Health Tech

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.

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.

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.

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 aim of the BeSENSHome project is to study and implement the implementation and development of innovative advanced systems and smart sensor networks to ensure environmental comfort within residences, day care centres, workplaces and facilities accommodating people with neurocognitive disabilities. In order to achieve this innovative goal, such systems must allow for (i) accurate customisation based on the needs of the occupants, defining a strategy that puts individuals at the centre, and (ii) control of the built environment.Thanks to artificial intelligence (AI), coupled with the sensor network, the environment will be able to learn the preferences or requirements of the occupant, identifying stressful conditions, adjusting environmental conditions and alerting possible caregivers in case their intervention is needed, before any potentially dangerous conditions can occur. The integration of such a sensor network with the furniture of the rooms will be architecturally detailed to ensure its inclusion in existing environments. To achieve these objectives and make the system as useful and user-friendly as possible, a participatory research approach will be applied throughout the project. https://besenshome.units.it/ The BeSENSHome project is co-financed by the European Regional Development Fund as part of the Interreg VI-A Italy-Austria 2021-2027 cooperation program.

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.

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.

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.

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.

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.

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.

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.

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.

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.