@Article{AI4CARE_Wilhelm2023a, author = {Wilhelm, Sebastian and Kasbauer, Jakob and Jakob, Dietmar and Elser, Benedikt and Ahrens, Diane}, journal = {Journal of Sensor and Actuator Networks}, title = {Exploiting Smart Meter Water Consumption Measurements for Human Activity Event Recognition}, year = {2023}, issn = {2224-2708}, month = jun, number = {3}, pages = {46}, volume = {12}, abstract = {Human activity event recognition (HAER) within a residence is a topic of significant interest in the field of ambient assisted living (AAL). Commonly, various sensors are installed within a residence to enable the monitoring of people. This work presents a new approach for human activity event recognition (HAER) within a residence by (re-)using measurements from commercial smart water meters. Our approach is based on the assumption that changes in water flow within a residence, specifically the transition from no flow to flow above a certain threshold, indicate human activity. Using a separate, labeled evaluation data set from three households that was collected under controlled/laboratory-like conditions, we assess the performance of our HAER method. Our results showed that the approach has a high precision (0.86) and recall (1.00). Within this work, we further recorded a new open data set of water consumption data in 17 German households with a median sample rate of 0.083 Hz to demonstrate that water flow data are sufficient to detect activity events within a regular daily routine. Overall, this article demonstrates that smart water meter data can be effectively used for HAER within a residence.}, doi = {10.3390/jsan12030046}, groups = {Published, DIT Repository}, keywords = {Water Monitoring, Human Activity Event Recognition (HAER), Human Activity Recognition (HAR), Smart Meter, Ambient Assisted Living (AAL), Water Consumption, Internet of Things (IoT)}, publisher = {MDPI AG}, url = {https://doi.org/10.3390/jsan12030046}, }
@Article{AI4CARE_Wilhelm2021d, author = {Wilhelm, Sebastian and Kasbauer, Jakob}, journal = {Sensors}, title = {Exploiting Smart Meter Power Consumption Measurements for Human Activity Recognition (HAR) with a Motif-Detection-Based Non-Intrusive Load Monitoring (NILM) Approach}, year = {2021}, issn = {1424-8220}, month = dec, number = {23}, pages = {8036}, volume = {21}, abstract = {Numerous approaches exist for disaggregating power consumption data, referred to as non-intrusive load monitoring (NILM). Whereas NILM is primarily used for energy monitoring, we intend to disaggregate a household's power consumption to detect human activity in the residence. Therefore, this paper presents a novel approach for NILM, which uses pattern recognition on the raw power waveform of the smart meter measurements to recognize individual household appliance actions. The presented NILM approach is capable of (near) real-time appliance action detection in a streaming setting, using edge computing. It is unique in our approach that we quantify the disaggregating uncertainty using continuous pattern correlation instead of binary device activity states. Further, we outline using the disaggregated appliance activity data for human activity recognition (HAR). To evaluate our approach, we use a dataset collected from actual households. We show that the developed NILM approach works, and the disaggregation quality depends on the pattern selection and the appliance type. In summary, we demonstrate that it is possible to detect human activity within the residence using a motif-detection-based NILM approach applied to smart meter measurements.}, doi = {10.3390/s21238036}, groups = {Published, DIT Repository}, keywords = {Non-Intrusive Load Monitoring (NILM), Human Activity Recognition (HAR), Smart Meter, Ambient Assisted Living (AAL), Motif Search, Ambient Intelligence (AmI), Internet of Things (IoT)}, publisher = {MDPI AG}, url = {https://doi.org/10.3390/s21238036}, }
