TY - CHAP A1 - Seepold, Ralf A1 - Dermati, Christoph A1 - Kostka, Artur A1 - Pfeil, Lars A1 - Lange, Ralf A1 - Hermann, Matthias A1 - Martinez, Benedikt T1 - Analyzing environmental conditions and vital signs to increase healthy living T2 - Mobile Networks for Biometric Data Analysis (Lecture notes in electrical engineering ; Vol. 392) N2 - Present demographic change and a growing population of elderly people leads to new medical needs. Meeting these with state of the art technology is as a consequence a rapidly growing market. So this work is aimed at taking modern concepts of mobile and sensor technology and putting them in a medical context. By measuring a user’s vital signs on sensors which are processed on a Android smartphone, the target system is able to determine the current health state of the user and to visualize gathered information. The system also includes a weather forecasting functionality, which alerts the user on possibly dangerous future meteorological events. All information are collected centrally and distributed to users based on their location. Further, the system can correlate the client-side measurement of vital signs with a server-side weather history. This enables personalized forecasting for each user individually. Finally, a portable and affordable application was developed that continuously monitors the health status by many vital sensors, all united on a common smartphone. Y1 - 2016 SN - 978-3-319-39698-9 SN - 978-3-319-39700-9 U6 - http://dx.doi.org/10.1007/978-3-319-39700-9_3 SP - 27 EP - 39 PB - Springer CY - Cham ER - TY - CHAP A1 - Scherz, Wilhelm Daniel A1 - Ortega, Juan Antonio A1 - Martínez Madrid, Natividad A1 - Seepold, Ralf T1 - Heart Rate Variability Indicating Stress Visualized by Correlations Plots T2 - Bioinformatics and Biomedical Engineering : Third International Conference (IWBBIO 2015), April 15-17, 2015, Granada, Spain (Lecture Notes in Computer Science ; Vol. 9044) N2 - Stress is recognized as a factor of predominant disease and in the future the costs for treatment will increase. The presented approach tries to detect stress in a very basic and easy to implement way, so that the cost for the device and effort to wear it remain low. The user should benefit from the fact that the system offers an easy interface reporting the status of his body in real time. In parallel, the system provides interfaces to pass the obtained data forward for further processing and (professional) analyses, in case the user agrees. The system is designed to be used in every day’s activities and it is not restricted to laboratory use or environments. The implementation of the enhanced prototype shows that the detection of stress and the reporting can be managed using correlation plots and automatic pattern recognition even on a very light-weighted microcontroller platform. Y1 - 2015 SN - 978-3-319-16480-9 U6 - http://dx.doi.org/10.1007/978-3-319-16480-9_69 SP - 710 EP - 719 PB - Springer CY - Cham ER - TY - CHAP A1 - Datko, Patrick A1 - Seepold, Ralf A1 - Martínez Madrid, Natividad T1 - Stress map based information system for increasing road safety T2 - Mobile Networks for Biometric Data Analysis Lecture Notes in Electrical Engineering ; Vol. 392) N2 - Stress is becoming an important topic in modern life. The influence of stress results in a higher rate of health disorders such as burnout, heart problems, obesity, asthma, diabetes, depressions and many others. Furthermore individual’s behavior and capabilities could be directly affected leading to altered cognition, inappropriate decision making and problem solving skills. In a dynamic and unpredictable environment, such as automotive, this can result in a higher risk for accidents. Different papers faced the estimation as well as prediction of drivers’ stress level during driving. Another important question is not only the stress level of the driver himself, but also the influence on and of a group of other drivers in the near area. This paper proposes a system, which determines a group of drivers in a near area as clusters and it derives the individual stress level. This information will be analyzed to generate a stress map, which represents