@article{MTMT:36935295,
	title = {Automatic Calculation of the Rheoencephalographic Pulse Wave Peaks: The First Results},
	url = {https://m2.mtmt.hu/api/publication/36935295},
	author = {Pintér, István and Bagany, Mihaly and Szabó, Sándor András and Bodo, Michael},
	doi = {10.21467/ijm.4.1.9492},
	journal-iso = {IJM},
	journal = {International Journal of Methodology},
	volume = {1},
	unique-id = {36935295},
	abstract = {To create an algorithm to detect rheoencephalographic (REG) pulse wave second peak increase, which may detect an increase in intracranial pressure (ICP). REG was measured in 19 healthy volunteers during control and a 15-degree head-down tilt (HDT), which caused an increase in ICP. We developed an algorithm for automatically calculating P1 and P2 from the REG pulse waveform. The result was compared to manual measurements during control and HDT positions. The automatic determination of the peaks’ time instants was considered a series of two-class decision problems in ±15-ms-wide sliding decision windows. We achieved an accuracy of 0.9826, a sensitivity of 0.7727, and a specificity of 0.9902. We used the correlation coefficient between manual measurements and automated data and the normalized mean absolute error (NMAE) metric to characterize the precision of peak amplitude value estimation. We achieved a high correlation (> 0.8) in 92% of all tests, and NMAE < 0.3 in 96%. The remaining cases were analyzed using Bland-Altman plots to uncover the main causes of differences. We tested the hypothesis of increasing P2 peak amplitude during HDT compared to the control position. In the female group, the number of significant increases was 4 out of 6 (67%), both in manual and automatic measurements. In the case of the male group’s manual measurements, 12 of 13 (92%), and the automatic calculation gave 10 of 13 (77%). The significance is to switch from invasive ICP to noninvasive REG to have the same information for decision-making at the bedside to save the lives of neurocritical care patients. Future REG correlation studies suggested using REG in neurocritical care monitoring, space research, and military medical practice.},
	year = {2026},
	pages = {1-15},
	orcid-numbers = {Pintér, István/0000-0002-2180-0504; Szabó, Sándor András/0000-0002-1362-4723; Bodo, Michael/0000-0002-6046-1154}
}

@article{MTMT:37066156,
	title = {Tranzisztoros Colpitts-oszcillátorral előállított hangfrekvenciás kaotikus jelek vizsgálata},
	url = {https://m2.mtmt.hu/api/publication/37066156},
	author = {Pintér, István and Kovács, Lóránt},
	doi = {10.47833/2026.1.ENG.015},
	journal-iso = {GRADUS},
	journal = {GRADUS},
	volume = {13},
	unique-id = {37066156},
	abstract = {A cikkben tranzisztoros Colpitts-oszcillátorral előállítható, hangfrekvenciás periodikus és kaotikus jelekkel foglalkozunk. Háromféle módszerrel állítottunk elő ilyen jeleket, és ábrázolásukat a vonatkozó szakirodalomban közöltekkel összehasonlítva megállapítottuk, hogy mindhárom módszerrel sikerült a periodikus jeleken kívül hangfrekvenciás kaotikus jeleket is létrehozni.
		
		The topic of the paper is generation of audio frequency periodic and chaotic signals using transistor Colpitts-oscillator. The signals were generated with three different methods, and after comparing our signals' illustrative images with those published in the relevant literature, we concluded, that not only periodic, but chaotic signals can be generated, too.},
	year = {2026},
	eissn = {2064-8014},
	orcid-numbers = {Kovács, Lóránt/0009-0005-1304-4509}
}

@inproceedings{MTMT:37541472,
	title = {Acoustic Traffic Monitoring with MEMS Microphones, Concatenated log-Bark Spectrograms and CNN},
	url = {https://m2.mtmt.hu/api/publication/37541472},
	author = {Pintér, István and Kovács, Lóránt},
	booktitle = {Proceedings of the 13th International Conference on Applied Informatics},
	doi = {10.17048/icai.2026.216},
	unique-id = {37541472},
	abstract = {The paper presents our results in algorithm-development and solutions for two ATM problems using MEMS microphone-signals. The aim was that the algorithms have to be realised in the sensor itself, thus we followed the edge-AI system-concept. The IDMT-Traffic dataset was used in algorithm development. The paper proposes the concatenated log-Bark spectrogram as feature extraction, followed by the custom CNN classifier. In the motion’s direction determination (from left/from right/no vehicle) the overall accuracy was 97.70±0.64%. The detection of passing vehicle in background noise was considered as a two-class classification problem (vehicle/no vehicle). The accuracy, F1-score and Matthew’s Correlation Coefficient (MCC) performance parameters achieved were 99.75%, 0.9975, 0.9949, respectively. The conclusion, based on experimental evidence, was that the MEMS-microphones could be used to develop edge-AI type sensors for motion’s direction determination and detection of passing vehicle in background noise using the concatenated log-Bark spectrograms converted to grayscale images as input to a CNN-classifier.},
	year = {2026},
	pages = {216-226},
	orcid-numbers = {Kovács, Lóránt/0009-0005-1304-4509}
}

