Jacek Rumiński - Publikacje - MOST Wiedzy

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Rok 2024
  • Detection of People Swimming in Water Reservoirs with the Use of Multimodal Imaging and Machine Learning
    Publikacja

    - Rok 2024

    Every year in many countries, there are fatal unintentional drownings in different water reservoirs like swimming pools, lakes, seas, or oceans. The existing threats of this type require creating a method that could automatically supervise such places to increase the safety of bathers. This work aimed to create methods and prototype solutions for detecting people bathing in water reservoirs using a multimodal imaging system and...

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  • Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
    Publikacja

    - Rok 2024

    This paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...

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Rok 2023
Rok 2022
Rok 2021
Rok 2020
Rok 2019
Rok 2018
  • A Meta-Analysis of Pulse Arrival Time Based Blood Pressure Estimation

    The paper presents a preliminary meta-analysis of the sample correlation between pulse arrival time (PAT) and blood pressure (BP). The aim of the study was to verify sample correlation coefficient between PAT and BP using an affine model BP = a · P AT + b for systolic and diastolic blood pressure. The databases included in the search were the IEEE Xplore Digital Library, Springer Link and Google Scholar. Only papers from 2005 to...

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  • Analysis of the Accuracy of Pulse Estimation Using Smart Watches
    Publikacja

    The purpose of this paper is to perform an analysis of the accuracy of the pulse estimation by comparing readings from a smartwatch with readings from medical devices. The study required writing applications that allow continuous pulse measurement. As a result, two applications were created for the smartwatch. The first one is dedicated to Android Wear devices, while the other one is compatible with Tizen watches. The next step...

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  • Digits Recognition with Quadrant Photodiode and Convolutional Neural Network
    Publikacja

    - Rok 2018

    In this paper we have investigated the capabilities of a quadrant photodiode based gesture sensor in the recognition of digits drawn in the air. The sensor consisting of 4 active elements, 4 LEDs and a pinhole was considered as input interface for both discrete and continuous gestures. Index finger and a round pointer were used as navigating mediums for the sensor. Experiments performed with 5 volunteers...

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  • Gesture Recognition With the Linear Optical Sensor and Recurrent Neural Networks

    In this paper, the optical linear sensor, a representative of low-resolution sensors, was investigated in the multiclass recognition of near-field hand gestures. The recurrent neural network (RNN) with a gated recurrent unit (GRU) memory cell was utilized as a gestures classifier. A set of 27 gestures was collected from a group of volunteers. The 27 000 sequences obtained were divided into training, validation, and test subsets....

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  • Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions
    Publikacja

    - Rok 2018

    Abstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...

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  • Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions

    In this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...

wyświetlono 7370 razy