a graphical view about road section with a higher stress influence. Aggregated data can be used to generate navigation routes with a lower stress influence to decrease stress influenced driving as well as improve road safety. Y1 - 2016 SN - 978-3-319-39698-9 SN - 978-3-319-39700-9 U6 - http://dx.doi.org/10.1007/978-3-319-39700-9_11 SP - 135 EP - 144 PB - Springer CY - Cham ER - TY - JOUR A1 - Datko, Patrick A1 - Scherz, Wilhelm Daniel A1 - Velicu, Oana Ramona A1 - Seepold, Ralf A1 - Martínez Madrid, Natividad T1 - Personal recommendation system for improving sleep quality JF - Intelligent Decision Technologies 2016, Proceedings of the 8th KES International Conference on Intelligent Decision Technologies (KES-IDT 2016) – Part I (Smart Innovation, Systems and Technologies ; 56) N2 - Sleep is an important aspect in life of every human being. The average sleep duration for an adult is approximately 7 h per day. Sleep is necessary to regenerate physical and psychological state of a human. A bad sleep quality has a major impact on the health status and can lead to different diseases. In this paper an approach will be presented, which uses a long-term monitoring of vital data gathered by a body sensor during the day and the night supported by mobile application connected to an analyzing system, to estimate sleep quality of its user as well as give recommendations to improve it in real-time. Actimetry and historical data will be used to improve the individual recommendations, based on common techniques used in the area of machine learning and big data analysis. Y1 - 2016 SN - 978-3-319-39629-3 SN - 978-3-319-39630-9 U6 - http://dx.doi.org/10.1007/978-3-319-39630-9_34 SP - 405 EP - 412 PB - Springer CY - Cham ER - TY - CHAP A1 - Gansloser, Jens A1 - Seepold, Ralf T1 - Development of an algorithm and a sensor to monitor the heart rate by volumetric measurement techniques T2 - Mobile Networks for Biometric Data Analysis N2 - The person’s heart rate is an important indicator of their health status. A heart rate that is too high or too low could be a sign of several different diseases, such as a heart disorder, obesity, asthma, or many others. Many devices require users to wear the device on their chest or place a finger on the device. The approach presented in this paper describes the principle and implementation of a heart rate monitoring device, which is able to detect the heart rate with high precision with the sensor integrated in a wristband. One method to measure the heart rate is the photoplethysmogram technique. This method measures the change of blood volume through the absorption or reflection of light. A light emitting diode (LED) shines through a thin amount of tissue. A photo-diode registers the intensity of light that traverses the tissue or is reflected by the tissue. Since blood changes its volume with each heartbeat, the photo-diode detects more or less light from the LED. The device is able to measure the heart rate with a high precision, it has low performance and hardware requirements, and it allows an implementation with small micro-controllers. Y1 - 2016 SN - 978-3-319-39698-9 SN - 978-3-319-39700-9 U6 - http://dx.doi.org/10.1007/978-3-319-39700-9_7 VL - 2016 SP - 79 EP - 89 PB - Springer CY - Cham ER - TY - CHAP A1 - Hermann, Matthias A1 - Martínez Madrid, Natividad A1 - Seepold, Ralf T1 - Detection of Variations in Holter ECG Recordings Based on Dynamic Cluster Analysis T2 - Intelligent Decision Technologies : Proceedings of the 7th KES International Conference on Intelligent Decision Technologies (KES-IDT 2015) (Smart Innovation, Systems and Technologies ; 39) N2 - The proposed approach applies current unsupervised clustering approaches in a different dynamic manner. Instead of taking all the data as input and finding clusters among them, the given approach clusters Holter ECG data (long-term electrocardiography data from a holter monitor) on a given interval which enables a dynamic clustering approach (DCA). Therefore advanced clustering techniques based on the well known Dynamic Time Warping algorithm are used. Having clusters e.g. on a daily basis, clusters can be compared by defining cluster shape