Health Tech

Technology has become an intrinsic part of our lives and increasingly allows holistic, preventive and not least integrative solutions. The focus is on people themselves - not only in their role as patients or athletes. At the same time, the available technological and information technology options have developed rapidly and the acceptance of their use in medicine, health and sports is increasing.

The research focus Health Tech is dedicated to the challenge of combining innovative technologies with trends in medicine, health care, sports and related fields and to develop products and services from them in cooperation with partners from industry and research or to support their further development. The overriding goal is to maintain and/or restore people's health on the one hand, and to promote sport in society through the use of technology and help athletes in top-level sport to achieve first-class performance on the other.

Sports Technology

Sport as part of our health is experiencing a technological boom. At the same time, highly monitored athletes are already a reality in elite sports. Data acquisition and data analysis play a central role here and are increasingly being transferred to mass sports. The research focus is already supporting many partners in industry, science and associations both in the application of new technologies in elite sports and in the transfer of these technologies to mass sports. Topics such as artificial intelligence, digital twins or virtual reality play a key role in sports and reflect the competencies of the research fields.

Robotics in Health

Medicine has relied on the use of robotics and telemanipulators in surgical applications for quite some time. This trend is continuing throughout the healthcare sector, with service and care robots becoming increasingly important. Another growth area is therapy robots, which allow therapy at home and thus enable rehabilitation away from the daily clinical routine.

Medical Devices

Medical devices are a fascinating success story at the interface between medical and technological professionals that focuses on improving people's quality of life. One goal of the research focus is to support this field in translational research from the idea to the market-ready product. In particular, the focus is on the development of methods that can improve the efficiency of the development process in this highly regulated field. Digital twins for the product development of technology-based and individualized therapies are as important as technologies for the training of medical professionals and the improved data-driven development of technologies with the involvement of medical professionals in the development process.

Contact
Prof.  Bernhard Hollaus, PhD | Health & Sports Technology Bachelor's program Medical-, Health- and Sports Engineering
Prof. Bernhard Hollaus, PhD Health & Sports Technology +43 512 2070 - 4431

If you have any questions regarding this research area, please contact us: healthtech@mci.edu


Prof.  Bernhard Hollaus, PhD | Health & Sports Technology Bachelor's program Medical-, Health- and Sports Engineering
Prof. Bernhard Hollaus, PhD Health & Sports Technology +43 512 2070 - 4431
 Anna-Sophie Käferböck, BSc MSc | Doctoral Student Bachelor's program Medical-, Health- and Sports Engineering
Anna-Sophie Käferböck, BSc MSc Doctoral Student +43 512 2070 - 4444
Prof. Dr. Dipl.-Ing. Daniel Sieber | Head of Department & Studies Bachelor's program Medical-, Health- and Sports Engineering
Prof. Dr. Dipl.-Ing. Daniel Sieber Head of Department & Studies +43 512 2070 - 4400
 Manuel Berger, BSc MSc PhD | Teaching & Research Assistant Bachelor's program Medical-, Health- and Sports Engineering
Manuel Berger, BSc MSc PhD Teaching & Research Assistant +43 512 2070 - 4441
Prof.  Yeongmi Kim, PhD | Medical Devices & Control Engineering Bachelor's program Medical-, Health- and Sports Engineering
Prof. Yeongmi Kim, PhD Medical Devices & Control Engineering +43 512 2070 - 4432
Dr. techn. Thomas Senfter | Teaching & Research Assistant Bachelor's program Industrial Engineering & Management
Dr. techn. Thomas Senfter Teaching & Research Assistant +43 512 2070 - 4155
Dipl.-Ing. Dr. Eva Graf | Medical, Health and Sport Engineering Bachelor's program Medical-, Health- and Sports Engineering
Dipl.-Ing. Dr. Eva Graf Medical, Health and Sport Engineering +43 512 2070 - 4434
 Jonas Kreiner, BSc | Laboratory Engineer Bachelor's program Medical-, Health- and Sports Engineering
Jonas Kreiner, BSc Laboratory Engineer +43 512 2070 - 4451
 Jasper Volmer, MSc | Teaching & Research Assistant Bachelor's program Medical-, Health- and Sports Engineering
Jasper Volmer, MSc Teaching & Research Assistant +43 512 2070 - 4446
 Thomas Hausberger, BSc MSc | Project Assistant Bachelor's program Medical-, Health- and Sports Engineering
Thomas Hausberger, BSc MSc Project Assistant
Dott. Mag. Yunus Schmirander, BSc | Teaching & Research Assistant Bachelor's program Medical-, Health- and Sports Engineering
Dott. Mag. Yunus Schmirander, BSc Teaching & Research Assistant +43 512 2070 - 4442
 Simon Winkler, BSc MSc | Teaching & Research Assistant Bachelor's program Medical-, Health- and Sports Engineering
Simon Winkler, BSc MSc Teaching & Research Assistant +43 512 2070 - 4445

