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Technology to support high-quality nursing care

University of Applied Sciences Upper Austria, Hagenberg Campus.

Nurses in care homes can often face extremely demanding workloads, and effective use of smart technology can play a vital role in easing their daily pressures. We spoke to Martina Zeinzinger and Jana Koch about their work in understanding how new information systems need to be designed to support nursing staff and help them provide high-quality care. Caring for elderly residents in care homes places a considerable workload on nursing teams, who balance many responsibilities in providing attentive, highquality care. Smart sensor technologies are emerging as valuable tools in this effort, offering detailed information on the condition of residents and helping staff respond quickly to changing needs. This is the focus of the EU-funded Smart Care Assist project, which is developing an innovative information system using smart textiles. “We aim to develop a device that truly supports nursing staff in their daily work,” says Martina Zeinzinger, a researcher at the Embedded Systems Lab, Hagenberg Research Centre at the University of Applied Sciences Upper Austria, who leads the project. The concept integrates data from textile sensors within care beds to detect presence, humidity, and movement, providing additional information to caregivers. Alongside the technical development, the team is conducting interviews and collecting feedback from caregivers to better understand how to meet their practical needs. The goal is to process and visualise this data in an intuitive and supportive way. “A nurse can then identify which residents might need help at a particular time,” explains Zeinzinger.

Enhancing care and prevention in collaboration with nursing staff Detecting both moisture and movement is also crucial for identifying the risk of bedsores, or pressure ulcers, a significant concern in long-term care. “If people lie for too long in one position, pressure can build up, damaging the skin and tissue. This is very painful and it can take quite a long time to heal,” Zeinzinger explains. The project aims

to develop a system that monitors movement patterns using existing data, helping to identify residents at risk and allowing staff to take preventative action. “We want to collect and present information in a way that caregivers find genuinely beneficial. In this case they can see when a person is moving less than might be expected, indicating that they might need more attention,” says Zeinzinger. “Changed movement can also be linked to other health conditions. If we can quantify this accurately, we believe it could provide valuable health insights. In areas such as incontinence care – which can be distressing for residents – data from smart bed inserts may also help staff identify when care is truly needed, potentially reducing unnecessary interventions. Presence detection supports dementia care by balancing independence and safety. For instance, if a patient doesn’t return to bed within a set time, nurses are notified in case the person has become disoriented.” In practice, this means developing the best methods to combine sensor data from the smart bed inserts, which are developed by the project partner Texible GmbH, and presenting it through clear, supportive visualisations that fit seamlessly into nursing workflows. The visualisation of the data is led by project partner C&S Computer and Software GmbH, a provider of innovative software solutions for the care sector, ensuring that the information presented to staff is both accessible and actionable. The sensors have been tested so far in two nursing homes, with the project team gathering data to refine the technology and ensure it accurately identifies humid and dry environments and reliably detects presence and movement. A central part of the project is its collaborative design process

with nursing staff. “Too often, new devices are introduced with the best intentions, but without enough feedback from users,” says Zeinzinger. “Sometimes, nurses find these tools add to their workload instead of reducing it.” To avoid this, the Smart Care Assist team has conducted interviews and surveys with nursing staff to gather their input throughout the development process. “We have established open discussions so that everybody is kept informed and involved,” outlines Jana Koch of C&S Computer and Software GmbH. “Our goal is to deepen our understanding of how a system must

be designed to truly meet the needs of care professionals.” Researchers are currently analysing the various strands of data and are defining the next steps. The plan is to improve the system based on the available data, then test it in nursing homes and hospitals, initially through simulations with staff rather than with actual residents. The Living Care Lab, developed by the Faculty for Medical Technology and Social Sciences at the University of Applied Sciences Upper Austria, provides an ideal environment to refine and improve the device. “We will use the Living Care Lab to conduct additional tests and fine-tune the system,” continues

for longer, while Zeinzinger highlights its potential for training and education. “Nurses might gain confidence in their decision-making when supported by sensor data,” she outlines. “Using Living Care Lab methods, training on new assistance systems can be introduced very effectively.” There is significant scope for further development, and while the project itself is set to conclude in the summer 2026, the research will continue. The research team is already exploring additional capabilities, such as non-intrusive fall detection, to further expand the system’s usefulness. “Falls pose a danger because they often

“We are looking for answers to the question of how smart assistance systems for care beds have to be designed to relieve caregivers and at the same time support optimal care for patients. Zeinzinger. “We want to provide an effective tool that provides useful information for nursing staff, as they know their residents better than we do and understand their usual activity levels. We aim to combine present information from sensors in an intuitively understandable way.”

Nursing homes - and beyond While the project’s primary focus is on nursing homes, the potential application of the device extends further. The same technology could enhance care in hospitals or in domestic settings for example, enabling elderly people to remain in their own homes

result in serious injuries, but are sometimes not noticed for a fairly long time.“ An effective, non-intrusive sensor that respects the privacy of carers and care recipients could support nurses to take action earlier and improve the safety and quality of life of residents. This remains a central aim for nursing homes, and Zeinzinger says there is great interest in using technology to improve care. “The nursing staff participating in this project are all very open to using and testing new solutions,” she stresses. “There’s a shared understanding that technology can ease workloads and strengthen care quality.”

Smart Care Assist

Assistance system for caregivers

Project Objectives

Smart Care Assist seeks answers to the question of how nursing beds with smart textiles can relieve the burden on caregivers while simultaneously supporting optimal patient care.

Project Funding

Smart Care Assist is an Interreg Bavaria– Austria research project co-financed by the EU. Project ID: BA0100035

Project Partners

• FH OÖ Forschungs & Entwicklungs GmbH, Roseggerstraße 15, 4600 Wels (Lead Partner) • Texible GmbH https://www.texible.com/ • C&S Computer und Software GmbH https://www.managingcare.de/ • Ordensklinikum Linz Elisabethinen https://www.ordensklinikum.at/de/ • Stiftung Liebenau GmbH https://www.stiftung-liebenau.at/ • AllgäuStift GmbH https://www.allgaeustift.de/ • Allgäu Stift Marienpark gGmbH https://www.allgaeustift.de/marienpark

Contact Details

Project Coordinator, Martina Zeinzinger Research Center Hagenberg Embedded Systems Lab FH OÖ Forschungs & Entwicklungs GmbH Softwarepark 11 · SH3.110 A-4232 Hagenberg/Austria/Europe T: +43 (0)50804 27147 E: martina.zeinzinger@fh-hagenberg.at W: https://fh-ooe.at/ W: https://www.embedded-lab.at

Martina Zeinzinger, Jana Koch, Prof. Dr. Irmtraud Ehrenmüller, Prof. DI Mag. Dr. Josef Langer, and Prof. DI Dr. Florian Eibensteiner (left to right)

Martina Zeinzinger is a researcher in the Embedded Systems Lab at the University of Applied Sciences Upper Austria. Her work focuses on digital assistance systems in health and care applications. Jana Koch is a research assistant and project coordinator at the C&S Institut in Augsburg. Prof. Dr. Irmtraud Ehrenmüller is a business economist at the University of Applied Sciences Upper Austria. Prof. DI Mag. Dr. Josef Langer is founder of the Embedded Systems Lab, which he heads together with Prof. Florian Eibensteiner. Prof. DI Dr. Florian Eibensteiner is a professor of hardware-software co-engineering and head of the Josef Ressel Centre for Artificial Intelligence on Resource Limited Devices.

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