International Journal of Environmental Research and Public Health
Sensor-based human activity recognition (HAR) is a method for observing a person’s activity in an... more Sensor-based human activity recognition (HAR) is a method for observing a person’s activity in an environment. With this method, it is possible to monitor remotely. HAR can analyze a person’s gait, whether normal or abnormal. Some of its applications may use several sensors mounted on the body, but this method tends to be complex and inconvenient. One alternative to wearable sensors is using video. One of the most commonly used HAR platforms is PoseNET. PoseNET is a sophisticated platform that can detect the skeleton and joints of the body, which are then known as joints. However, a method is still needed to process the raw data from PoseNET to detect subject activity. Therefore, this research proposes a way to detect abnormalities in gait using empirical mode decomposition and the Hilbert spectrum and transforming keys-joints, and skeletons from vision-based pose detection into the angular displacement of walking gait patterns (signals). Joint change information is extracted using ...
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
Sistem pengawasan pasien rumah sakit yang dilakukan selama ini kebanyakan masih dilakukan secara ... more Sistem pengawasan pasien rumah sakit yang dilakukan selama ini kebanyakan masih dilakukan secara konvensional yakni dengan sistem mengunjungi pasien berjadwal. Alat pengawasan kondisi pasien tersimpan di dalam ruangan dan bisa dicek hanya saat berada dalam ruangan tersebut. Remote Patient Monitoring (RPM) adalah solusi pemanfaatan teknologi dalam bidang kesehatan yang memungkinkan pasien termonitor secara realtime dan dapat diakses kapan saja. Dalam memonitoring kondisi pasien, salah satu yang perlu terus dipantau adalah respiration rate. Respiration rate ini merupakah salah satu parameter yang paling penting dalam memonitoring pasien karena menjadi penanda kondisi patologis pasien. Dalam pengawasan pasien yang disebut sebagai ABCD Sekunder salah satunya parameter yang menjadi perhatian adalah pernafasan. Melalui tulisan ini telah dibuat suatu perangkat respiration rate monitoring yang dapat diakses secara real time untuk mengimplementasikan konsep RPM. Terdapat juga tambahan fitur ...
Termometer Digital saat ini menggunakan indera penglihatan untuk mengetahui informasi mengenai su... more Termometer Digital saat ini menggunakan indera penglihatan untuk mengetahui informasi mengenai suhu badan. Penderita tunanetra memiliki keterbatasan dalam penglihatan, sehingga dibutuhkan Termometer Digital dengan output berupa suara agar para penderita tunanetra dapat mengetahui berapa suhu badan mereka dengan cepat dan mandiri. Termometer Digital untuk Tunanetra telah banyak direalisasikan menggunakan sensor suhu LM35 yang memiliki nilai akurasi dan keliniearan yang baik. Namun sensor ini memiliki sensitivitas suhu yang tinggi sehingga hasil pengukuran suhu tubuh menjadi sulit untuk dibaca karena hasil pengukuran akan cepat berubah ketika mendeteksi perubahan suhu yang relative kecil. Kelemahan sensor LM35 yang lain adalah sensor ini perlu dikemas lebih lanjut ketika akan digunakan pada pasien. Akan tetapi, saat sensor tersebut dikemas maka akan mempengaruhi nilai keakuratan pengukuran. Pada Tugas Akhir ini akan diimplementasikan sebuah Termomter Digital menggunakan sensor suhu DS...
In this Final Project already implemented a digital blood pressure on finger. The purpose is to p... more In this Final Project already implemented a digital blood pressure on finger. The purpose is to prove whether the results of blood pressure measurements on finger by using the oscillomety method can be used as parameters in the measurement of blood pressure such as blood pressure measurements on the arm and wrist. From the research obtained accuracy value of 98.51% in systole and 97.67% in diastole.