Smart Golf Club
Duration:
2023

Project Lead:
Yannic Heyer, BSc MSc
FH-Prof. Bernhard Hollaus, PhD

Description:
The goal is to develop a machine leaming model for the classification of IMU data recorded at a golf club. After the swing of the golf club the impact offset between club head and ball should be processed into three classes: Outside, Center, Inside. In addition, a housing is to be designed and manufactured that enables a secure and reproducible attachment of the IMU sensor to the shaft of the golf club.

Messrodel V2
Duration:
2022 - 2024

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Description:
The aim of the "Messrodel" project is to generate knowledge about the behavior of a luge in the ice channel. On the one hand, the behavior of the luge is to be made measurable through the use of appropriate sensor technology; on the other hand, it should also be possible to summarize, process, store and analyze measurement results. In addition, the behavior of the luge is to be simulated using standard simulation methods in mechanical engineering. Ideally, this should result in a model that can also be validated by the measurements.

Quarterceive 2.0
Duration:
2017 - 2018

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Description:
The goal of the project is on the one hand to develop an app and the underlying hardware, on the other hand to gain scientific knowledge in the field of sports science in American football. With the core functionalities of the app, it should be possible to send training machines appearances and commands on the basis of evaluable data.

RESPIT - Drowning Prevention
Duration:
2021 - 2022

Project Lead:
FH-Prof. Yeongmi Kim, PhD

Description:
The aim of this project was to reduce the drowning risk of children who just learned to walk. The risk is substantial as they can usually not swim yet. This results in the fact that drowning is one of the main causes of accidental deaths for children. To tackle this problem, a device that monitors respiration as soon as the child wearing it is in the water was developed. By using a stretch sensor sewn into casual swimwear, respiratory movement is measured and processed. To detect respiratory distress and the onset of drowning, two different approaches have been developed. One is based on processing the signal's slope and the other one on a convolutional neural network. To send an alarm in case of detection, an underwater wireless communication system was developed which is based on ultrasonic acoustic waves. The receiver of the system is then emitting an acoustic and visual alarm signal to minize time to rescue.

The OpenEar Project
Duration:
2016 - 2024

Project Lead:
FH-Prof. Dr. Dipl.-Ing. Daniel Sieber

Description:
An Open Science project for the creation of high-fidelity models of the human anatomy library for the temporal bone as a basis for research and development in image guided surgery, virtual reality surgical training and more. Models are based on multimodal 3D reconstructed fusion imaging including color images from micro-slicing as well as Cone Beam Computed Tomography images and resulting segmented voxel based, as well as triangulated models.