@InProceedings{AI4CARE_Wilhelm2021c, author = {Wilhelm, Sebastian}, booktitle = {Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (HEALTHINF)}, title = {Activity-monitoring in Private Households for Emergency Detection: A Survey of Common Methods and Existing Disaggregable Data Sources}, year = {2021}, address = {Online Conference}, editor = {Pesquita, Cátia and Fred, Ana and Gamboa, Hugo}, month = feb, note = {Held online from February 11--13, 2021}, pages = {263--272}, publisher = {SCITEPRESS - Science and Technology Publications}, volume = {5}, abstract = {Ambient-Assisted Living (AAL) technologies can enable the elderly people to live a self-determined life in their own home environment instead of hospitals and retirement homes for a longer period of time. Hence, AAL systems are not only used for everyday support but also for the detection of potential emergency situations and for triggering notification chains. For this purpose the people are usually continuously monitored within their residents by ambient or wearable sensors to detect deviations in their daily behavior. This work surveys common used technologies for Human Activity Recognition (HAR)/Human Presence Detection (HPD), which is the basis for emergency detection. Furthermore, by examining various home automation software, existing data sources from the residential infrastructure, are identified that would be suitable for detecting personal activities.}, doi = {10.5220/0010180002630272}, groups = {Published, DIT Repository}, isbn = {978-989-758-490-9}, issn = {2184-4305}, keywords = {Human Activity Recognition (HAR), Human Presence Detection (HPD), Ambient Assisted Living (AAL), Activity Monitoring, Presence Detection, Ambient Sensor, Emergency Detection, Smart Home, Survey}, url = {https://www.scitepress.org/PublishedPapers/2021/101800/101800.pdf}, }
@InProceedings{AI4CARE_Wilhelm2020, author = {Wilhelm, Sebastian and Jakob, Dietmar and Kasbauer, Jakob and Dietmeier, Melanie and Gerl, Armin and Elser, Benedikt and Ahrens, Diane}, booktitle = {Proceedings of Fifth International Congress on Information and Communication Technology}, title = {Organizational, Technical, Ethical and Legal Requirements of Capturing Household Electricity Data for Use as an AAL System}, year = {2020}, address = {Brunel University, London, UK}, editor = {Yang, Xin-She and Sherratt, R. Simon and Dey, Nilanjan and Joshi, Amit}, month = feb, note = {Conference held at Brunel University, London, on February 20--21, 2020}, pages = {374--392}, publisher = {Springer Singapore}, series = {Advances in Intelligent Systems and Computing}, volume = {1183}, abstract = {Due to demographic change, elderly care is one of the major challenges for society in near future, fostering new services to support and enhance the life quality of the elderly generation. A particular aspect is the desire to live in one’s homes instead of hospitals and retirement homes as long as possible. Therefore, it is essential to monitor the health status, i.e. the activity of the individual. In our data-driven society, data is collected at an increasing rate enabling personalized services for our daily life using machine-learning and data mining technologies. However, the lack of labeled datasets from a realistic environment hampers research for training and evaluating algorithms. In the project BLADL, we use data mining technologies to gauge the health status of elderly people. Within this work, we discuss the challenges and caveats both from a technical and ethical perspectives to create such a dataset.}, comment = {ICT4AWE 2025}, doi = {10.1007/978-981-15-5856-6_38}, groups = {Published, DIT Repository}, isbn = {978-981-15-5856-6}, issn = {2194-5357}, keywords = {Data Models, Privacy, Elderly Care, Electricity Load Profiles, Household Electricity Data, Ethics, Home Appliance, Smart Metering, Data Recording, Data Transmission, Ambient-Assisted Living, Human Activity Detection, Data Recording Architecture}, url = {https://doi.org/10.1007/978-981-15-5856-6_38}, }