Particularly since the COVID-19 outbreak, Indonesia has seen an annual surge in criminal prosecut... more Particularly since the COVID-19 outbreak, Indonesia has seen an annual surge in criminal prosecutions. To increase home security, many technological advances have been made. Face recognition served as the main form of security for almost all of them. Face detection, face segmentation, and face recognition are the three steps in the face recognition process. To avoid misclassification and increase system dependability, accurate recognition of faces becomes crucial in security systems. The optimization tool Grid Search CV produces using a number of machine learning methods that are proposed. Each machine learning has been created using its best model and has attained accuracy levels of at least 90%. The most effective strategy is SVM, which has 100% accuracy rates. A technique for choosing the best model is an alternative. The computation time will be compared to that of more complex systems before these results are eventually communicated to the real system
The EEG is one of the main medical instruments used by clinicians in the analysis and diagnosis o... more The EEG is one of the main medical instruments used by clinicians in the analysis and diagnosis of epilepsy through visual observations or computers. Visual inspection is difficult, time-consuming, and cannot be conducted in real time. Therefore, we propose a digital system for the classification of epileptic EEG in real time on a Field Programmable Gate Array (FPGA). The implemented digital system comprised a communication interface, feature extraction, and classifier model functions. The Hjorth descriptor method was used for feature extraction of activity, mobility, and complexity, with KNN was utilized as a predictor in the classification stage. The proposed system, run on a The Zynq-7000 FPGA device, can generate up to 90.74% accuracy in normal, inter-ictal, and ictal EEG classifications. FPGA devices provided classification results within 0.015 s. The total memory LUT resource used was less than 10%. This system is expected to tackle problems in visual inspection and computer p...
One of the symptoms that appears in patients with COVID-19 is hypoxia or a lack of oxygen in the ... more One of the symptoms that appears in patients with COVID-19 is hypoxia or a lack of oxygen in the body’s tissues or cells below the proper level. One of the methods used to treat hypoxia is to provide oxygen to the patient. Another device that is needed in oxygen therapy for the patient is an oxygen regulator. An oxygen regulator is needed to regulate the volume of oxygen released to the patient. Currently, the control of oxygen flow by the regulator is still done manually. Therefore, in this study, an oxygen regulator was designed that has the ability to regulate the volume of oxygen output based on body weight, respiration rate, and blood saturation. Using these three parameters, the volume of oxygen to be released is adjusted according to the patient’s needs. The system consists of a temperature sensor, mlx90614, and an oxygen saturation sensor, Max30102. The data from the two sensors are processed using microcontrollers to control the movement of the stepper motor as a regulator ...
Gait atau cara berjalan setiap individu bisa dikatakan unik karena setiap individu umumya memilik... more Gait atau cara berjalan setiap individu bisa dikatakan unik karena setiap individu umumya memiliki cara berjalan yang unik. Kelebihan lainnya biometrik dari gait dapat bekerja dalam jarak jauh. Pengenalan individu melalui webcam dengan masukan berupa video dapat menjadi alternatif lain untuk pengenalan individu biometrik selain dengan metode pengenalan biometrik lainnya seperti sidik jari dan iris mata. Tugas akhir ini mengimplementasikan metode reduksi data singular value decomposition (SVD) dan metode klasifikasi jaringan syaraf tiruan (JST) back propagation dalam identifikasi individu berdasarkan gait. Dengan mencari kombinasi parameter-parameter back propagation terbaik pada nilai epoch, learning rate, jumlah neuron hidden layer, dan target MSE dengan melakukan trial and error hingga menemukan nilai persentase akurasi optimal pada pengujian pengenalan individu. Output dari sistem ini adalah ketepatan dalam mengenali suatu objek berjalan. Singular value decomposition dengan jarin...
The purpose of this paper is to propose a cascade complementary filter (CCF) for tracking abdomin... more The purpose of this paper is to propose a cascade complementary filter (CCF) for tracking abdominal or diaphragmatic movement induced by respiratory activity. An inertial sensor (3 DOF accelerometer and 3 DOF gyroscope) is mounted on the upper abdomen, allowing the tilt value of the upper abdomen to be measured. CCF is aimed at overcoming the limitations of the linear CF method for online gyroscope estimation. Our proposed CCF algorithm compensates gyroscope bias with a nonlinear filter and then fuses it with accelerometer angle to obtain abdominal inclination. The CCF method performed better than the linear CF method in terms of respiratory rate error. While CCF increased estimation accuracy, it also appeared to be independent of attitude estimation parameters. The frequency of the CCF respiratory signal remained steady between 0.2 Hz and 0.4 Hz throughout the experiment, with a mean of 0.29 Hz. In other words, the results range between 12 and 24 breaths per minute, which is consid...