Project partners:
Medizinische Hochschule Hannover, Klinik für Hals-, Nasen- und Ohrenheilkunde
Universitäten Ausland
Rigshospitalet Copenhagen, ENT Department
Universitäten Ausland

Publications/literature:
Sieber D, Erfurt P, John S, Ribeiro dos Santos G, Schurzig D, Sørensen MS, Lenarz T. The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing. Nature Scientific Data (2019). https://doi.org/10.1038/sdata.2

DigitalBikeTwin
Duration:
2023 - 2024

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Description:
Due to the bike and e-bike boom in recent years, bicycle thefts in Austria also remain at a high level. According to data from the Federal Criminal Police Office, 17,595 bicycles were stolen in 2021. These are only the official figures. Many crimes are not even reported to the police. The traffic clubs even assume that the number of unreported cases is ten times higher. In addition, the detection rate for bicycle thefts is very low at around 9%. Despite a quick report to the police, an exact description of the bike or the frame number, the victims usually do not get their bike back. What remains is a costly new purchase and the uneasy feeling of not being able to do enough to prevent another theft. According to the German Federal Criminal Police Office, the annual loss amounts to between €10 and €14 million (estimated number of unreported cases: €140 - €196 million). The digitalization of the (e-)bike is now a decisive factor for manufacturers, as it significantly influences customers' purchasing decisions. Many large and small digital "helpers" around the battery management and the configuration of the drive system of e-bikes, GPS trackers and tire pressure sensors to the fusion of the bike with the rider and the additional input of vital parameters or the active interaction of the bike and its rider with the immediate environment, let the bike become an IoT system. The overall goal of DigitalBikeTwin is to develop a solution that digitally maps components of the bike, its rider and the environment, integrating them into a consistent overall solution and thus representing the digital twin of the bike. This goal is achieved by implementing the hardware developed by emergo technologies in different versions, for e-bikes with direct communication with the drive system (motor, battery, display, etc.) and communication with other actuators/sensors on the bike, the person or the environment.

dVRK - The da Vinci Research Kit
Duration:
2016 - 2024

Project Lead:
FH-Prof. Dr. Dipl.-Ing. Daniel Sieber
FH-Prof. Yeongmi Kim, PhD

Description:
MCI is part of an alliance of about 40 institutions worldwide which have access to the daVinci Research Kit (dVRK) which allows working on one of the most exciting and sophisticated surgical robot platforms. The system assists the surgeon, sitting at a master console and viewing the procedure through a 3D endoscopic panoramic viewing system while controlling the system's precise robotic arms through hand movements resultting in complex microsurgical operations.The dVRK enables a broad range of research, from the exploration of innovative new ways of performing information- and image-guided surgeries to developing novel surgical instrumentation, innovative user interfaces, and even futuristic surgical task automation methods and their potential impacts.


Project partners:
Johns Hopkins University, Department of Computer Science
Universitäten Ausland

Publications/literature:
S. Kohlgrüber ,Y. Kim, and P. Kazanzides (2021) : Model-based Design and Digital Implementation to Improve Control of the da Vinci Research Kit Telerobotic Surgical System, IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 12435-1

Spot - The Robotic Dog
Duration:
2021 - 2024

Team:
Ephraim Westenberger, BSc

Description:
SPOT is an advanced and highly customizable robotic system which can operate autonomously based on stereoscopic and proximity cameras, inertial measurement units and other sensors. With a broad range of possibilities to add capabilities to the system through defined interfaces of the system, MCI aims at exploring the use of SPOT as a personal robot in medical technologies. The system's Python API provides access to the high-level functionalities like controlling SPOT's movement and accessing the cameras and sensors of the robot. Custom developed hardware attachments, called payloads, can be connected via different communication interfaces of the robot. This enables students to create their own software and hardware projects for one of the most exciting robotic platforms on the market. SPOT has already been adapted for applications such as a robotic dog for the blind, for autonomous "follow-me" applications and has also enjoyed skiing at Nordkette - Innsbruck's most challenging skiing terrain. Furthermore, our SPOT User Group is a student group which is run by students for students. The students themselves can bring their ideas, interests and use cases to the group, creating a learning environment free from university requirements and obligations. The project aims to generate knowledge in an interdisciplinary group of students and in addition, to further build long-term competencies in the field of Medical Robotics, Personal Robots and Assisted Living.