@Article{AI4CARE_Wilhelm2024, author = {Wilhelm, Sebastian and Wahl, Florian}, journal = {Sensors}, title = {Emergency Detection in Smart Homes Using Inactivity Score for Handling Uncertain Sensor Data}, year = {2024}, issn = {1424-8220}, month = oct, number = {20}, pages = {6583}, volume = {24}, abstract = {In an aging society, the need for efficient emergency detection systems in smart homes is becoming increasingly important. For elderly people living alone, technical solutions for detecting emergencies are essential to receiving help quickly when needed. Numerous solutions already exist based on wearable or ambient sensors. However, existing methods for emergency detection typically assume that sensor data are error-free and contain no false positives, which cannot always be guaranteed in practice. Therefore, we present a novel method for detecting emergencies in private households that detects unusually long inactivity periods and can process erroneous or uncertain activity information. We introduce the Inactivity Score, which provides a probabilistic weighting of inactivity periods based on the reliability of sensor measurements. By analyzing historical Inactivity Scores, anomalies that potentially represent an emergency can be identified. The proposed method is compared with four related approaches on seven different datasets. Our method surpasses existing approaches when considering the number of false positives and the mean time to detect emergencies. It achieves an average detection time of approximately 05:23:28 h with only 0.09 false alarms per day under noise-free conditions. Moreover, unlike related approaches, the proposed method remains effective with noisy data.}, doi = {10.3390/s24206583}, groups = {Published, DIT Repository}, keywords = {Emergency Detection, Ambient-Assisted Living, Activity Recognition, Uncertain Sensor Data, Inactivity Score, Smart Home, IoT}, publisher = {MDPI AG}, url = {https://doi.org/10.3390/s24206583}, }
@InBook{AI4CARE_Wahl2024, author = {Wahl, Florian and Wilhelm, Sebastian}, editor = {Swoboda, Walter and Seifert, Nadine}, pages = {307--324}, publisher = {Springer Berlin Heidelberg}, title = {Sensorik und künstliche Intelligenz in der Pflege}, year = {2024}, isbn = {9783662679142}, month = may, abstract = {Pflegesysteme befinden sich im Dilemma zwischen einer steigenden Anzahl Pflegebedürftiger einerseits und dem Fachkräftemangel auf Seiten der Pflegekräfte andererseits. Bis 2030 erwartet die Bertelsmannstiftung eine Lücke von 260 bis 490 Tausend Pflegekräften. Der Einsatz von Technologien wie Sensorik und KI bietet hier vielversprechende Lösungen, um Pflegekräfte zu entlasten, die Effizienz in der Pflege zu steigern und gleichzeitig die Lebensqualität von Pflegebedürftigen zu erhöhen. Die Entwicklungen in den Bereichen KI und Sensorik erlauben uns künftig diese Technologien intesiver in der Pflege einzusetzen. In diesem Kapitel geben wir eine kurze Übersicht über die Grundlagen der (KI) und typische Sensormodalitäten. Anschließend stellen wir die typischen Analyseebenen vor, welche für KI-Anwendungen im Pflegebereich interessan sind. Bevor wir ein Fazit ziehen, beschreiben wir zwei Beispielanwendungen: Die Aktivitätserkennung mittels Sensorbrille sowie die Notfallerkennung auf Basis von Smart-Meter Daten. Wir sind der Überzeugung, dass KI in der Zukunft einen signifikanten Beitrag zur Effizienzsteigerung und Verbesserung der Pflege beitragen kann und wird.}, booktitle = {Digitale Innovationen in der Pflege}, doi = {10.1007/978-3-662-67914-2_12}, groups = {Published, DIT Repository}, url = {https://doi.org/10.1007/978-3-662-67914-2_12}, }
@InProceedings{AI4Care_Wilhelm2020a, author = {Wilhelm, Sebastian and Jakob, Dietmar and Ahrens, Diane}, booktitle = {Proceedings of the Conference on Mensch und Computer}, title = {Human Presence Detection by monitoring the indoor CO2 concentration}, year = {2020}, month = sep, pages = {199-203}, publisher = {ACM}, series = {MuC’20}, abstract = {Presence detection systems are becoming more and more important and are used in smart home environments, in the Ambient Assisted Living (AAL) domain or in surveillance technology. Common systems focus on using motion sensors or cameras, which have only a limited viewing angle and therefore monitoring gaps can easily occur within a room. Humans produce carbon dioxide (2) through their respiration, which is distributed in rooms. As a result, if one (or more) persons are in a room, a significant increase in 2 concentration in the room can be noted. With this work we investigate an approach to detect the presence or absence of people indoors by monitoring the 2 concentration in the ambient air.