Health Tech

Technology is playing an increasingly important role in injury prevention in sport. Modern methods help to identify risks at an early stage, control strain and optimise individual training. One key area is analysing movement using camera systems, sensors and artificial intelligence. This technology makes it possible to identify incorrect loads and unfavourable movement patterns before they lead to injury. Wearables such as smartwatches and sensors in shoes or clothing record parameters such as step frequency, load and muscle activity in real time. Strength and fatigue diagnostics also play a crucial role. Dynamic force plates, electromyography (EMG) and other biomechanical tests help to recognise muscular imbalances or overloads and counteract them in a targeted manner. Another important aspect is data analysis using artificial intelligence. AI systems analyse large amounts of data and help to determine individual risk factors. This enables trainers and sports physicians to take more precise preventative measures. Finally, regeneration technology also makes a significant contribution to injury prevention. Methods such as cold and heat treatments, compression systems and electrical muscle stimulation (EMS) support recovery and reduce the risk of injury. By using modern technologies, injuries in sport can be avoided in a targeted manner, performance can be improved and the risk of injury can be minimised.

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 anterior cruciate ligament (ACL) is instrumental in stabilizing the knee. To this end, it prevents forward sliding of the lower leg, as well as disproportionate rotation of the lower leg relative to the thigh. Thus, a cruciate ligament injury impairs the proper range of motion. A tear of the anterior cruciate ligament represents a very common ligament injury at the knee joint. To restore stability, cruciate ligament reconstruction is performed in most cases. However, 25% of patients suffer a re-injury (Vavken et al., 2012). With the help of an additional surgical procedure, lateral tenodesis, the risk of re-injury can be reduced (Chen et al., 2021, Getgood et al., 2020) by distributing the load between the graft and the repositioned tendon (Marom et al., 2020). On the other hand, this procedure is associated with additional OR time, implant cost, and morbidity (additional access, increased pain). This project aims to improve and simultaneously automate the decision-making processes in cruciate ligament surgery using advanced AI-based algorithms. The system is primarily aimed at optimizing the decision as to whether a tenodesis is necessary or not. In concrete terms, an improved version of the tendodesis score is to be determined from the patient data entered. For this purpose, a program is trained on the basis of artificial neural networks, which subsequently evaluates and weights the risk factors when the data of new patients are provided, and subsequently arrives at a better assessment.

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.

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.