Heatable Gloves for Professionals
Duration:
2022 - 2023

Project Lead:
Dr. techn. Thomas Senfter
FH-Prof. Bernhard Hollaus, PhD

Team:
Sandro Tobias Müller, BSc

Jonas Kreiner, BSc

Kevin Fischler, BSc

Description:
The aim of this cooperative project is to develop a heatable glove for emergency organizations that combines the application properties of a work glove with the thermal properties of a heatable glove. This should enable alpine emergency forces to better carry out their tasks (from caring for the injured to accident investigations by the alpine police). In cooperation with Zanier and Aberjung, a new type of product can be developed for the market that is optimally tailored to the needs of customers.

Skijump Judge
Duration:
2022 - 2023

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Description:
Video distance measurement in ski jumping is carried out via direct measurement of the landing area or digitally by an operator. It is the task of the operator, who monitors the landing zone of the ski jumper with up to four cameras, to manually confirm the touchdown of each jump. The operator then selects the relevant camera for this landing and continues to view the video sequence of the landing frame by frame. The goal is to select the frame in the video sequence where the ski jumper fully touches the ground with both skis to determine the jump distance. To do this, the operator selects the point between the heel of the front boot and the toe of the rear foot to use software to calculate the jumped distance. This distance can be determined to within 0.5 meters based on the camera recording at 50 fps. An automation of the described steps for video distance measurement should serve to support the operator in his work and thus improve the reliability of the system. Through the development of such a system, further advantages for the ski jumping sport can be gained. These were mainly initialized by the professional input of the former ski jumper Thomas Hofer, who sees an automated video width measurement in training situations as an enormous progress for athletes and coaches. The current measurement method in training sessions is a purely visual measurement of the distance by the coach. Automation and digitalization can provide athletes with much more accurate feedback and thus a greater opportunity to improve their jumps. Thus, not only professional sports but also junior and youth sports can benefit from a software solution. In addition to measuring distances, it is important to be able to objectively determine the athletes' posture scores. This is confirmed, among others, by the declarations of support from the ÖSV national team, the ÖSV and the Schigymnasium Stams. This objective analysis of the posture scores is described as particularly relevant and as an effective training tool for improving posture scores. In combination with the automated distance measurement, a more accurate assessment of the athletes' overall performance is thus possible.

Smart Trucks
Duration:
2022 - 2023

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Team:
Gabriel Belmino Freitas

Ephraim Westenberger, BSc

Lennart Fresen, BSc

Description:
The goal of this cooperation project is to develop a performance tracker for the fun sports sector. This should create the basis for building platforms similar to Runtastic or Strava for many different types of fun sports. The key to this basic technology is the combination of motion sensors with a neural network. In the course of the project, data from skaters of different ages, levels and genders will be recorded at many different locations. From this data the neural network will be developed to evaluate a trick. Due to the cooperation with xdouble and Stefan Ebner, the project is very broadly positioned and can therefore optimally master corporate, scientific but also training-related challenges.

Optimal Start
Duration:
2021

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Description:
The goal of the Optimal Start project is to develop a prototype training tool for the start of luge. The tool will synchronize data from an existing motion capturing system with a video and display them together. Thus, individual errors of the athlete at the start should not only be visible in the signal, but also visually show the athlete his respective body pose. It is hoped that the tool will provide much more direct feedback to the athletes, which is also better for their development.

Initial Neonatal Ventilation Assistant (IVNA)
Duration:
2024

Project Lead:
Anna-Sophie Käferböck, BSc MSc

Description:
Efficient ventilation of neonates in a resuscitation situation remains a challenge for hospital staff. The state of the art is a manual hose system with a metering valve that requires one person to provide continuous ventilation. In addition, the nature of neonatal lung tissue requires flattening of the pressure curve during ventilation to prevent rupture. IVNA is committed to automating the entire ventilation process to provide high-quality ventilation that is adapted to the patient.

VRodel
Duration:
2022 - 2024

Project Lead:
FH-Prof. Bernhard Hollaus, PhD

Team:
David Mikulic

Maximilian Gallinat

Jonas Kreiner, BSc

Description:
Luging has been steadily increasing in popularity for several years. This has also led to a significant increase in the number of luging accidents, some of which are fatal. Therefore, the VRodel project was created to learn the basic luging techniques in a virtual world to make luging safer in the real world.