}, collection = {MuC’20}, comment = {entry: vwindorfer-bogner on behalf of Sebastian Wilhelm}, doi = {• 10.1145/3404983.3409991}, groups = {Published}, keywords = {Presence Detection, Carbon Dioxide Monitoring, Human ActivityRecognition (HAR), Ambient Assisted Living (AAL), Surveillance,Carbon Dioxide, Sensor Data}, url = {https://dl.acm.org/doi/10.1145/3404983.3409991}, }
@InProceedings{AI4CARE_Wilhelm2021c, author = {Wilhelm, Sebastian and Jakob, Dietmar and Kasbauer, Jakob and Ahrens, Diane}, booktitle = {Proceedings of Sixth International Congress on Information and Communication Technology}, title = {GeLaP: German Labeled Dataset for Power Consumption}, year = {2021}, month = sep, pages = {21–33}, publisher = {Springer Singapore}, abstract = {Due to the increasing spread of smart meters, numerous researchers are currently working on disaggregating the power consumption data. This procedure is commonly known as Non-Intrusive Load Monitoring (NILM). However, most approaches to energy disaggregation first require a labeled dataset to train these algorithms. In this paper, we present a new labeled power consumption dataset that was collected in 20 private households in Germany between September 2019 and July 2020. For this purpose, the total power consumption of each household was measured with a commercial available smart meter and the individual consumption data of 10 selected household appliances were collected.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.1007/978-981-16-2377-6_5}, groups = {Published}, isbn = {9789811623776}, issn = {2367-3389}, keywords = {Smart meter,Dataset,Load disaggregation,Single-measurement,Scientific data,Power meter,Energy conservation}, url = {https://link.springer.com/chapter/10.1007/978-981-16-2377-6_5#citeas}, }
@InProceedings{AI4CARE_Wilhelm2019a, author = {Wilhelm, Sebastian and Jakob, Dietmar and Dietmeier, Melanie}, booktitle = {INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft}, title = {Development of a senior-friendly training concept for imparting media literacy}, year = {2019}, abstract = {The use of digital solutions to support rural areas, and in particular elderly people, is the goal of the ‘Digitales Dorf’ and ‘BLADL’ research projects. This work assessed seniors’ media literacy in two model communities; with the result that fear of fraudster and lack of knowledge are the most common causes that prevent elderly people from using digital technologies. Based on these evaluation results, a combined training offer of tutorial and digital consultation hour was developed and evaluated.}, comment = {entry: vwindorfer-bogner on behalf of Sebastian Wilhelm}, doi = {10.18420/inf2019_83}, groups = {Published}, keywords = {Digitization , Media literacy , Senior education}, url = {https://dl.gi.de/items/36cc8dda-9ef8-430b-9864-d11c6473d121}, }
@InProceedings{AICARE_Jakob2021, author = {Jakob, Dietmar and Wilhelm, Sebastian and Gerl, Armin and Ahrens, Diane}, booktitle = {HCI International 2021 - Late Breaking Papers: Cognition, Inclusion, Learning, and Culture}, title = {A Quantitative Study on Awareness, Usage and Reservations of Voice Control Interfaces by Elderly People}, year = {2021}, month = nov, pages = {237–257}, publisher = {Springer International Publishing}, abstract = {One third of Germans talk to ‘Alexa’, ‘Siri’ and other voice-controlled devices. These devices become omnipresent and change the way how humans interact with digital technologies. We hypothesize, this Human-Computer-Interface can minimize barriers for elderly people in their usage of digital services. But, do elderly people even know about voice-controlled technologies? Are the systems used by elderly and what reservations do they have?