International Journal of Online and Biomedical Engineering (iJOE), 2021
One of sleep-disordered breathing (SDB) form is sleep apnea, commonly known as snoring during sle... more One of sleep-disordered breathing (SDB) form is sleep apnea, commonly known as snoring during sleep, based on various complex mechanisms and predisposing factors. Sleep apnea is also related to various medical problems. It impacts morbidity and mortality so that it becomes a burden on public health services. Its detection needs to be done correctly through electrocardiogram signals to detect sleep apnea more quickly and precisely. This study was conducted to detect sleep apnea based on electrocardiogram signals using multi-scale entropy analysis. Multi-scale entropy (MSE) is used in a finite length of time series for measuring the complexity of the signal. MSE can be applied to both physical and physiological data sets and. In this paper we used MSE to detect Sleep Apnea on electrocardiogram (ECG) signals. MSE was applied two classes of ECG data, normal ECG signals, and apnea ECG signals. In this paper, classification and verification were carried out using the Support Vector Machin...
Electroencephalogram (EEG) signal is a biological signal produced from an electrical activity fro... more Electroencephalogram (EEG) signal is a biological signal produced from an electrical activity from the brain. Abnormalities that occur in the pattern or content of the EEG signal indicate a brain disorder or disease. One of the disorders or diseases associated with brain function is epilepsy. Various methods were developed by researchers to analyze abnormalities of EEG signals using digital signal techniques. Many algorithms have been applied to achieve high performance for the classification of EEG epilepsy. However, the complexity and randomness of EEG signals is a challenge for researchers to apply the appropriate algorithm. In this research, fractal analysis of EEG signals is expected to be able to distinguish EEG signals in seizure, no seizure, and normal conditions. The multiscale method used is a multi-distance signal level difference (MSLD) and combined with the fractal dimension. Furthermore, classification is done using Quadratic SVM through 5-fold cross-validation which p...
International Journal of Online and Biomedical Engineering (iJOE), 2021
Epilepsy is the most common form of neurological disease. The electroencephalogram (EEG) is the m... more Epilepsy is the most common form of neurological disease. The electroencephalogram (EEG) is the main tool in the observation of epilepsy. The detection and prediction of seizures in EEG signals require multi-domain analysis, one of which is the time domain combined with other approaches for feature extraction. In this study, a method for detecting seizures in epileptic EEG is proposed using analysis of the distribution of the signal spectrum in the time range t. The EEG signal which includes normal, inter-ictal and ictal is transformed into the time-frequency domain using the Short-Time Fourier Transform (STFT). Simulations were carried out on varying window length, overlap and FFT points to find the highest detection accuracy. The frequency distribution and first-order statistics were then calculated as feature vectors for the classification process. A support vector machine was employed to evaluate the proposed method. The simulation results showed the highest accuracy of 92.3% us...
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021
Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is a ... more Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is a neurological brain disorder due to disturbed nerve cell activity characterized by repeated seizures. Electroencephalographic (EEG) signal processing detects and classifies these seizures as one of the abnormality types in the brain within temporal and spectral content. The proposed method in this paper employed a combination of two feature extractions, namely coarse-grained and fractal dimension, a challenge to obtain a highly accurate procedure to evaluate and predict the epileptic EEG signal of normal, interictal, and seizure classes. The result of classification accuracy using variance fractal dimension (VFD) and quadratic support machine vector (SVM) with a number scale of 10 is 99% as the highest one, excellent performance of the predictive model in terms of the error rate. In addition, a higher scale number does not determine a higher accuracy in this study.
Electrocardiogram (ECG) is a biopotential signal which generated by electrical activity of the he... more Electrocardiogram (ECG) is a biopotential signal which generated by electrical activity of the heart muscle cells. ECG is taken by placing electrodes at a certain point a person’s body. This research propose a wearable ECG device. This device can be used to monitor athlete’s heart condition. ECG device is designed in small size that can be put on the waist with a mini LCD to view ECG signal graph. The ECG system used 3 lead’s configuration based on modified Einthoven triangle method then called modified chest lead. Electrodes that placed on the body, taking electrical signal activity of the heart then the signal is amplified and filtered by signal conditioning. By Analog to Digital Converter signals are converted into digital data then the microcontroller reads data from ADC and displays graphs of signal and heart rate on the Nokia 5110s LCD screen. keywords: Electrocardiogram, Biomedik, Einthoven, ADC, Nokia 5110 Electrocardiogram (ECG) merupakan suatu sinyal biopotensial hasil dar...
