TY  - CONF
AU  - Tadić, Predrag
AU  - Petrović, Jovana
AU  - Đorđević, Natalija
AU  - Ivanović, Marija
AU  - Lazović, Aleksandar
AU  - Vukčević, Vladan
AU  - Ristić, Arsen
AU  - Hadžievski, Ljupčo
PY  - 2023
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/13044
AB  - We present our progress on the “Multi-SENSor SysteM and ARTificial intelligence in service of heart failure diagnosis (SensSmart)” project, which was introduced at the last year’s edition of the Workshop [1]. The goal of the SensSmart project is to enable early diagnosis of heart failure, through the development of: 1) a multi-sensor polycardiograph apparatus (PCG) that produces simultaneous acquisition of the subject’s electrocardiogram (ECG), photoplethysmogram (PPG), heart sounds, and heart movements, and 2) AI-assisted analysis of the acquired signals. This presentation is going to focus on the acquisition and processing of PPG signals. PPG is obtained by using a pulse oximeter which illuminates the skin and measures the changes in light absorption, thereby enabling the detection of blood volume changes in the vessels. Our PCG apparatus measures the blood flow through the brachial, radial, and carotid arteries. During each heartbeat, the generated waveform typically exhibits several characteristic points [2]. The magnitudes and time distances between these points are useful indicators of many cardiac conditions, including heart failure [3]. However, the inter-patient variability of the PPG waveform makes it challenging to derive simple rule-based diagnostic procedures. This has led many researchers to turn to statistical or machine learning methods for processing of PPG signals [4].  In this presentation, we give an overview of AI-based signal processing methods for PPG, and present some preliminary results and challenges in extracting features from real-world signals obtained using our PCG.
PB  - Belgrade : Institute of Physics
C3  - 16th Photonics Workshop : Book of abstracts
T1  - Photoplethysmogram as a source of biomarkers  for AI-based diagnosis of heart failure
SP  - 24
EP  - 24
UR  - https://hdl.handle.net/21.15107/rcub_vinar_13044
ER  - 

@conference{
author = "Tadić, Predrag and Petrović, Jovana and Đorđević, Natalija and Ivanović, Marija and Lazović, Aleksandar and Vukčević, Vladan and Ristić, Arsen and Hadžievski, Ljupčo",
year = "2023",
abstract = "We present our progress on the “Multi-SENSor SysteM and ARTificial intelligence in service of heart failure diagnosis (SensSmart)” project, which was introduced at the last year’s edition of the Workshop [1]. The goal of the SensSmart project is to enable early diagnosis of heart failure, through the development of: 1) a multi-sensor polycardiograph apparatus (PCG) that produces simultaneous acquisition of the subject’s electrocardiogram (ECG), photoplethysmogram (PPG), heart sounds, and heart movements, and 2) AI-assisted analysis of the acquired signals. This presentation is going to focus on the acquisition and processing of PPG signals. PPG is obtained by using a pulse oximeter which illuminates the skin and measures the changes in light absorption, thereby enabling the detection of blood volume changes in the vessels. Our PCG apparatus measures the blood flow through the brachial, radial, and carotid arteries. During each heartbeat, the generated waveform typically exhibits several characteristic points [2]. The magnitudes and time distances between these points are useful indicators of many cardiac conditions, including heart failure [3]. However, the inter-patient variability of the PPG waveform makes it challenging to derive simple rule-based diagnostic procedures. This has led many researchers to turn to statistical or machine learning methods for processing of PPG signals [4].  In this presentation, we give an overview of AI-based signal processing methods for PPG, and present some preliminary results and challenges in extracting features from real-world signals obtained using our PCG.",
publisher = "Belgrade : Institute of Physics",
journal = "16th Photonics Workshop : Book of abstracts",
title = "Photoplethysmogram as a source of biomarkers  for AI-based diagnosis of heart failure",
pages = "24-24",
url = "https://hdl.handle.net/21.15107/rcub_vinar_13044"
}

Tadić, P., Petrović, J., Đorđević, N., Ivanović, M., Lazović, A., Vukčević, V., Ristić, A.,& Hadžievski, L.. (2023). Photoplethysmogram as a source of biomarkers  for AI-based diagnosis of heart failure. in 16th Photonics Workshop : Book of abstracts
Belgrade : Institute of Physics., 24-24.
https://hdl.handle.net/21.15107/rcub_vinar_13044

Tadić P, Petrović J, Đorđević N, Ivanović M, Lazović A, Vukčević V, Ristić A, Hadžievski L. Photoplethysmogram as a source of biomarkers  for AI-based diagnosis of heart failure. in 16th Photonics Workshop : Book of abstracts. 2023;:24-24.
https://hdl.handle.net/21.15107/rcub_vinar_13044 .