Based on a quantitative study in three municipalities in a rural area ( ), we found that 59% of people aged 55+ years know voice-controlled devices, 37% used them at least once and even 26% use them regularly. But, more than two thirds of respondents (69%) are concerned that their data are not safe. In contrast, only 35% express concerns to be unable to use the devices. The study concludes that there is a gap between the perceived usefulness and trust in the devices for the surveyed demographic.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.1007/978-3-030-90328-2_15}, groups = {Published}, isbn = {9783030903282}, issn = {1611-3349}, keywords = {Empirical studies in HCI,Voice control,Voice user interface,Elderly,Quantitative study,Human Computer Interaction}, url = {https://link.springer.com/chapter/10.1007/978-3-030-90328-2_15}, }
@Article{AI4CARE_Wilhelm2019, author = {Wilhelm, Sebastian and Gerl, Armin}, journal = {P290 - BTW2019 - Datenbanksysteme für Business, Technologie und Web - Workshopband}, title = {Policy-based Authentication and Authorization based on the Layered Privacy Language}, year = {2019}, abstract = {In 2018 the General Data Protection Regulation (GDPR) has been enforced providing a new legal framework with rules and regulations for processing personal data. The requirement for distinguishing between purposes has been introduced, leading to the necessity of adapting existing authentication and authorization processes. We introduce a detailed authentication and authorization extension, which is able to verify requests on personal data based on the Layered Privacy Language (LPL). This extension is evaluated in the form of a benchmark, utilizing the Policy-based De-identification, to demonstrating its efficiency and suitability for data-warehouses.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.18420/btw2019-ws-25}, groups = {Published}, keywords = {Access Control , GDPR , Privacy , Privacy Language}, url = {https://dl.gi.de/items/f231108a-3773-4462-9629-7b4cf9848d71}, }
@Article{AI4CARE_Sommer2024e, author = {Sommer, Domenic and Wilhelm, Sebastian und Wahl, Florian}, journal = {MDPI Healthcare 2024}, title = {Nurses’ Workplace Perceptions in Southern Germany—Job Satisfaction and Self-Intended Retention towards Nursing}, year = {2024}, issn = {2227-9032}, month = jan, number = {2}, pages = {172}, volume = {12}, abstract = {Our cross-sectional study, conducted from October 2022 to January 2023, aims to assess post-COVID job satisfaction, crucial work dimensions, and self-reported factors influencing nursing retention. Using an online survey, we surveyed 2572 nurses in different working fields in Bavaria, Germany. We employed a quantitative analysis, including a multivariable regression, to assess key influence factors on nursing retention. In addition, we evaluated open-ended questions via a template analysis to use in a joint display. In the status quo, 43.2% of nurses were not committed to staying in the profession over the next 12 months. A total of 66.7% of our surveyed nurses were found to be dissatisfied with the (i) time for direct patient care. Sources of dissatisfaction above 50% include (ii) service organization, (iii) documentation, (iv) codetermination, and (v) payment. The qualitative data underline necessary improvements in these areas. Regarding retention factors, we identified that nurses with (i) older age, (ii) living alone, (iii) not working in elder care, (iv) satisfactory working hours, (v) satisfactory career choice, (vi) career opportunities, (vii) satisfactory payment, and (viii) adequate working and rest times are more likely to remain in the profession. Conversely, dissatisfaction in (ix) supporting people makes nurses more likely to leave their profession and show emotional constraints. We uncovered a dichotomy where nurses have strong empathy for their profession but yearn for improvements due to unmet expectations. Policy implications should include measures for younger nurses and those in elderly care. Nevertheless, there is a need for further research, because our research is limited by potential bias from convenience sampling, and digitalization will soon show up as a potential solution to improve, e.g., documentation and enhanced time for direct patient time.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.3390/healthcare12020172}, groups = {Published}, keywords = {nursing,healtcare jobs,intention to leave,job satisfaction,employee retention}, publisher = {MDPI AG}, url = {https://www.mdpi.com/2227-9032/12/2/172}, }
@InProceedings{AI4CARE_Wilhelm2021b, author = {Wilhelm, Sebastian}, booktitle = {Human Interaction, Emerging Technologies and Future Applications IV Proceedings of the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications (IHIET – AI 2021), April 28-30, 2021, Strasbourg, France}, title = {Exploiting Home Infrastructure Data for the Good: Emergency Detection by Reusing Existing Data Sources}, year = {2021}, month = apr, pages = {51–58}, publisher = {Springer International Publishing}, abstract = {Monitoring people within their residence can enable elderly to live a self-determined life in their own home environment for a longer period of time.
