Hochschule Reutlingen

Miniaturized computers can be built into everyday objects so that they can interact with the world. Nowadays, these devices can be used as biometric sensors, expanding the possibilities and applications in the field of medicine and biomedical computing, embedded in automotive platforms rewriting the future of mobility; or assisting the automation of regular tasks inside our homes for assisted or entertainment purposes. The IoT-Lab team is researching all these topics and enhancing current and future applications of mobile and distributed technologies.

Biomedical Computing

  • Biometric sensors and sensor integration
  • Bio vital signal acquisition and processing
  • Embedded systems and prototyping platforms
  • Telemedicine, eHealth/eCare

Automotive Computing

  • Driving assistive technologies
  • Driver’s emotional and behavioral tracking
  • Virtual car simulator installation
  • In-car communication and user interfaces

Smart Home & Living

  • Ambient Assisted Living: Aging society and demographic change
  • Internet of Things
  • Sensor and actor networking
  • Home automation and entertainment

Research Labs

The IOT-Lab research group has three physical laboratories at the University of Reutlingen, each one focused on a specialized topic.

AAL-Lab

IoT-Lab + SmaRTextiles@IoT

Future Mobility Lab

AAL-Lab

Demographic change is moving into the home. Daily life has many facets: orientation in space, eating, leisure, sleeping and also medical care are part of it. In the laboratory, realistic scenes are supported with appropriate technology. The goal is to lead a self-determined life at home.

The Ambient Assisted Living Lab (AAL-Lab) is a development and experimental laboratory. The research done in this lab helps remove barriers to the use of environmental support technologies by people with high assistance needs, including user, technology, network and market barriers for AAL solutions.

The AAL-Lab is built up as a small apartment including a smart kitchen, sleeping, eating and living areas, a bathroom, an observation room and an infrastructure room.

 

Read more

IoT-Lab + SmaRTextiles@IoT

Miniaturized computers can be built into everyday objects so that they can interact with the world. For example, a T-shirt can be used to record an ECG or a fabric flower can be used to measure the intensity of UV radiation. Innovative wearables are developed in the interdisciplinary SmartTextiles workshop of the Internet-of-Things Lab.

The IoT-Lab+SmaRT@IoT-Workshop is conceived as an interdisciplinary space with infrastructure for the development of embedded software, hardware and textile systems.

Future Mobility Lab

The driving simulator analyses driving behavior in realistic 3D scenarios. Driver-centered assistance systems are tested and further developed. Almost every reaction can be detected and evaluated in the simulator. Emotions are distinguished by sensors. Driving safety is improved and consumption is reduced.

The Future-Mobility-Lab consists of two driving simulators: one maker-style for rapid prototyping and a newly designed one with a cockpit using bio-based materials and interactive textile sensors.

 

Read more

Our Projects

We develop miniaturized computing systems that can be embedded into everyday objects, enabling them to sense and interact with their environment. These technologies open up new possibilities across various application areas and support future technological developments.

Current Projects

There are currently no active research projects.

Finished Projects

SLaH

InBio

IBH Living Lab "Active & Assisted Living": Individual project 1: Breaking down barriers

IBH Living Lab "Active & Assisted Living": Individual project 3: Home Health Living Lab

Cooperations

Our research is driven by strong collaborations with academic institutions and specialized competence centers. These partnerships bring together complementary expertise, foster knowledge transfer, and help translate scientific insights into practical applications.

  • KomZet SHL BW
  • Universidad de Sevilla
  • Hochschule Konstanz 

Publications

The Role of Digital Twins in Personalized Sleep Medicine (2022); Angel Serrano Alarcon, Natividad MartĂ­nez Madrid, Ralf Seepold, Juan A. Ortega - 10.1007/978-3-031-16855-0_

Assistive health systems for home-dwelling elderly: connecting training and monitoring technologies to a data integration platform; Petra Friedrich, Maksym Gaiduk, Ăngel Serrano AlarcĂłn, Daniel Scherz, Natividad Martinez Madrid, Ralf Seepold, Matthias Gaßner, Dominik, Fuchs -10.1016/j.procs.2022.09.359

Main requirements of end-to-end deep learning models for biomedical time series classification in healthcare environments; Angel Serrano Alarcon, Natividad MartĂ­nez Madrid, Ralf Seepold, Juan A. Ortega -10.1016/j.procs.2022.09.532

A Minimum Set of Physiological Parameters to Diagnose Obstructive Sleep Apnea Syndrome Using Non-Invasive Portable Monitors. A Systematic Review (2021); Ángel Serrano AlarcĂłn, Ralf Seepold, Natividad MartĂ­nez Madrid - 10.3390/life11111249

