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Author

  • Scherz, Wilhelm Daniel (12) (remove)

Year of publication

  • 2019 (1)
  • 2018 (1)
  • 2017 (2)
  • 2016 (3)
  • 2015 (5)

Document Type

  • Conference Proceeding (12) (remove)

Language

  • English (11)
  • German (1)

Keywords

  • Activity monitoring (1)
  • ECG (2)
  • EKG (1)
  • EMG (1)
  • Physical activity (2)
  • Stress (3)

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Tracking infrastructure of large crowd movement (2015)
Eberlei, Andreas ; Herzberg, Manuel ; Kaltenbach, Jonas ; Ringgeler, Dominik ; Datko, Patrick ; Scherz, Wilhelm Daniel ; Thimm, Tatjana ; Seepold, Ralf
Towards emotion pattern extraction with the help of stress detection techniques in order to enable a healthy life (2015)
Scherz, Wilhelm Daniel ; Ortega, Juan Antonio ; Seepold, Ralf
Stress determent via QRS complex detection, analysis and pre-processing (2016)
Scherz, Wilhelm Daniel ; Ortega, Juan Antonio ; Seepold, Ralf ; Martínez Madrid, Natividad
Stress is recognized as a predominant disease with raising costs for rehabilitation and treatment. Currently there several different approaches that can be used for determining and calculating the stress levels. Usually the methods for determining stress are divided in two categories. The first category do not require any special equipment for measuring the stress. This category useless the variation in the behaviour patterns that occur while stress. The core disadvantage for the category is their limitation to specific use case. The second category uses laboratories instruments and biological sensors. This category allow to measure stress precisely and proficiently but on the same time they are not mobile and transportable and do not support real-time feedback. This work presents a mobile system that provides the calculation of stress. For achieving this, the of a mobile ECG sensor is analysed, processed and visualised over a mobile system like a smartphone. This work also explains the used stress measurement algorithm. The result of this work is a portable system that can be used with a mobile system like a smartphone as visual interface for reporting the current stress level.
PredTour - predicting tourism movements (2017)
Thimm, Tatjana ; Bild, Christine ; Gaiduk, Maksym ; Scherz, Wilhelm Daniel ; Seepold, Ralf ; Hüttermann, Marcel ; Hannich, Frank ; Haarmann, Jens
Peer reviewed abstract, 10.11.2017
Pattern recognition techniques and classification sets supporting behavioural tagging when using a limited number of body sensors (2017)
Scherz, Wilhelm Daniel ; Ortega, Juan Antonio ; Seepold, Ralf ; Conti, Massimo
Stress and physical activities are important aspects of life of people. Body reactions on stress and on physical activities can be very similar but long-term stress leads to diseases and damages the body. Currently there is no method to differentiate easily and clearly between these two aspects in a time slot. We have confronted this problem while developing a mobile system for detection and analysis of stress. This paper presents an approach, which uses a long-term monitor with ECG/EKG capabilities and analysis of the heart rate data that is extracted from the device. The focus of the work is to find characteristics that are useful for differentiation between physical activity and stress.
Low-cost Body area network supporting preventive healthcare and medical aid (2015)
Martínez Madrid, Natividad ; Velicu, Oana Ramona ; Scherz, Wilhelm Daniel ; Seepold, Ralf
Heart Rate Variability Indicating Stress Visualized by Correlations Plots (2015)
Scherz, Wilhelm Daniel ; Ortega, Juan Antonio ; Martínez Madrid, Natividad ; Seepold, Ralf
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.
Filtering process and data exchange architecture over ECG custom-hardware platform (2015)
Soria Morillo, Luis Miguel ; Scherz, Wilhelm Daniel ; Seepold, Ralf ; Ortega, Juan Antonio
Distinction of physical activity and stress using RR intervals (2018)
Scherz, Wilhelm Daniel ; Seepold, Ralf ; Crippa, Paolo
Detection of heart rate characteristics as an approach to distinguish between mental stress and physical activity (2016)
Scherz, Wilhelm Daniel ; Seepold, Ralf
Biological data tracing and pattern recognition in real-time (2016)
Scherz, Wilhelm Daniel ; Soria Morillo, Luis Miguel ; Seepold, Ralf
Stress is a recognized as a predominant disease with growing costs of treatment. The approach presented here is aimed to detect stress using a light weighted, mobile, cheap and easy to use system. The result shows that stress can be detected even in case a person’s natural bio vital data is out of the main range. The system enables storage of measured data, while maintaining communication channels of online and post-processing.
Activity monitoring and phase detection using a portable EMG/ECG system (2019)
Scherz, Wilhelm Daniel ; Seepold, Ralf ; Crippa, Paolo ; Martínez Madrid, Natividad ; Biagetti, Giorgio ; Falaschetti, Laura ; Turchetti, Claudio
The investigation of stress requires to distinguish between stress caused by physical activity and stress that is caused by psychosocial factors. The behaviour of the heart in response to stress and physical activity is very similar in case the set of monitored parameters is reduced to one. Currently, the differentiation remains difficult and methods which only use the heart rate are not able to differentiate between stress and physical activity, without using additional sensor data input. The approach focusses on methods which generate signals providing characteristics that are useful for detecting stress, physical activity, no activity and relaxation.
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