Therefore, commonly activity profiles of the residents are created using various sensors in the house. Deviations from the typical activity profile may indicate an emergency situation. An alternative approach for monitoring people within their residence we investigates within our research is reusing existing data sources instead of installing additional sensors. In private households there are already numerous data sources such as smart meters, weather station, routers or voice assistants available. Intelligent algorithms can be used to evaluate this data and conclude on personal activities. This, in turn, allows the creation of activity profiles of the residents without using external sensor technology. This work outlines the research gap in reusing existing data sources for Human Activity Recognition (HAR) and emergency detection, which we intend to fill with our further work.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.1007/978-3-030-74009-2_7}, groups = {Published}, isbn = {9783030740092}, issn = {2194-5365}, keywords = {Human Activity Recognition (HAR),Human Presence Detection (HPD),Ambience Assisted Living (AAL),Activity Monitoring,Presence detection,Ambient sensor,Emergency detection}, url = {https://link.springer.com/chapter/10.1007/978-3-030-74009-2_7}, }
@Article{AI4CARE_Jakob2020, author = {Jakob, Dietmar and Wilhelm, Sebastian and Gerl, Armin}, journal = {Mensch und Computer 2020}, title = {Data Privacy Management (DPM) - A Private Household Smart Metering Use Case}, year = {2020}, abstract = {The automated collection of real life data in private households places special requirements on a Data Privacy Management (DPM) concept. The development and implementation of a DPM concept for use in a scientific environment is demonstrated according to a successful use case – the project BLADL. The intention of this paper is to provide a guideline for ethical and privacy-preserving data collection and management in research projects in the EU.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.18420/muc2020-ws119-003}, groups = {Published}, keywords = {Privacy,GDPR,Ethics,Data Collection,Data Privacy Management,Data Set,Scientific Data,Process Mangement,Smart Metering,Elderly}, language = {en}, publisher = {Gesellschaft für Informatik e.V.}, url = {https://dl.gi.de/items/d8555c71-5f58-4139-8d19-5847755e359c}, }
@Article{AI4CARE_Lichtenauer2024, author = {Lichtenauer, Norbert and Schmidbauer, Lukas and Wilhelm, Sebastian and Wahl, Florian}, journal = {MDPI Information}, title = {A Scoping Review on Analysis of the Barriers and Support Factors of Open Data}, year = {2024}, issn = {2078-2489}, month = dec, number = {1}, pages = {5}, volume = {14}, abstract = {Background: Using personal data as Open Data is a pervasive topic globally, spanning various sectors and disciplines. Recent technological advancements, particularly in artificial intelligence and algorithm-driven analysis, have significantly expanded the capacity for the automated analysis of vast datasets. There’s an expectation that Open Data analysis can drive innovation, enhance services, and streamline administrative processes. However, this necessitates a legally and ethically sound framework alongside intelligent technical tools to comprehensively analyze data for societal benefit. Methodology: A systematic review across seven databases (MEDLINE, CINAHL, BASE, LIVIVO, Web of Science, IEEExplore, and ACM) was conducted to assess the current research on barriers, support factors, and options for the anonymized processing of personal data as Open Data. Additionally, a supplementary search was performed in Google Scholar. A total of n=1192 studies were identified, and n=55 met the inclusion criteria through a multi-stage selection process for further analysis. Results: Fourteen potential supporting factors (n=14 ) and thirteen barriers (n=13 ) to the provision and anonymization of personal data were identified. These encompassed technical prerequisites as well as institutional, personnel, ethical, and legal considerations. These findings offer insights into existing obstacles and supportive structures within Open Data processes for effective implementation.}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.3390/info15010005}, groups = {Published}, publisher = {MDPI AG}, url = {https://www.mdpi.com/2078-2489/15/1/5}, }