Tadić, Predrag, Petrović, Jovana, Đorđević, Natalija, Ivanović, Marija, Lazović, Aleksandar, Vukčević, Vladan, Ristić, Arsen, Hadžievski, Ljupčo, "Photoplethysmogram as a source of biomarkers  for AI-based diagnosis of heart failure" in 16th Photonics Workshop : Book of abstracts (2023):24-24,
https://hdl.handle.net/21.15107/rcub_vinar_13044 .

TY  - CONF
AU  - Lazović, Aleksandar
AU  - Popović Maneski, Lana
AU  - Hadžievski, Ljupčo
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/10876
AB  - To research the possibility of noninvasive detection of heart failure we developed an acquisition system with multiple sensors. The system synchronously measures cardiovascular pulsations, heart sounds and ECG using different types of sensors positioned only on the patient’s body. The system has a modular structure with five modules: 1. Module for controlling the light source (MWLS) 2. Module for data acquisition from fiber optical sensors (FBGA) with the compact optical spectral analyzer 3. Module for the acquisition of hearth sounds (PCG) with four ports for microphones; 4. Module for the acquisition of standard ECG signals; 5. Module for data acquisition from three accelerometers and three photoplethysmography sensors (ACC/PPG).
PB  - Belgrade : ETRAN
PB  - Belgrade : Academic Mind
C3  - Proceedings of Papers – 6th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2019, Silver Lake, Serbia, June 03 – 06, 2019 / Zbornik radova - 63. Konferencija za elektroniku, telekomunikacije, računarstvo, automatiku i nuklearnu tehniku, Srebrno jezero, 03 – 06. juna, 2019. godine
T1  - Multi-sensor acquisition system for noninvasive detection of heart failure
SP  - 235
EP  - 238
UR  - https://hdl.handle.net/21.15107/rcub_vinar_10876
ER  - 

@conference{
author = "Lazović, Aleksandar and Popović Maneski, Lana and Hadžievski, Ljupčo",
year = "2019",
abstract = "To research the possibility of noninvasive detection of heart failure we developed an acquisition system with multiple sensors. The system synchronously measures cardiovascular pulsations, heart sounds and ECG using different types of sensors positioned only on the patient’s body. The system has a modular structure with five modules: 1. Module for controlling the light source (MWLS) 2. Module for data acquisition from fiber optical sensors (FBGA) with the compact optical spectral analyzer 3. Module for the acquisition of hearth sounds (PCG) with four ports for microphones; 4. Module for the acquisition of standard ECG signals; 5. Module for data acquisition from three accelerometers and three photoplethysmography sensors (ACC/PPG).",
publisher = "Belgrade : ETRAN, Belgrade : Academic Mind",
journal = "Proceedings of Papers – 6th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2019, Silver Lake, Serbia, June 03 – 06, 2019 / Zbornik radova - 63. Konferencija za elektroniku, telekomunikacije, računarstvo, automatiku i nuklearnu tehniku, Srebrno jezero, 03 – 06. juna, 2019. godine",
title = "Multi-sensor acquisition system for noninvasive detection of heart failure",
pages = "235-238",
url = "https://hdl.handle.net/21.15107/rcub_vinar_10876"
}

Lazović, A., Popović Maneski, L.,& Hadžievski, L.. (2019). Multi-sensor acquisition system for noninvasive detection of heart failure. in Proceedings of Papers – 6th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2019, Silver Lake, Serbia, June 03 – 06, 2019 / Zbornik radova - 63. Konferencija za elektroniku, telekomunikacije, računarstvo, automatiku i nuklearnu tehniku, Srebrno jezero, 03 – 06. juna, 2019. godine
Belgrade : ETRAN., 235-238.
https://hdl.handle.net/21.15107/rcub_vinar_10876

Lazović A, Popović Maneski L, Hadžievski L. Multi-sensor acquisition system for noninvasive detection of heart failure. in Proceedings of Papers – 6th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2019, Silver Lake, Serbia, June 03 – 06, 2019 / Zbornik radova - 63. Konferencija za elektroniku, telekomunikacije, računarstvo, automatiku i nuklearnu tehniku, Srebrno jezero, 03 – 06. juna, 2019. godine. 2019;:235-238.
https://hdl.handle.net/21.15107/rcub_vinar_10876 .

Lazović, Aleksandar, Popović Maneski, Lana, Hadžievski, Ljupčo, "Multi-sensor acquisition system for noninvasive detection of heart failure" in Proceedings of Papers – 6th International Conference on Electrical, Electronic and Computing Engineering, IcETRAN 2019, Silver Lake, Serbia, June 03 – 06, 2019 / Zbornik radova - 63. Konferencija za elektroniku, telekomunikacije, računarstvo, automatiku i nuklearnu tehniku, Srebrno jezero, 03 – 06. juna, 2019. godine (2019):235-238,
https://hdl.handle.net/21.15107/rcub_vinar_10876 .