  • Hollaus, B., Raschner, C., & Mehrle, A. (2018). Development of release velocity and spin prediction models for passing machines in American football. Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology. doi:10.1177/1754337118774448
  • Sieber D, Erfurt P, John S, Ribeiro dos Santos G, Schurzig D, Sørensen MS, Lenarz T. The OpenEar library of 3D models of the human temporal bone based on computed tomography and micro-slicing. Nature Scientific Data (2019). DOI: 10.1038/sdata.2018.297
  • Sieber D, Andersen SAW, Soerensen MS, Trier P. OpenEar image data enables case variation in high fidelity virtual reality ear surgery. Otology & Neurotology (2021). DOI: 10.1097/MAO.0000000000003175
  • Hollaus, B., Raschner, C., Mehrle, A. (2020, June). Development and Verification of a Highly Accurate and Precise Passing Machine for American Football, Proceedings of the 13th Conference of the International Sports Engineering Association 2020, 49, 94, doi:10.3390/proceedings2020049111
  • M. Panny, I. Nagiller, M. Nagiller, and Y. Kim, Home rehabilitation system for the upper extremity focusing on technology-aided assessment of spasticity, Current Directions in Biomedical Engineering
  • Lee, H., Eizad, A., Park, J. Kim, Y. Hwang, S., Oh, M., Yoon, J., Development of a Novel 2-Dimensional Neck Haptic Device for Gait Balance Training, IEEE Robotics and Automation Letters (RA-L), ISSN: 2377-3766
  • Su, H., Qi, W., Schmirander, Y., Ovur, S.E., Cai, S. and Xiong, X. (2022). A human activity-aware shared control solution for medical human–robot interaction. Assembly Automation, 42(3), pp. 388-394
  • Hollaus B, Heyer Y, Steiner J, Strutzenberger G. Location Matters—Can a Smart Golf Club Detect Where the Club Face Hits the Ball? Sensors. 2023; 23(24):9783.
  • Ganser A, Hollaus B, Stabinger S. Classification of Tennis Shots with a Neural Network Approach. Sensors. 2021; 21(17):5703. https://doi.org/10.3390/s21175703
  • Hollaus, B., Stabinger, S., Mehrle, A., Raschner, C. (2020, November). Using Wearable Sensors and a Convolutional Neural Network for Catch Detection in American Football. Sensors 2020, 20, 6722, doi:10.3390/s20236722

  • Hollaus, B., Eisenbraun J. (2020, September). Hochpräzises Passen durch Wurfmaschinen im American Football, presented online at Spinfortec, Bayreuth, Germany
  • Hollaus, B., Stabinger S, Eisenbraun J. (2020, September). Fangdetektion im American Football mit Wearables und AI, presented online at Spinfortec, Bayreuth, Germany
  • Eisenbraun, J.;Hollaus, B. (2021, September) Detection of Catches or Drops in American Football Using Data of Wearables and a Neural Network Approach. Paper presented online at the European College of Sport Science
  • Hollaus, B. (2021, September). Tennis Shot Classification using a wearable and neural networks. Paper presented online at European College of Sport Science
  • Seminar (a colloquium for Convergence Future Communication) - Stroke rehabilitation and assistive technology – Challenges and Opportunities, Kyunghee University
  • Kim Y.; Seminar - Medical Robotics, 2022 Global New Industry & New Technology, KIAT (Korea Institute for Advancement of Technology)
  • M. Panny, I. Nagiller, M. Nagiller, and Y. Kim, Home rehabilitation system for the upper extremity focusing on technology-aided assessment of spasticity - Full paper Oral Presentation - BMT 2022
  • M. Preiss, A. Walder, and Y. Kim, Haptically enhanced VR surgical training system Oral Presentation - Full paper Oral Presentation - BMT 2022

  • Patent Nr. EP2629737B1