Pemantauan vital sign tubuh pasien dapat digunakan untuk menentukan tindakan penanganan yang tepa... more Pemantauan vital sign tubuh pasien dapat digunakan untuk menentukan tindakan penanganan yang tepat pada pasien. Pemantauan vital sign tubuh seorang pasien dilakukan dengan menggunakan perangkat sensor yang terhubung dengan perangkat pemantauan yang berada di kamar pasien. Diperlukan pengawasan dari pihak medis untuk melakukan pengecekan rutin pada kamar pasien untuk mengecek kondisi pasien. Sehingga apabila terdapat pasien yang memerlukan pemantauan berkelanjutan maupun berkala akan membutuhkan waktu yang cukup lama. Oleh karena itu, dibutuhkan suatu perangkat deteksi dan pemantauan vital sign pasien jarak jauh yang dapat memberikan informasi secara real time agar dapat bertindak lebih cepat dan tepat. Dalam tugas akhir ini peneliti membuat sebuah prototype implementasi sistem vital sign monitoring secara multipoint menggunakan wireless sensor network untuk pemantauan vital sign tubuh pasien. Sistem ini menggunakan sebuah perangkat vital sign monitoring untuk mengambil data vital si...
Abstrak Dalam bidang kesehatan, terdapat suatu teknik untuk memeriksa kondisi pasien yang... more Abstrak Dalam bidang kesehatan, terdapat suatu teknik untuk memeriksa kondisi pasien yang dinamakan Auskultasi. Auskultasi merupakan teknik mendengarkan suara yang dihasilkan dari proses biologis yang terjadi dalam tubuh. Teknik ini menggunakan stetoskop sebagai alat bantu. Dengan stetoskop dokter akan bisa menganalisa kondisi fisik pasien melalui suara yang terdengar dari dalam tubuh, misalnya suara jantung, perut, maupun paru – paru. Pada penelitian ini, digunakan rekaman suara perut sebagai objek penelitian. Pada proses perekaman, sering kali ditemukannya noise yang akan mengganggu proses diagnosis salah satunya suara jantung. Suara jantung akan terdengar melalui rekaman suara perut tersebut dikarenakan frekuensi suara jantung lebih tinggi dari frekuensi suara perut. Adaptive noise cancellation sebagai salah satu aplikasi filter adaptif dengan algoritma Least Mean Square, mampu mereduksi suara jantung dari rekaman suara perut. Kinerja sistem dalam penelitian ini diamati ...
A crackle sound on lung happen because there’s a anomaly on respiratory tract. Crackle sound like... more A crackle sound on lung happen because there’s a anomaly on respiratory tract. Crackle sound like a rattling or clicking that happen to be heard when inhaling or exhaling or both phase of breathing. Ascultate is method that use to evaluate abnormalities inside respiratory tract but this method are still a subjective method. There’s a lot of research that using this problem as its goal with using a different kind of method like using features extraction method, one of those is Discrete Wavelet Transform(DWT). Using Wavelet Transform help to separate the crackle feature from lung sound and using a classification to classify it characteristic. the method is easy to use on wave form of data and it used on this final project. The extracted features classify and tested using Restricted Boltzmann Machine(RBM) which resulting 69% as highest accuracy result. Keywords: lung sound, features extraction, RBM, DWT, crackle
Bipolar Disorder (BD) is one of kinds of mental disease that is quite common found in Indonesia. ... more Bipolar Disorder (BD) is one of kinds of mental disease that is quite common found in Indonesia. Those suffering from this disease will drastically experience a shift in mood in a certain period of time. This shift in mood, in turn, can cause many undesired things. The detection of Bipolar Disorder can be done through various diagnosing methods, one of which is by using EEG (Electroencephalogram) signal or ECG (electrocardiogram). One of the methods to detect BD using the ECG signal is by assessing the heart-rate variability (HRV) in which HRV in the patients of Bipolar Disorder tends to be lower than that of normal persons. In this research, an analysis method of HRV was developed to detect Bipolar Disorder using the ECG signal. The method proposed consisted of notch filter, wavelet decomposition, R-R detection, and HRV analysis using Mean Heart Rate (MHR), Standard Deviation of Normal to Normal (SDNN) and Root Mean Square of successive RR interval differences (RMSSD), and SVM for ...