@InProceedings{AI4Care_Sommer2023a, author = {Sommer, Domenic and Greiler, Tobias and Fischer, Stefan and Wilhelm, Sebastian and Hanninger, Lisa-Marie and Wahl, Florian}, booktitle = {HCI International 2023 Posters25th International Conference on Human-Computer Interaction, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings, Part II}, title = {Investigating User Requirements: A Participant Observation Study to Define the Information Needs at a Hospital Reception}, year = {2023}, month = jul, pages = {157–166}, abstract = {The hospital reception (HR) is one of the first contact points for information about treatment stays, visits, or administrative matters, and thus has influence on the perceived hospital quality. In Dec. 2022, we investigated the information needs during a one week participant observation of the entrance hall at a rural Bavarian hospital. We aim to understand the HRs information needs and how these requests are answered. Previous studies show that the information needs can vary significantly among patients, visitors and employees, impacting the overall hospital experience. There is a lack of research on the information requirements at hospital receptions, with most studies focusing on emergency admissions. In our literature search, we couldn’t locate studies that addressed information needs at a hospital reception. We conducted a participant observation using a standardized form. Over the seven day observation period, N = 1,499 requests were made at HR. The requests were examined by summarizing qualitative content analysis in different categories about locations or concerns. Visitors account for 51.3% (n = 769) of all requests, followed by patients at 38.5% (n = 577), employees at 5.3% (n = 79), and other stakeholder at 1.6% (n = 24). The highest utilization of the reception is due to visitors showing a COVID-19 test certificate (n = 289) and asking the reception staff for a patient room number (n = 204). Patients most frequently asked about their appointment registration (n = 148), the procedure in case of an emergency (n = 98), and orientation (n = 79). The minor requests came from employees in the form of administrative requests like borrowing keys (n = 39). On average, the staff needs 65 s to attend to one person. New technologies, like service robots in the entrance hall, can reduce the number of requests in the future. Our study helps to meet user needs through designing service robots. Follow-up studies are planned to validate our findings.}, comment-vwindorfer-bogner = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.1007/978-3-031-35992-7_23}, groups = {Published}, keywords = {User Requirement Analysis,Information Needs,User Requests,Empirical Study,Hospital Reception}, url = {https://link.springer.com/chapter/10.1007/978-3-031-35992-7_23}, }
@InProceedings{AI4Care_Sommer2023, author = {Sommer, Domenic and Wilhelm, Sebastian and Ahrens, Diane and Wahl, Florian}, booktitle = {In Proceedings of the 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health - ICT4AWE;}, title = {Implementing an Intersectoral Telemedicine Network in Rural Areas: Evaluation from the Point of View of Telemedicine Users}, year = {2023}, abstract = {Telemedicine (TMed) is becoming popular due to the growing number of elderly and the shortage of healthcare workers. In Germany, TMed is rarely part of rural healthcare, and the research state is limited. To improve healthcare and to research the conditions under which TMed can be used in German rural areas, an intersectoral, TMed network was set up from July 2018 to Oct. 2020 and evaluated with mixed methods, including qualitative interviews and quantitative feedback forms. Seven Use-Cases (UCs) were implemented in the dimensions: (i) home visits (n = 170), (ii) patient video consultation (n = 30), (iii) intensive care (n = 15), (iv) mountain accident (n = 6), (v) wound management (n = 6), (vi) caregiver video consultation (n = 3) and (vii) electronic health record (n = 10). Our study indicates that digitally supported general practitioner (GP)- home visits and intensive care are the most frequent UCs. TMed is satisfactory and leads to advantages for rural healthcare. However, vital data transmission and the electronic health record (eHR) were less in demand due to high preparation efforts. Findings from previous studies can be confirmed. Facilitators for TMed who should be considered and further researched are: training on digital literacy including awareness-rising, financing, cross-institutional documentation, and suitable mobile network infrastructure.}, comment-vwindorfer-bogner = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.5220/0011755500003476}, groups = {Published}, keywords = {Telemedicine, Remote Medicine, Delivery of Healthcare, Ehealth, Rural Health, Germany.,Telemedicine,Remote Medicine,Delivery of Healthcare,Ehealth,Rural Healt,Germany}, url = {https://www.scitepress.org/Link.aspx?doi=10.5220/0011755500003476}, }
@InProceedings{AI4Care_Jakob2023, author = {Jakob, Dietmar and Wilhelm, Sebastian and Gerl, Armin and Wahl, Florian and Ahrens, Diane}, booktitle = {Human Aspects of IT for the Aged Population9th International Conference, ITAP 2023, Held as Part of the 25th HCI International Conference, HCII 2023, Copenhagen, Denmark, July 23–28, 2023, Proceedings, Part I}, title = {Voice Controlled Devices: A Comparative Study of Awareness, Ownership, Usage, and Reservations Between Young and Older Adults}, year = {2023}, month = jul, pages = {348–365}, publisher = {Springer Nature Switzerland}, abstract = {The utilization of voice commands as a means of device control has gained widespread acceptance in consumer technology. Implementing Apple’s voice interface Siri in smartphones has significantly increased voice interface popularity among young and older adults.
