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Lucian Pestritu

Bio: Lucian Pestritu is an academic researcher. The author has contributed to research in topics: Remote patient monitoring & Heart rate monitor. The author has an hindex of 2, co-authored 2 publications receiving 10 citations.

Papers
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Proceedings ArticleDOI
01 Nov 2013
TL;DR: A method for monitoring the heart rate using a low-end video camera based on extracting beat-to-beat intervals by passing the color intensity average through a processing pipeline comprised of six stages is presented.
Abstract: This article presents a method for monitoring the heart rate using a low-end video camera. The user places the fingertip on the camera lens and the software detects the periodic variations in light intensity caused by the pulsation of blood in the capillary tissue. The measurement technique is based on extracting beat-to-beat intervals by passing the color intensity average through a processing pipeline comprised of six stages. Our tests indicate a measurement error below 3 bpm, when compared to commonly available home care devices. We present a possible application of our method in the area of stress diagnosis and treatment. The application can be used at home to monitor personal health and enable individuals to perform enhanced self care.

7 citations

Proceedings ArticleDOI
09 Sep 2013
TL;DR: A practical and computationally inexpensive technique for measuring the heart rate using the low-end video cameras already present in a wide range of consumer electronics and treating it through computer music generation is presented.
Abstract: This paper describes a framework for determining stress by measuring the heart rate and treating it through computer music generation. We present a practical and computationally inexpensive technique for measuring the heart rate using the low-end video cameras already present in a wide range of consumer electronics. Our method for treating stress is based on music therapy using computer generated music. Currently the heart rate monitor application and the computer music generation tool are implemented. Further work includes the analysis of heart rate variability and the integration of the framework on a smart phone.

3 citations


Cited by
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Proceedings ArticleDOI
01 Nov 2015
TL;DR: The neural network tools used for edge detection are presented and a proposed one that is able to perform edge detection in dental Cone Beam Computer Tomography (CBCT) images, a necessary step for the teeth 3D reconstruction is proposed.
Abstract: Edge detection is an important task in image processing, many times as part of the segmentation process. When segmentation is performed in medical imaging, one of the preferred tools is neural networks, because of their capabilities of adaptive learning and non-linear mapping. We present in this paper the neural network tools used for edge detection and we propose one that is able to perform edge detection in dental Cone Beam Computer Tomography (CBCT) images, a necessary step for the teeth 3D reconstruction.

13 citations

Journal ArticleDOI
TL;DR: It is concluded that appropriately curated playlists may be able to lead the listener to positive relaxation or activation states or indeed to positive mood change that may have health benefits.
Abstract: Research suggests that music has a powerful effect on the human mind and body. This article explores the impact of music as an intervention. For this purpose, the X-System technology is used to curate relaxing and enlivening music playlists designed to positively impact wellbeing and emotional state during the COVID-19 pandemic. A wellbeing model grounded in autopoietic theory of self-organisation in living systems is developed to inform the evaluation of the impact of the intervention and ensure the reliability of the data. More specifically, data quality is enhanced by focusing the participants’ awareness on their immediate embodied experience of physical, emotional and relational wellbeing and sense of pleasure/displeasure prior to and after listening to a preferred playlist. The statistical analysis shows significant positive changes in emotional wellbeing, valence and sense of meaning ( $p ) with a medium effect size. It also reveals a statistically significant change for physical wellbeing ( $p=0.009$ ) with a small effect size. With the relaxing playlists leading to decrease in arousal levels and the enlivening playlists to an increase in activation, it is also concluded that appropriately curated playlists may be able to lead the listener to positive relaxation or activation states or indeed to positive mood change that may have health benefits.

10 citations

Proceedings ArticleDOI
01 Nov 2015
TL;DR: This paper proposes to use the crowd-sensing paradigm for monitoring the environment, especially the air quality parameters relevant for asthma patients, using affordable and available hardware platforms based on Arduino.
Abstract: Chronic diseases are the main cause of mortality in developed countries. Among them, asthma has an increasing prevalence in urban areas. We propose to use the crowd-sensing paradigm for monitoring the environment, especially the air quality parameters relevant for asthma patients. Asthma is a good candidate for participatory medicine approaches as current medical guidelines promote self-management of the disease by informed and ICT enabled patients. The paper continues our work for m-health applications for asthma patients and focuses on decentralized air quality monitoring by the patients themselves using affordable and available hardware platforms based on Arduino.

9 citations

Proceedings ArticleDOI
13 Jul 2015
TL;DR: A new thermostat is developed that combines Langevin dynamics with the global Berendsen thermostats which is parallelized in CUDA, as well as in OpenCL, which suits the molecular dynamics algorithms.
Abstract: The simulations done in molecular dynamics (MD) are used to learn about the behavior of macromolecular systems. While analyzing large macromolecular systems, the computation can last long, many times for days, weeks and months, due to which the need of parallelization occurs for shortening the time. The graphics processing unit (GPU) yields to multithread computational capacity by the use of CUDA high-level language which suits the molecular dynamics algorithms. The OpenCL platform allows its reckoning kernels to run without difficulty on GPUs, as well as on multicore computers. We developed a new thermostat that combines Langevin dynamics with the global Berendsen thermostat which is parallelized in CUDA, as well as in OpenCL. The GPU parallelization is presented in this paper by applying stochastic dynamics, respectively the Langevin integrator, together with the Berendsen thermostat. A system of atoms is tested by taking into consideration the friction coefficient and the coupling parameter.

4 citations