Design of a sleep apnoea detection system for a home environment (2021); Maksym Gaiduk, Lucas Weber, Ăngel Serrano AlarcĂłn, Ralf Seepold, Natividad MartĂ­nez Madrid, Simone Orcioni, Massimo Conti -10.1016/j.procs.2021.09.095

A Comparison of Objective and Subjective Sleep Quality Measurement in a Group of Elderly Persons in a Home Environment (2021); Maksym Gaiduk, Ralf Seepold, Natividad MartĂ­nez Madrid, Juan Antonio Ortega, Massimo Conti, Simone Orcioni, Thomas Penzel, Wilhelm Daniel Scherz, Juan JosĂ© Perea, Ăngel Serrano AlarcĂłn, Gerald Weiss - 10.1007/978-3-030-66729-0_35

Conversion from electrocardiosignals to equivalent electrical sources on heart surface (2020); Zhikhareva, G ; Kramm, Mikhail ; Bodin, Oleg ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; Chernikov, A ; Kupriyanova, Y ; Zhuravleva, N

Recognizing breathing rate and movement while sleeping in home environment (2020); Gaiduk, Maksym ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; Orcioni, Simone ; Conti, Massimo

Analysis of survey tools for recommender systems in the selection of ambient assisted living technologies (2020); Shkilniuk, Yurii ; Serrano AlarcĂłn, Ángel ; Gaiduk, Maksym ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

RR interval analysis for the distinction between stress, physical activity and no activity using a portable ECG (2020); Scherz, Wilhelm ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; Crippa, Paolo ; Ortega, Juan

Can Virtual Reality be used as a significant stressor for studies using ECG? (2020); Scherz, Wilhelm ; Corcoba Magaña, Victor ; Seepold, Ralf ; Martínez Madrid, Natividad ; Ortega, Juan

A portable ECG for recording and flexible development of algorithms and stress detection (2020); Scherz, Wilhelm ; Baun, Jannik ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; Ortega, Juan

The effects of the driver’s mental state and passenger compartment conditions on driving performance and driving stress (2020); Corcoba Magaña, Victor ; Scherz, Wilhelm ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; GarcĂ­a Pañeda, Xabiel ; Garcia, Roberto

Comparison of sleep characteristics measurements: a case study with a population aged 65 and above (2020); Gaiduk, Maksym ; Seepold, Ralf ; Ortega, Juan ; MartĂ­nez Madrid, Natividad

Embedded system for non-obtrusive sleep apnea detection (2020); Gaiduk, Maksym ; Orcioni, Simone ; Conti, Massimo ; Seepold, Ralf ; Penzel, Thomas ; MartĂ­nez Madrid, Natividad ; Ortega, Juan

Heart rate detection with accelerometric sensors under the mattress (2020); Conti, Massimo ; Aironi, Carlo ; Orcioni, Simone ; Seepold, Ralf ; Gaiduk, Maksym ; MartĂ­nez Madrid, Natividad

Machine learning and data fusion techniques applied to physical activity classification using photoplethysmographic and accelerometric signals (2020); Biagetti, Giorgio ; Crippa, Paolo ; Falaschetti, Laura ; Focante, Edoardo ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf ; Turchetti, Claudio

Telemedicine system model to help children with autism spectrum disorders (2019); Seepold, Ralf ; Lebedev, Georgy ; MartĂ­nez Madrid, Natividad

Home hospital e-health centers for barrier-free and cross-border telemedicine (2019); Seepold, Ralf ; Gaiduk, Maksym ; Ortega, Juan Antonio ; Conti, Massimo ; Orcioni, Simone ; MartĂ­nez Madrid, Natividad

Artefaktkorrektur und verfeinerte Metriken fĂŒr ein EEG-basiertes System zur MĂŒdigkeitserkennung (2019); Pasler, Paul ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Activity monitoring and phase detection using a portable EMG/ECG system (2019); Scherz, Wilhelm Daniel ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; Crippa, Paolo ; Biagetti, Giorgio ; Falaschetti, Laura ; Turchetti, Claudio

HĂ€usliche Versorgung von Kindern mit Autismus-Spektrum-Störungen (2019); MartĂ­nez Madrid, Natividad ; Seepold, Ralf ; Lebedev, Georgy

ECG sensor for detection of driver's drowsiness (2019); Gromer, Markus ; Salb, David ; Walzer, Thomas ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf

Non-invasives System fĂŒr die kontinuierliche Schlafanalyse (2019); Gaiduk, Maksym ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad ; Ortega RamĂ­rez, Juan Antonio ; Penzel, Thomas

Recognition of sleep/wake states analyzing heart rate, breathing and movement signals (2019); Gaiduk, Maksym ; Seepold, Ralf ; Penzel, Thomas ; Ortega RamĂ­rez, Juan Antonio ; Glos, Martin ; MartĂ­nez Madrid, Natividad