@CONFERENCE{MTMT:37541509,
	title = {Acoustic Traffic Monitoring with MEMS Microphones, Concatenated log-Bark Spectrograms and CNN},
	url = {https://m2.mtmt.hu/api/publication/37541509},
	author = {Pintér, István and Kovács, Lóránt},
	booktitle = {The 13th International Conference on Applied Informatics, ICAI 2026},
	unique-id = {37541509},
	year = {2026},
	pages = {1-3},
	orcid-numbers = {Kovács, Lóránt/0009-0005-1304-4509}
}

@misc{MTMT:37541550,
	title = {Acoustic Traffic Monitoring with MEMS Microphones, Concatenated log-Bark Spectrograms and CNN},
	url = {https://m2.mtmt.hu/api/publication/37541550},
	author = {Pintér, István and Kovács, Lóránt},
	unique-id = {37541550},
	year = {2026},
	orcid-numbers = {Kovács, Lóránt/0009-0005-1304-4509}
}

@misc{MTMT:37592418,
	title = {Estimation of Laboratory Results of Forage Samples from Nir Spectra Using Machine Learning Methods},
	url = {https://m2.mtmt.hu/api/publication/37592418},
	author = {Pintér, István and Kovács, Lóránt and György, Bazár},
	unique-id = {37592418},
	year = {2026},
	orcid-numbers = {Kovács, Lóránt/0009-0005-1304-4509}
}

@CONFERENCE{MTMT:36176961,
	title = {Noninvasive Measurement of Intracranial Pressure and Cerebral Blood Flow Autoregulation with Rheoencephalography},
	url = {https://m2.mtmt.hu/api/publication/36176961},
	author = {Szabó, Sándor András and Pintér, István and Bagány, Mihály and Bodo, Mihaly},
	booktitle = {1st International Health Science Conference Szeged},
	unique-id = {36176961},
	year = {2025},
	pages = {125-125},
	orcid-numbers = {Szabó, Sándor András/0000-0002-1362-4723}
}

@misc{MTMT:36466278,
	title = {Tranzisztoros Colpitts-oszcillátorral előállított hangfrekvenciás kaotikus jelek vizsgálata},
	url = {https://m2.mtmt.hu/api/publication/36466278},
	author = {Pintér, István and Kovács, Lóránt},
	unique-id = {36466278},
	year = {2025},
	orcid-numbers = {Kovács, Lóránt/0009-0005-1304-4509}
}

@CONFERENCE{MTMT:34598610,
	title = {Noninvasive Measurement of Intracranial Pressure and Cerebral Blood Flow Autoregulation: a Rheoencephalography Study},
	url = {https://m2.mtmt.hu/api/publication/34598610},
	author = {Bodo, Mihaly and Pintér, István and Bagány, Mihály and Szabó, Sándor András},
	booktitle = {NASA Human Research Program: Investigators’ Workshop February 13-16, 2024},
	unique-id = {34598610},
	year = {2024},
	orcid-numbers = {Szabó, Sándor András/0000-0002-1362-4723}
}

@article{MTMT:34754948,
	title = {Rheoencephalography: A non-invasive method for neuromonitoring},
	url = {https://m2.mtmt.hu/api/publication/34754948},
	author = {Szabó, Sándor András and Tótka, Zsolt Tibor and Nagy-Bozsoky, József and Pintér, István and Bagány, Mihály and Bodo, Mihaly},
	doi = {10.2478/joeb-2024-0003},
	journal-iso = {J ELECTR BIOIMP},
	journal = {JOURNAL OF ELECTRICAL BIOIMPEDANCE},
	volume = {15},
	unique-id = {34754948},
	issn = {1891-5469},
	abstract = {In neurocritical care, the gold standard method is intracranial pressure (ICP) monitoring for the patient's lifesaving. Since it is an invasive method, it is desirable to use an alternative, noninvasive technique. The computerized real-time invasive cerebral blood flow (CBF) autoregulation (AR) monitoring calculates the status of CBF AR, called the pressure reactivity index (PRx). Studies documented that the electrical impedance of the head (Rheoencephalography – REG) can detect the status of CBF AR (REGx) and ICP noninvasively. We aimed to test REG to reflect ICP and CBF AR.},
	year = {2024},
	pages = {10-25},
	orcid-numbers = {Szabó, Sándor András/0000-0002-1362-4723}
}