Telemedycyna

Telemedycyna kojarzy się najczęściej z operacjami "na odległość" w makro lub mikro wymiarze. Przykładem może być lekarz, który operuje chorego w kosmosie, na łodzi podwodnej, przebywając w centrum telemedycznym oddalonym o tysiące kilometrów. Profesor F. Moohr z Lipska, operujący serce za pomocą robotów sterowanych na odległość, twierdzi, że koszty takiego działania są bardzo duże. Ciekawostką może być fakt, że Profesor pierwsze kroki medyczne stawiał w Akademii Medycznej w Gdańsku. Telemedycyna opiera się na postępie technologicznym, który obserwuje się w ostatniej dekadzie. Oznacza to konieczność współpracy między lekarzami i inżynierami w zakresie badań naukowych, edukacji, jak i świadczenia usług medycznych. Interdyscyplinarny charakter telemedycyny wymaga współpracy szczególnie między uczelniami medycznymi i technicznymi. Z dotychczasowych doświadczeń współpracy między Akademią Medyczną w Gdańsku (AMG) i Politechniką Gdańską wynika, że prawdopodobnie również w zakresie technologii przyszłości (eHealth) będą rozwijane wspólne projekty badawcze i edukacyjne

A Detector of Sleep Disorders for Using at Home, Journal of Telecommunications and Information Technology, 2014, nr 2

Obstructive sleep apnea usually requires all-night examination in a specialized clinic, under the supervision of a medical staff. Because of those requirements it is an expensive and a non-widely utilized test. Moving the examination procedure to patients’ home with automatic analysis algorithms involved will decrease the costs and make it available for larger group of patients. The developed device allows all-night recordings of the following biosignals: three channels ECG, thoracic impedance (respiration), snoring sounds and larynx vibrations. Additional information, like patient’s body position changes and electrodes’ attachment quality are estimated as well. The reproducible and high quality signals are obtained using the developed and unobtrusive device

Reliability of Pulse Measurements in Videoplethysmography

Reliable, remote pulse rate measurement is potentially very important for medical diagnostics and screening. In this paper the Videoplethysmography was analyzed especially to verify the possible use of signals obtained for the YUV color model in order to estimate the pulse rate, to examine what is the best pulse estimation method for short video sequences and finally, to analyze how potential PPG-signals can be distinguished from other (e.g. background) signals. The presented methods were verified using data collected from 60 volunteers

Mask Detection and Classification in Thermal Face Images

Face masks are recommended to reduce the transmission of many viruses, especially SARS-CoV-2. Therefore, the automatic detection of whether there is a mask on the face, what type of mask is worn, and how it is worn is an important research topic. In this work, the use of thermal imaging was considered to analyze the possibility of detecting (localizing) a mask on the face, as well as to check whether it is possible to classify the type of mask on the face. The previously proposed dataset of thermal images was extended and annotated with the description of a type of mask and a location of a mask within a face. Different deep learning models were adapted. The best model for face mask detection turned out to be the Yolov5 model in the "nano" version, reaching mAP higher than 97% and precision of about 95%. High accuracy was also obtained for mask type classification. The best results were obtained for the convolutional neural network model built on an autoencoder initially trained in the thermal image reconstruction problem. The pretrained encoder was used to train a classifier which achieved an accuracy of 91%

Face with Mask Detection in Thermal Images Using Deep Neural Networks

As the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The goal of this work is to analyze the effectiveness of deep-learning-based face detection algorithms applied to thermal images, especially for faces covered by virus protective face masks. As part of this work, a set of thermal images was prepared containing over 7900 images of faces with and without masks. Selected raw data preprocessing methods were also investigated to analyze their influence on the face detection results. It was shown that the use of transfer learning based on features learned from visible light images results in mAP greater than 82% for half of the investigated models. The best model turned out to be the one based on Yolov3 model (mean average precision—mAP, was at least 99.3%, while the precision was at least 66.1%). Inference time of the models selected for evaluation on a small and cheap platform allows them to be used for many applications, especially in apps that promote public health

Telemedicine – education and practice

Telemedicine is most commonly associated with a “long-distance” surgery in macro or micro dimensions. An example is a doctor operating on a patient who is in space or on a submarine, while he himself is in a telemedicine center found thousands of kilometers away [1]. The basis for telemedicine is the technological progress that we are observing in the last decade. Therefore, there is a need for cooperation between doctors and engineers in the fields of research, education and in offering medical services. Interdisciplinary character of telemedicine requires cooperation especially between medical and technical universities. The article presents already completed and just started telemedicine projects in Poland as a result of cooperation between Medical University of Gdansk and Gdansk University of Technolog

D2.1 The Specification and Overall Requirements of the eGlasses Platform

The purpose of this document is to review the requirements of the platform in terms of human factors issues that to be addressed, provide an update on the state of the art in augmented reality requirements and to provide an early technical specification. Addressing these issues will ensure that the platform can deliver its full potential when actually operated by the end-users. Indeed, a poorly designed system will not only reduce utility and acceptance of the platform but also induce discomfort and frustration. The document keeps the requirements at a general level as it does not support specific use-case implementations. Instead this document provides a list of general specifications and requirements that must be addressed in order for the eGlasses platform to be a success

Analysis of Properties of an Active Linear Gesture Sensor

Basic gesture sensors can play a significant role as input units in mobile smart devices. However, they have to handle a wide variety of gestures while preserving the advantages of basic sensors. In this paper a user-determined approach to the design of a sparse optical gesture sensor is proposed. The statistical research on a study group of individuals includes the measurement of user-related parameters like the speed of a performed swipe (dynamic gesture) and the morphology of fingers. The obtained results, as well as other a priori requirements for an optical gesture sensor were further used in the design process. Several properties were examined using simulations or experimental verification. It was shown that the designed optical gesture sensor provides accurate localization of fingers, and recognizes a set of static and dynamic hand gestures using a relatively low level of power consumption