305034 and 0, 059487.

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Cost and Benefit Analysis of Sports Tourism in Downhill Trek, Cikole Lembang, Bandung Barat District, West Java Province

Jurnal Kepariwisataan: Destinasi, Hospitalitas dan Perjalanan ◽

10.34013/jk.v5i1.293 ◽

2021 ◽

Vol 5 (1) ◽

pp. 1-9

Author(s):

Hery Sigit Cahyadi ◽

Herlan Suherlan ◽

Muhammad Aldo Dewantara

Keyword(s):

Cost Benefit ◽

Sport Tourism ◽

Benefit Analysis ◽

Cost And Benefit ◽

A Value ◽

Cost Benefit Ratio ◽

Calculation Results ◽

Cost And Benefit Analysis ◽

The Cost ◽

Benefits And Costs

The purpose of the research is to analyze the cost and benefit analysis and find out the feasibility of sport tourism development at Cikole, Lembang in support the lacal community income. This research was conducted at the Downhill Track Cikole Bike Park in Lembang District and is a tourist attraction in the form of downhill bicycle track facilities. The number obtained is the result of calculating the comparison between benefits and costs and shows the value that can be defined as a feasible activity, because the numbers obtained have a value of more than 1 which is an indication of eligibility with a results in the form of> 1 declared feasible and if <1 (less of) is declared ineligible. Based on the calculation results of the Cost-Benefit Ratio (CBR) analysis with the final result in the form of a comparison value of 3,3128528. With the increase in the number of visits and opening of new jobs, the results of the analysis in the form of downhill activities have been declared feasible.

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Cocaine prolongs norepinephrine synaptic potentials in rat dorsal raphe

Journal of Neurophysiology ◽

10.1152/jn.1995.73.2.687 ◽

1995 ◽

Vol 73 (2) ◽

pp. 687-692 ◽

Cited By ~ 5

Author(s):

S. Oleskevich ◽

J. T. Williams

Keyword(s):

Time Constant ◽

Time Course ◽

Dorsal Raphe ◽

Peak Amplitude ◽

Excitatory Postsynaptic Potential ◽

Postsynaptic Potential ◽

Bath Application ◽

Excitatory Action ◽

S Peak ◽

Dorsal Raphé

1. The effect of cocaine on the excitatory response to norepinephrine (NE) was investigated with the use of intracellular recording from rat dorsal raphe (DR) neurons in the slice preparation. 2. Focal stimulation evoked a slow excitatory postsynaptic potential (sEPSP) that was mediated by alpha 1-adrenoceptor activation. The sEPSP was studied in isolation with the use of a selective 5-HT1A receptor antagonist, pindobind 5HT1A, which eliminated the inhibitory postsynaptic potential (IPSP) that preceded the sEPSP. The sEPSP had a latency to peak of 6 s, a peak amplitude of 6 mV, and a time constant of decay (t) of 14 s. 3. Bath application of cocaine more than doubled the latency-to-peak (13 s) and the time constant of decay (29 s) and had no effect on the amplitude. 4. Iontophoretically applied NE produced a membrane potential depolarization with an amplitude and time course similar to the sEPSP (latency-to-peak = 10 s; peak amplitude = 5 mV; t = 20 s). Cocaine significantly increased the latency-to-peak and the time constant of decay of the depolarization induced by iontophoretically applied NE. 5. Superfusion with NE caused a concentration-dependent depolarization. Cocaine (1 microM) did not change the concentration response to NE. 6. These results suggest that cocaine enhances the excitatory action of NE in the dorsal raphe by a prolongation of the alpha 1-adrenoceptor-mediated sEPSP.

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219A machine learning classification algorithm to detect patients with paroxysmal atrial fibrillation during sinus rhythm

EP Europace ◽

10.1093/europace/euaa162.164 ◽

2020 ◽

Vol 22 (Supplement_1) ◽

Author(s):

D Tachmatzidis ◽

D Filos ◽

I Chouvarda ◽

D Mouselimis ◽

A Tsarouchas ◽

...

Keyword(s):

Atrial Fibrillation ◽

Sinus Rhythm ◽

P Wave ◽

Support Vector ◽

Svm Classifier ◽

P Waves ◽

Machine Learning Classification ◽

Increased Risk ◽

Wave Morphology ◽

The Mean

Abstract Background Atrial fibrillation (AF) - the most common sustained cardiac arrhythmia - while not a life-threatening condition itself, leads to an increased risk of stroke and high rates of mortality. Early detection and diagnosis of AF is a critical issue for all health stakeholders. Purpose The aim of this study is to identify P-wave morphology patterns encountered in patients with Paroxysmal AF (PAF) and to develop a classifier discriminating PAF patients from healthy volunteers. Methods Three-dimensional 1000Hz ECG signals of 5 minutes duration were obtained through the use of a Galix GBI-3S Holter monitor from a total of 68 PAF patients and 52 healthy individuals. Signal pre-processing, consisting of denoising, QRS auto-detection, and ectopic beats removal was performed and a signal window of 250ms prior to the Q-wave (Pseg) was considered for every single beat. P‑wave morphology analysis based on the dynamic application of the k‑means clustering process was performed. For those Pseg that were assigned in the largest cluster, the mean P-wave was computed. The correlation of every P-wave with the mean P-wave of the main cluster was calculated. In case that it exceeded a prespecified threshold, the P-wave was allocated to the main morphology. For the remaining P‑waves, the same approach was followed once again, and the secondary morphology was extracted (picture). The P-waves of the dominant morphology were further analyzed using wavelet transform, whereas time-domain characteristics were also extracted. A Support Vector Machine (SVM) model was created using the Gaussian Radial Basis Function kernel and the forward feature selection wrapper approach was followed. ECGs were allocated to the training, internal validation, and testing datasets in a 3:1:1 ratio. Results The percentage of P-waves following the main morphology in all three leads was lower in PAF patients (91.2 ±7.3%) than in healthy subjects (96.1 ±3.5%, p = 0.02). Classification between the two groups highlighted 7 features, while the SVM classifier resulted in a balanced accuracy of 91.4 ± 0.2% (sensitivity 94.2 ± 0.3%, specificity 88.6 ± 0.1%) Conclusion An Artificial Intelligence based ECG Classifier can efficiently identify PAF patients during normal sinus rhythm. Abstract Figure.

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