Body sensor network for in-home personal healthcare

A body sensor network solution for personal healthcare under an indoor environment is developed. The system is capable of logging the physiological signals of human beings, tracking the orientations of human body, and monitoring the environmental attributes, which covers all necessary information for the personal healthcare in an indoor environment. The major three chapters of this dissertation contain three subsystems in this work, each corresponding to one subsystem: BioLogger, PAMS and CosNet. Each chapter covers the background and motivation of the subsystem, the related theory, the hardware/software design, and the evaluation of the prototype’s performance

Methods and systems for extracting venous pulsation and respiratory information from photoplethysmographs

A system and method for separating a venous component and an arterial component from a red signal and an infrared signal of a PPG sensor is provided. The method uses the second order statistics of venous and arterial signals to separate the venous andarterial signals. After reliable separation of the venous and thearterial component signals,the component signals can be used for different purposes. In a preferred embodiment, the respiratory signal, pattern, and rate are extracted from the separated venous component and a reliable ?ratio of ratios? is extracted for SpO, using only the arterial component of the PPG signals. The disclosed embodiments enable real-time continuous monitoring of respiration pattern/rate and site-independentarterial oxygen saturation.Board of Regents, University of Texas Syste

Учебно-методическое обоснование целесообразности внедрения телемедицинских технологий для лиц пожилого возраста в одесском регионе = Telemedical technologies implementation teaching and methodic reasonability background for aged people in Odessa region

Polyasny V. A. Учебно-методическое обоснование целесообразности внедрения телемедицинских технологий для лиц пожилого возраста в одесском регионе = Telemedical technologies implementation teaching and methodic reasonability background for aged people in Odessa region. Journal of Education, Health and Sport. 2015;5(8):353-359. ISSN 2391-8306. DOI10.5281/zenodo.29565http://dx.doi.org/10.5281/zenodo.29565http://ojs.ukw.edu.pl/index.php/johs/article/view/2015%3B5%288%29%3A353-359https://pbn.nauka.gov.pl/works/614188Formerly Journal of Health Sciences. ISSN 1429-9623 / 2300-665X. Archives 2011–2014http://journal.rsw.edu.pl/index.php/JHS/issue/archive Deklaracja.Specyfika i zawartość merytoryczna czasopisma nie ulega zmianie.Zgodnie z informacją MNiSW z dnia 2 czerwca 2014 r., że w roku 2014 nie będzie przeprowadzana ocena czasopism naukowych; czasopismo o zmienionym tytule otrzymuje tyle samo punktów co na wykazie czasopism naukowych z dnia 31 grudnia 2014 r.The journal has had 5 points in Ministry of Science and Higher Education of Poland parametric evaluation. Part B item 1089. (31.12.2014).© The Author (s) 2015;This article is published with open access at Licensee Open Journal Systems of Kazimierz Wielki University in Bydgoszcz, Poland and Radom University in Radom, PolandOpen Access. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium,provided the original author(s) and source are credited. This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License(http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non commercial use, distribution and reproduction in any medium, provided the work is properly cited.This is an open access article licensed under the terms of the Creative Commons Attribution Non Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non commercialuse, distribution and reproduction in any medium, provided the work is properly cited.The authors declare that there is no conflict of interests regarding the publication of this paper.Received: 22.06.2015. Revised 24.08.2015. Accepted: 24.08.2015. УДК 681.317+ 61:621.397.13./398 УЧЕБНО-МЕТОДИЧЕСКОЕ ОБОСНОВАНИЕ ЦЕЛЕСООБРАЗНОСТИ внедрениЯ телемедицИНских технологий для лиц пожилого возраста в Одесском регионеTELEMEDICAL TECHNOLOGIES IMPLEMENTATION TEACHING AND METHODIC REASONABILITY BACKGROUND FOR AGED PEOPLE IN ODESSA REGION В. А. Полясный V. A. Polyasny  Одесский национальный медицинский университет, УкраинаOdessa National Medical University, Ukraine AbstractOn the basis of original results and data from literature the perspectives on exploration of ECG monitoring systems for patients suffered from heart and vessel diseases have been analyzed. Experiments were undertaken aimed for maintanence of stable and reliable telecommunicational connection in the city and rural zones. The character of connection from the mobile platform organized on the basis of ambulance has been also performed. The conclusion was made that monitoring systems as well as wireless communication – based telemedical consultations creates perspectives inOdessaregion.  Key words: telemedicine, cardiologic telemedical devices, telemedical network.   Резюме На основе собственных данных и данных литературы проанализированы возможности практического применения систем дистанционного мониторирования ЭКГ у пациентов с острыми заболеваниями сердечно-сосудистой системы. Проведены исследования с обеспечением устойчивой телекоммуникационной связи в условиях мегаполиса, а также сельской местности, при поддержке связи с мобильной платформой-автомобилем медицинской помощи. Сделан вывод о возможности эффективного мониторирования, телемедицинского консультирования кардиологических пациентов пожилого возраста с применением беспроводных систем связи в Одесском регионе.Ключовые слова: телемедицина, кардиологическое телемедицинское оборудование, телемедицинская сеть. Резюме НАВЧАЛЬНО-МЕТОДИЧНЕ ОБГРУНТУВАННЯ ДОЦІЛЬНОСТІ ВПРОВАДЖЕННЯ ТЕЛЕМЕДИЧНИХ ТЕХНОЛОГІЙ ДЛЯ ОСІБ ПОХИЛОГО ВІКУ В ОДЕСЬКОМУ РЕГІОНІ. На основі власних даних та даних літератури проаналізовано можливості практичного застосування систем дистанційного моніторування ЕКГ у пацієнтів з гострими захворюваннями серцево-судинної системи. Проведено дослідження із забезпеченням стійкого телекомунікаційного зв’язку в умовах мегаполісу, а також сільській місцевості, за підтримки зв'язку з мобільною платформою-автомобілем медичної допомоги. Зроблено висновок про можливість ефективного моніторування, телемедичного консультування кардіологічних пацієнтів похилого віку із застосуванням бездротових систем зв'язку в Одеському регіоні.Ключові слова: телемедицина, кардіологічне телемедичне устаткування, телемедична мережа

A study on the effects of window size on electrocardiogram signal quality classification

The sliding window-based method is one of the most used method for automatic Electrocardiogram (ECG) signal quality classification. Based on this method, ECG signals are generally divided into small segments depending on a window size and these segments are then used in another classification process, e.g., feature extraction. The segmentation step is necessary and important for signal classification and signal segments with different window sizes can directly affect the performance of classification. However, in signal quality classification, the window size is often randomly selected and further analysis on the most appropriate window sizes is thus required. In this paper, an extensive investigation of the effects of window size on signal quality classification is presented.A set of statistical-amplitude-based features widely used in the literature was extracted based on 10 different window sizes, ranging from 1 to 10 seconds.To construct signal quality classification models, four well-known machine learning techniques, i.e., Decision Tree, Multilayer Perceptron, k-Nearest Neighbor, and Naïve Bayes, were employed.The performance of the quality classification models was validated on an ECG dataset collected using wireless sensors from 20 volunteers while performing routine activities, e.g.,sitting, walking, and jogging.The evaluation results obtained from four machine-learning classifiers demonstrated that the performance of signal quality classification using window sizes of 5 and 7 seconds were good compared with other sizes