Embedded system to recognize movement and breathing in assisted living environments (2019); RodrĂ­guez de Trujillo, Eva ; Seepold, Ralf ; Gaiduk, Maksym ; MartĂ­nez Madrid, Natividad ; Orcioni, Simone ; Conti, Massimo

mHealth for therapeutic adherence (2019); Orcioni, Simone ; Pellegrini, Roberto ; Seepold, Ralf ; Gaiduk, Maksym ; MartĂ­nez Madrid, Natividad ; Conti, Massimo

Personalized health service in assistive environments and telemonitoring of sleep patterns (2019); Seepold, Ralf ; Gaiduk, Maksym ; MartĂ­nez Madrid, Natividad

Open wearables mobile platform to support personalized medicine (2019); Junger, Denise ; MartĂ­nez Madrid, Natividad ; Malek, Nisar ; Thies, Christian

Integrated system for individual decentralized monitoring for the personalized medicine (2019); Junger, Denise ; MartĂ­nez Madrid, Natividad ; Malek, Nisar ; Thies, Christian

Textile Sensor Platform (TSP) - development of a textile real-time electrocardiogram (2018); Walzer, Thomas ; Thies, Christian ; Meier, Klaus ; MartĂ­nez Madrid, Natividad

A review of health monitoring systems using sensors on bed or cushion (2018); Orcioni, Simone ; Conti, Massimo ; MartĂ­nez Madrid, Natividad ; Gaiduk, Maksym ; Seepold, Ralf

Non-invasive sleep analysis with intelligent sensors (2018); Gaiduk, Maksym ; Seepold, Ralf ; Orcioni, Simone ; Conti, Massimo ; MartĂ­nez Madrid, Natividad

Das Smartphone als Personal Gateway zur Vermittlung zwischen Wearables und SmartHome (2018); MartĂ­nez Madrid, Natividad ; Walzer, Thomas

A review of health monitoring systems using sensors on bed or cushion (2018) ; Conti, Massimo ; Orcioni, Simone ; MartĂ­nez Madrid, Natividad ; Gaiduk, Maksym ; Seepold, Ralf

WearIT - a rapid prototyping platform for wearables (2018); Leber, Isabel ; MartĂ­nez Madrid, Natividad

Thematic issue on human-centred ambient intelligence: cognitive approaches, reasoning and learning (2017); Falomir, Zoe ; Ortega RamĂ­rez, Juan Antonio ; MartĂ­nez Madrid, Natividad ; Guesguen, Hans

A case study in smart textile design process (2017); Walzer, Thomas ; Fischer, Susanne ; MartĂ­nez Madrid, Natividad

Guideline for the conceptual development of user interfaces for mobile medical applications (2017); Statti, Armando ; MartĂ­nez Madrid, Natividad

Sleep phase identification based on non-invasive recordings (2017); Klein, Agnes ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf ; Gaiduk, Maksym

Classification of sleep stages: commonly used methods and main aims for the improvement(2017); Gaiduk, Maksym ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Creating recommendations in an energy-efficient and safety relevant driving system while considering driver stress and driver reaction (2017); Yay, Emre ; MartĂ­nez Madrid, Natividad

Requirements analysis for user interfaces in mobile ehealth applications (2017); Statti, Armando ; MartĂ­nez Madrid, Natividad

Parameter set selection and classification of sleep phases tracing biovital data (2017); Klein, Agnes ; Penzel, Thomas ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf

A sensor grid for pressure and movement detection supporting sleep phase analysis (2017); Gaiduk, Maksym ; Kuhn, Ina ; Seepold, Ralf ; Ortega RamĂ­rez, Juan Antonio ; MartĂ­nez Madrid, Natividad

Heart rate spectrum analysis for sleep quality detection (2017); Scherz, Wilhelm Daniel ; Fritz, Daniel ; Velicu, Oana Ramona ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Stress-aware generation of recommendations in a driving system to increase user acceptance (2016); Yay, Emre ; MartĂ­nez Madrid, Natividad

A rule-based assistant system for managing the clothing cycle (2016); Walzer, Thomas ; Yay, Emre ; MartĂ­nez Madrid, Natividad

Stress determent via QRS complex detection, analysis and pre-processing (2016); Scherz, Wilhelm Daniel ; Ortega RamĂ­rez, Juan Antonio ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Stress map based information system for increasing road safety (2016); Datko, Patrick ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Personal recommendation system for improving sleep quality (2016); Datko, Patrick ; Scherz, Wilhelm Daniel ; Velicu, Oana Ramona ; Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Experimental sleep phases monitoring (2016); Velicu, Oana Ramona ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf

Influence of stress in driving behaviour (2016); Yay, Emre ; MartĂ­nez Madrid, Natividad ; Ortega RamĂ­rez, Juan Antonio

Detecting the adherence of driving rules in an energy-efficient, safe and adaptive driving system (2016); Yay, Emre ; MartĂ­nez Madrid, Natividad ; Ortega RamĂ­rez, Juan Antonio

Sleep stages classification using vital signals recordings (2015); Klein, Agnes ; Velicu, Oana Ramona ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf

Detection of variations in holter ECG recordings based on dynamic cluster analysis (2015); Hermann, Matthias ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf

Case management techniques capturing individual dysfunctionality (2015); Seepold, Ralf ; MartĂ­nez Madrid, Natividad

Heart rate variability indicating stress visualized by correlations plots (2015); Scherz, Wilhelm Daniel ; Ortega RamĂ­rez, Juan Antonio ; MartĂ­nez Madrid, Natividad ; Seepold, Ralf

An adaptive driving system regarding energy-efficiency and safety (2013); Yay, Emre ; MartĂ­nez Madrid, Natividad

A collaborative standard-based mobile telemonitoring platform (2013);  Kolesnik, Maksim ; MartĂ­nez Madrid, Natividad

Job & Thesis Opportunities

Interested in a job or thesis?

Jobs

Theses

Objective 

The aim of this work is to investigate whether there are differences in the detection of obstructive sleep apnea between male and female patients. The age of the patients will also be taken into account to check whether the symptoms become more severe with age or whether this is due to other factors (overweight, etc.). Therefore, the main objective is to find the best features from the signals collected from patients and develop machine learning architectures to obtain the best results in the prediction of sleep apnea. Either by distinguishing between men and women or by using data from all patients in general. Ultimately, the study should present the differences in predicting apnea by distinguishing between men and women, as well as by age ranges. 

Description 

This work is interesting since detection in female patients is more difficult to detect than in males due in large part to the fact that obstructive apnea episodes are shorter, so they become almost imperceptible. A clear example is that while snoring, gasping, and witnessed apneas are classic symptoms exhibited often by men the signs differ slightly for women. Polysomnography data from the National Sleep Research Resource (NSRR) can be used for this work and research should be done on machine learning models that generate good results in predicting sleep apnea in women. A study on the performance of the model on male and female data should also be included in this work. 

Resources: 

NSRR :  

Papers of interest:  

Objective 

Given the impossibility of having a specific test to detect insomnia, apart from examinations by the doctor, questionnaires... Typically, polysomnography data has not been adequate to detect insomnia, however, this is changing with the advent of artificial intelligence. As a consequence of this, in this work the objective is to investigate machine learning techniques for the detection of insomnia. For this it will be necessary to investigate possible datasets with polysomnography or actigraphy data to study which are the best signals to be used with the algorithms for the detection of insomnia. The goal would be to use as few signals as possible. 

Description 

The Sleep Research Resource (NSRR) can be used to search for datasets. Once the dataset to be used has been selected, the input of the models must be defined, in addition to the selection of the architecture that can work best. The ultimate goal would be to train machine learning models that will yield the best possible results and be a future aid to clinicians. Therefore, models that are explainable will be necessary. For the detection of insomnia, one can classify the sleep phases or search for arousals. Therefore, a clear objective of this work would be to search for the best features for the detection of insomnia. 

Resources: 

NSRR :  

Papers o interest:  

Objective 

The student aims at finding out a correlation between mindfulness practises and exercise and how it can affect positively to have a better rest. 

Description 

The idea is that the student can be the subject but also the person who carries out the study. A device to measure the quality of sleep and other physiological measures can be used. The student thinks about ways to register the information, for example, the student can do mindfulness before sleeping for several days and keeps their feeling in a diary. Then, the student can compare the results with those days when mindfulness was not practised. An experiment plan should be done. The idea is that the student can give format to the data and also include behavioural variables into the datasets. By doing this, the student would have their own datasets based on the data modelling chosen to make their analysis (over data science techniques) apart from those got by the device. A smartwatch could provide information about the physical activity and also information about the sleep.  

Resources:

Objective:  

To Enable automated aggregation, replication, and distribution of clinical data among researchers and practitioners with greater traceability and controlled provenance tracking, taking advantage of blockchain technology. 

Description: 

Clinical trial management generates large amounts of data, requiring healthcare administrators to maintain reliable, consistent records for peer review and regulatory compliance. Blockchain tools, in conjunction with electronic data capture (EDC), can help improve clinical data regulation in this sense. Therefore, the idea is to provide some insight of the ways to implement this kind of systems. 

Resources: 

https://onlinelibrary.wiley.com/doi/10.1002/9781119675525.ch13 

https://www.jmir.org/2021/8/e17475/