International Journal of Environmental Research and Public Health
Sensor-based human activity recognition (HAR) is a method for observing a person’s activity in an... more Sensor-based human activity recognition (HAR) is a method for observing a person’s activity in an environment. With this method, it is possible to monitor remotely. HAR can analyze a person’s gait, whether normal or abnormal. Some of its applications may use several sensors mounted on the body, but this method tends to be complex and inconvenient. One alternative to wearable sensors is using video. One of the most commonly used HAR platforms is PoseNET. PoseNET is a sophisticated platform that can detect the skeleton and joints of the body, which are then known as joints. However, a method is still needed to process the raw data from PoseNET to detect subject activity. Therefore, this research proposes a way to detect abnormalities in gait using empirical mode decomposition and the Hilbert spectrum and transforming keys-joints, and skeletons from vision-based pose detection into the angular displacement of walking gait patterns (signals). Joint change information is extracted using ...
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika)
Sistem pengawasan pasien rumah sakit yang dilakukan selama ini kebanyakan masih dilakukan secara ... more Sistem pengawasan pasien rumah sakit yang dilakukan selama ini kebanyakan masih dilakukan secara konvensional yakni dengan sistem mengunjungi pasien berjadwal. Alat pengawasan kondisi pasien tersimpan di dalam ruangan dan bisa dicek hanya saat berada dalam ruangan tersebut. Remote Patient Monitoring (RPM) adalah solusi pemanfaatan teknologi dalam bidang kesehatan yang memungkinkan pasien termonitor secara realtime dan dapat diakses kapan saja. Dalam memonitoring kondisi pasien, salah satu yang perlu terus dipantau adalah respiration rate. Respiration rate ini merupakah salah satu parameter yang paling penting dalam memonitoring pasien karena menjadi penanda kondisi patologis pasien. Dalam pengawasan pasien yang disebut sebagai ABCD Sekunder salah satunya parameter yang menjadi perhatian adalah pernafasan. Melalui tulisan ini telah dibuat suatu perangkat respiration rate monitoring yang dapat diakses secara real time untuk mengimplementasikan konsep RPM. Terdapat juga tambahan fitur ...
Termometer Digital saat ini menggunakan indera penglihatan untuk mengetahui informasi mengenai su... more Termometer Digital saat ini menggunakan indera penglihatan untuk mengetahui informasi mengenai suhu badan. Penderita tunanetra memiliki keterbatasan dalam penglihatan, sehingga dibutuhkan Termometer Digital dengan output berupa suara agar para penderita tunanetra dapat mengetahui berapa suhu badan mereka dengan cepat dan mandiri. Termometer Digital untuk Tunanetra telah banyak direalisasikan menggunakan sensor suhu LM35 yang memiliki nilai akurasi dan keliniearan yang baik. Namun sensor ini memiliki sensitivitas suhu yang tinggi sehingga hasil pengukuran suhu tubuh menjadi sulit untuk dibaca karena hasil pengukuran akan cepat berubah ketika mendeteksi perubahan suhu yang relative kecil. Kelemahan sensor LM35 yang lain adalah sensor ini perlu dikemas lebih lanjut ketika akan digunakan pada pasien. Akan tetapi, saat sensor tersebut dikemas maka akan mempengaruhi nilai keakuratan pengukuran. Pada Tugas Akhir ini akan diimplementasikan sebuah Termomter Digital menggunakan sensor suhu DS...
In this Final Project already implemented a digital blood pressure on finger. The purpose is to p... more In this Final Project already implemented a digital blood pressure on finger. The purpose is to prove whether the results of blood pressure measurements on finger by using the oscillomety method can be used as parameters in the measurement of blood pressure such as blood pressure measurements on the arm and wrist. From the research obtained accuracy value of 98.51% in systole and 97.67% in diastole.