properties. Doing this gives a measure for variation in unsupervised cluster shapes and may reveal unknown changes in healthiness. Embedding this approach into wearable devices offers advantages over the current techniques. On the one hand users get feedback if their ECG data characteristic changes unforeseeable over time which makes early detection possible. On the other hand cluster properties like biggest or smallest cluster may help a doctor in making diagnoses or observing several patients. Further, on found clusters known processing techniques like stress detection or arrhythmia classification may be applied. KW - Dynamic cluster analysis KW - ECG holter KW - Dynamic time warping KW - OPTICS clustering Y1 - 2015 SN - 978-3-319-19857-6 U6 - http://dx.doi.org/10.1007/978-3-319-19857-6_19 SP - 209 EP - 217 PB - Springer CY - Cham ER - TY - CHAP A1 - Klein, Agnes A1 - Velicu, Oana Ramona A1 - Martínez Madrid, Natividad A1 - Seepold, Ralf T1 - Sleep stages classification using vital signals recordings T2 - 12th International Workshop on Intelligent Solutions in Embedded Systems WISES), 29-30 Oct. 2015, Ancona, Italy N2 - To evaluate the quality of a person's sleep it is essential to identify the sleep stages and their durations. Currently, the gold standard in terms of sleep analysis is overnight polysomnography (PSG), during which several techniques like EEG (eletroencephalogram), EOG (electrooculogram), EMG (electromyogram), ECG (electrocardiogram), SpO2 (blood oxygen saturation) and for example respiratory airflow and respiratory effort are recorded. These expensive and complex procedures, applied in sleep laboratories, are invasive and unfamiliar for the subjects and it is a reason why it might have an impact on the recorded data. These are the main reasons why low-cost home diagnostic systems are likely to be advantageous. Their aim is to reach a larger population by reducing the number of parameters recorded. Nowadays, many wearable devices promise to measure sleep quality using only the ECG and body-movement signals. This work presents an android application developed in order to proof the accuracy of an algorithm published in the sleep literature. The algorithm uses ECG and body movement recordings to estimate sleep stages. The pre-recorded signals fed into the algorithm have been taken from physionet1 online database. The obtained results have been compared with those of the standard method used in PSG. The mean agreement ratios between the sleep stages REM, Wake, NREM-1, NREM-2 and NREM-3 were 38.1%, 14%, 16%, 75% and 54.3%. KW - Heartbeat KW - Body-movement KW - Non REM stage KW - REM stage KW - Sleep stage KW - Algorithm Y1 - 2015 UR - http://ieeexplore.ieee.org/document/7356980/ SN - 978-8-8875-4808-2 N1 - Volltextzugriff im Campusnetz der Hochschule Konstanz möglich. VL - 2015 SP - 47 EP - 50 ER - TY - CHAP A1 - Martínez Madrid, Natividad A1 - Velicu, Oana Ramona A1 - Scherz, Wilhelm Daniel A1 - Seepold, Ralf T1 - Low-cost Body area network supporting preventive healthcare and medical aid T1 - Diseño de una red de área corporal para el soporte de la medicina preventiva y la asistencia médica T2 - Congreso de Asociación Latina para el Análisis de los Sistemas de Salud (ACTAS CALASS 2015), Sept. 2015, Ancona, Italy Y1 - 2015 SN - 1988-7914 ER - TY - CHAP A1 - Soria Morillo, Luis Miguel A1 - Scherz, Wilhelm Daniel A1 - Seepold, Ralf A1 - Ortega, Juan Antonio T1 - Filtering process and data exchange architecture over ECG custom-hardware platform T2 - Jarca 2015, ARCA XVII Conference on Qualitative Systems and Applications in Diagnosis, Robotics and Ambient Intelligence; Vinaros, Spain; 23-27 de junio de 2015 Y1 - 2015 ER - TY - CHAP A1 - Scherz, Wilhelm Daniel A1 - Ortega, Juan Antonio A1 - Seepold, Ralf T1 - Towards emotion pattern extraction with the help of stress detection techniques in order to enable a healthy life T2 - JARCA 2015; ARCA XVII Conference on Qualitative Systems and Applications in Diagnosis, Robotics, Ambient Intelligence and Smart Cities, Vinaros, Spain, 23 to the 27 June 2015 Y1 - 2015 UR - http://madeirasic.us.es/jarca15/?page_id=25&lang=en SN - 978-84-608-5599-6 SP - 39 EP - 44 ER -