Particularly since the COVID-19 outbreak, Indonesia has seen an annual surge in criminal prosecut... more Particularly since the COVID-19 outbreak, Indonesia has seen an annual surge in criminal prosecutions. To increase home security, many technological advances have been made. Face recognition served as the main form of security for almost all of them. Face detection, face segmentation, and face recognition are the three steps in the face recognition process. To avoid misclassification and increase system dependability, accurate recognition of faces becomes crucial in security systems. The optimization tool Grid Search CV produces using a number of machine learning methods that are proposed. Each machine learning has been created using its best model and has attained accuracy levels of at least 90%. The most effective strategy is SVM, which has 100% accuracy rates. A technique for choosing the best model is an alternative. The computation time will be compared to that of more complex systems before these results are eventually communicated to the real system
The EEG is one of the main medical instruments used by clinicians in the analysis and diagnosis o... more The EEG is one of the main medical instruments used by clinicians in the analysis and diagnosis of epilepsy through visual observations or computers. Visual inspection is difficult, time-consuming, and cannot be conducted in real time. Therefore, we propose a digital system for the classification of epileptic EEG in real time on a Field Programmable Gate Array (FPGA). The implemented digital system comprised a communication interface, feature extraction, and classifier model functions. The Hjorth descriptor method was used for feature extraction of activity, mobility, and complexity, with KNN was utilized as a predictor in the classification stage. The proposed system, run on a The Zynq-7000 FPGA device, can generate up to 90.74% accuracy in normal, inter-ictal, and ictal EEG classifications. FPGA devices provided classification results within 0.015 s. The total memory LUT resource used was less than 10%. This system is expected to tackle problems in visual inspection and computer p...
One of the symptoms that appears in patients with COVID-19 is hypoxia or a lack of oxygen in the ... more One of the symptoms that appears in patients with COVID-19 is hypoxia or a lack of oxygen in the body’s tissues or cells below the proper level. One of the methods used to treat hypoxia is to provide oxygen to the patient. Another device that is needed in oxygen therapy for the patient is an oxygen regulator. An oxygen regulator is needed to regulate the volume of oxygen released to the patient. Currently, the control of oxygen flow by the regulator is still done manually. Therefore, in this study, an oxygen regulator was designed that has the ability to regulate the volume of oxygen output based on body weight, respiration rate, and blood saturation. Using these three parameters, the volume of oxygen to be released is adjusted according to the patient’s needs. The system consists of a temperature sensor, mlx90614, and an oxygen saturation sensor, Max30102. The data from the two sensors are processed using microcontrollers to control the movement of the stepper motor as a regulator ...
Gait atau cara berjalan setiap individu bisa dikatakan unik karena setiap individu umumya memilik... more Gait atau cara berjalan setiap individu bisa dikatakan unik karena setiap individu umumya memiliki cara berjalan yang unik. Kelebihan lainnya biometrik dari gait dapat bekerja dalam jarak jauh. Pengenalan individu melalui webcam dengan masukan berupa video dapat menjadi alternatif lain untuk pengenalan individu biometrik selain dengan metode pengenalan biometrik lainnya seperti sidik jari dan iris mata. Tugas akhir ini mengimplementasikan metode reduksi data singular value decomposition (SVD) dan metode klasifikasi jaringan syaraf tiruan (JST) back propagation dalam identifikasi individu berdasarkan gait. Dengan mencari kombinasi parameter-parameter back propagation terbaik pada nilai epoch, learning rate, jumlah neuron hidden layer, dan target MSE dengan melakukan trial and error hingga menemukan nilai persentase akurasi optimal pada pengujian pengenalan individu. Output dari sistem ini adalah ketepatan dalam mengenali suatu objek berjalan. Singular value decomposition dengan jarin...
The purpose of this paper is to propose a cascade complementary filter (CCF) for tracking abdomin... more The purpose of this paper is to propose a cascade complementary filter (CCF) for tracking abdominal or diaphragmatic movement induced by respiratory activity. An inertial sensor (3 DOF accelerometer and 3 DOF gyroscope) is mounted on the upper abdomen, allowing the tilt value of the upper abdomen to be measured. CCF is aimed at overcoming the limitations of the linear CF method for online gyroscope estimation. Our proposed CCF algorithm compensates gyroscope bias with a nonlinear filter and then fuses it with accelerometer angle to obtain abdominal inclination. The CCF method performed better than the linear CF method in terms of respiratory rate error. While CCF increased estimation accuracy, it also appeared to be independent of attitude estimation parameters. The frequency of the CCF respiratory signal remained steady between 0.2 Hz and 0.4 Hz throughout the experiment, with a mean of 0.29 Hz. In other words, the results range between 12 and 24 breaths per minute, which is consid...
International Journal of Online and Biomedical Engineering (iJOE), 2021
One of sleep-disordered breathing (SDB) form is sleep apnea, commonly known as snoring during sle... more One of sleep-disordered breathing (SDB) form is sleep apnea, commonly known as snoring during sleep, based on various complex mechanisms and predisposing factors. Sleep apnea is also related to various medical problems. It impacts morbidity and mortality so that it becomes a burden on public health services. Its detection needs to be done correctly through electrocardiogram signals to detect sleep apnea more quickly and precisely. This study was conducted to detect sleep apnea based on electrocardiogram signals using multi-scale entropy analysis. Multi-scale entropy (MSE) is used in a finite length of time series for measuring the complexity of the signal. MSE can be applied to both physical and physiological data sets and. In this paper we used MSE to detect Sleep Apnea on electrocardiogram (ECG) signals. MSE was applied two classes of ECG data, normal ECG signals, and apnea ECG signals. In this paper, classification and verification were carried out using the Support Vector Machin...
Electroencephalogram (EEG) signal is a biological signal produced from an electrical activity fro... more Electroencephalogram (EEG) signal is a biological signal produced from an electrical activity from the brain. Abnormalities that occur in the pattern or content of the EEG signal indicate a brain disorder or disease. One of the disorders or diseases associated with brain function is epilepsy. Various methods were developed by researchers to analyze abnormalities of EEG signals using digital signal techniques. Many algorithms have been applied to achieve high performance for the classification of EEG epilepsy. However, the complexity and randomness of EEG signals is a challenge for researchers to apply the appropriate algorithm. In this research, fractal analysis of EEG signals is expected to be able to distinguish EEG signals in seizure, no seizure, and normal conditions. The multiscale method used is a multi-distance signal level difference (MSLD) and combined with the fractal dimension. Furthermore, classification is done using Quadratic SVM through 5-fold cross-validation which p...
International Journal of Online and Biomedical Engineering (iJOE), 2021
Epilepsy is the most common form of neurological disease. The electroencephalogram (EEG) is the m... more Epilepsy is the most common form of neurological disease. The electroencephalogram (EEG) is the main tool in the observation of epilepsy. The detection and prediction of seizures in EEG signals require multi-domain analysis, one of which is the time domain combined with other approaches for feature extraction. In this study, a method for detecting seizures in epileptic EEG is proposed using analysis of the distribution of the signal spectrum in the time range t. The EEG signal which includes normal, inter-ictal and ictal is transformed into the time-frequency domain using the Short-Time Fourier Transform (STFT). Simulations were carried out on varying window length, overlap and FFT points to find the highest detection accuracy. The frequency distribution and first-order statistics were then calculated as feature vectors for the classification process. A support vector machine was employed to evaluate the proposed method. The simulation results showed the highest accuracy of 92.3% us...
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021
Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is a ... more Epilepsy, cured by some offered treatments such as medication, surgery, and dietary plan, is a neurological brain disorder due to disturbed nerve cell activity characterized by repeated seizures. Electroencephalographic (EEG) signal processing detects and classifies these seizures as one of the abnormality types in the brain within temporal and spectral content. The proposed method in this paper employed a combination of two feature extractions, namely coarse-grained and fractal dimension, a challenge to obtain a highly accurate procedure to evaluate and predict the epileptic EEG signal of normal, interictal, and seizure classes. The result of classification accuracy using variance fractal dimension (VFD) and quadratic support machine vector (SVM) with a number scale of 10 is 99% as the highest one, excellent performance of the predictive model in terms of the error rate. In addition, a higher scale number does not determine a higher accuracy in this study.
Electrocardiogram (ECG) is a biopotential signal which generated by electrical activity of the he... more Electrocardiogram (ECG) is a biopotential signal which generated by electrical activity of the heart muscle cells. ECG is taken by placing electrodes at a certain point a person’s body. This research propose a wearable ECG device. This device can be used to monitor athlete’s heart condition. ECG device is designed in small size that can be put on the waist with a mini LCD to view ECG signal graph. The ECG system used 3 lead’s configuration based on modified Einthoven triangle method then called modified chest lead. Electrodes that placed on the body, taking electrical signal activity of the heart then the signal is amplified and filtered by signal conditioning. By Analog to Digital Converter signals are converted into digital data then the microcontroller reads data from ADC and displays graphs of signal and heart rate on the Nokia 5110s LCD screen. keywords: Electrocardiogram, Biomedik, Einthoven, ADC, Nokia 5110 Electrocardiogram (ECG) merupakan suatu sinyal biopotensial hasil dar...
Pemantauan vital sign tubuh pasien dapat digunakan untuk menentukan tindakan penanganan yang tepa... more Pemantauan vital sign tubuh pasien dapat digunakan untuk menentukan tindakan penanganan yang tepat pada pasien. Pemantauan vital sign tubuh seorang pasien dilakukan dengan menggunakan perangkat sensor yang terhubung dengan perangkat pemantauan yang berada di kamar pasien. Diperlukan pengawasan dari pihak medis untuk melakukan pengecekan rutin pada kamar pasien untuk mengecek kondisi pasien. Sehingga apabila terdapat pasien yang memerlukan pemantauan berkelanjutan maupun berkala akan membutuhkan waktu yang cukup lama. Oleh karena itu, dibutuhkan suatu perangkat deteksi dan pemantauan vital sign pasien jarak jauh yang dapat memberikan informasi secara real time agar dapat bertindak lebih cepat dan tepat. Dalam tugas akhir ini peneliti membuat sebuah prototype implementasi sistem vital sign monitoring secara multipoint menggunakan wireless sensor network untuk pemantauan vital sign tubuh pasien. Sistem ini menggunakan sebuah perangkat vital sign monitoring untuk mengambil data vital si...
Abstrak Dalam bidang kesehatan, terdapat suatu teknik untuk memeriksa kondisi pasien yang... more Abstrak Dalam bidang kesehatan, terdapat suatu teknik untuk memeriksa kondisi pasien yang dinamakan Auskultasi. Auskultasi merupakan teknik mendengarkan suara yang dihasilkan dari proses biologis yang terjadi dalam tubuh. Teknik ini menggunakan stetoskop sebagai alat bantu. Dengan stetoskop dokter akan bisa menganalisa kondisi fisik pasien melalui suara yang terdengar dari dalam tubuh, misalnya suara jantung, perut, maupun paru – paru. Pada penelitian ini, digunakan rekaman suara perut sebagai objek penelitian. Pada proses perekaman, sering kali ditemukannya noise yang akan mengganggu proses diagnosis salah satunya suara jantung. Suara jantung akan terdengar melalui rekaman suara perut tersebut dikarenakan frekuensi suara jantung lebih tinggi dari frekuensi suara perut. Adaptive noise cancellation sebagai salah satu aplikasi filter adaptif dengan algoritma Least Mean Square, mampu mereduksi suara jantung dari rekaman suara perut. Kinerja sistem dalam penelitian ini diamati ...
A crackle sound on lung happen because there’s a anomaly on respiratory tract. Crackle sound like... more A crackle sound on lung happen because there’s a anomaly on respiratory tract. Crackle sound like a rattling or clicking that happen to be heard when inhaling or exhaling or both phase of breathing. Ascultate is method that use to evaluate abnormalities inside respiratory tract but this method are still a subjective method. There’s a lot of research that using this problem as its goal with using a different kind of method like using features extraction method, one of those is Discrete Wavelet Transform(DWT). Using Wavelet Transform help to separate the crackle feature from lung sound and using a classification to classify it characteristic. the method is easy to use on wave form of data and it used on this final project. The extracted features classify and tested using Restricted Boltzmann Machine(RBM) which resulting 69% as highest accuracy result. Keywords: lung sound, features extraction, RBM, DWT, crackle
Bipolar Disorder (BD) is one of kinds of mental disease that is quite common found in Indonesia. ... more Bipolar Disorder (BD) is one of kinds of mental disease that is quite common found in Indonesia. Those suffering from this disease will drastically experience a shift in mood in a certain period of time. This shift in mood, in turn, can cause many undesired things. The detection of Bipolar Disorder can be done through various diagnosing methods, one of which is by using EEG (Electroencephalogram) signal or ECG (electrocardiogram). One of the methods to detect BD using the ECG signal is by assessing the heart-rate variability (HRV) in which HRV in the patients of Bipolar Disorder tends to be lower than that of normal persons. In this research, an analysis method of HRV was developed to detect Bipolar Disorder using the ECG signal. The method proposed consisted of notch filter, wavelet decomposition, R-R detection, and HRV analysis using Mean Heart Rate (MHR), Standard Deviation of Normal to Normal (SDNN) and Root Mean Square of successive RR interval differences (RMSSD), and SVM for ...
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Papers by Achmad Rizal