This article presents a comparative analysis of two similar studies: one conducted on young adults (aged 14-40) and the other on older adults (aged 55+) in Germany from Juli/August 2020, examining their familiarity with Voice Controlled Devices (VCDs), device ownership, usage, and reservations.
The comparison shows, that 96% of young adults and 59% of older adults were aware of VCDs. 87% of young adults and 43% of older adults knowingly own a VCD. Out of those who knowingly own a VCD, more older adults (45%) use the VCD frequently (at least once a week) than young adults (20%). However more young adults (68%) than older adults (64%), who knowingly own a VCD, have used a VCD at least once. The main difference for non-usage between the both population groups lies in the fact that the older adults believe not to be able to operate VCDs (35%), while only 7% of the young adults think they are not able to operate VCDs. Further, older adults are more afraid of fraudsters (52%) than young adults (32%). However, young adults expresses more concerns, of being surveilled (76%) than older adults (61%).}, comment = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.1007/978-3-031-34866-2_25}, groups = {Published}, isbn = {9783031348662}, issn = {1611-3349}, keywords = {Voice Controlled Device,Voice Control,Voice User Interface,Young Adults,Older Adults,Human Computer Interaction}, url = {https://link.springer.com/chapter/10.1007/978-3-031-34866-2_25}, }
@InBook{AI4Care_Wilhelm2023, author = {Wilhelm, Sebastian}, editor = {Ahrens, Diane}, pages = {139-149}, publisher = {Springer Gabler Wiesbaden}, title = {Digital unterstützte Nachbarschaftshilfe – ein Erfolgsmodell?}, year = {2023}, isbn = {978-3-658-38235-3}, month = jan, abstract = {Die organisierte, von bürgerschaftlichem Engagement getragene Nachbarschaftshilfe (ONH) ist eine Form der ehrenamtlichen Nachbarschaftshilfe, in der Hilfeleistungen durch eine zentrale Stelle koordiniert werden. Durch einen festen Organisationsrahmen sollen dadurch zum einen die Helfer geschützt werden und zum anderen auch sozial weniger vernetze Bürgern die Möglichkeit erhalten, Hilfeleistungen aus der Nachbarschaft in Anspruch zu nehmen. Die Administration einer ONH stellt jedoch einen zeit- und ressourcenintensiven Prozess dar. Im Rahmen dieser Arbeit wird daher untersucht, ob der Einsatz einer digitalen Plattform zur Unterstützung der Administration einer ONH in der Praxis erfolgreich eingesetzt werden kann. Dazu wurde in enger Abstimmung mit Experten und Stakeholdern eine Online-Plattform entwickelt und in drei Modellgemeinden eingeführt. Nach Einführung der Online-Plattform zeigte sich jedoch, dass analoge Kommunikation gegenüber der digitalen Abwicklung präferiert wurde.}, comment = {Smart Region: Angewandte digitale Lösungen für den ländlichen Raum
Best Practices aus den Modellprojekten „Digitales Dorf Bayern"}, comment-vwindorfer-bogner = {entry: vwindorfer-bogner on behalf of: Sebastian Wilhelm}, doi = {10.1007/978-3-658-38236-0_9}, groups = {Published}, keywords = {Nachbarschaft,Digitale Vernetzung,Ehrenamtliches Engagement,Nachbarschaft; Digitalisierung}, url = {https://link.springer.com/chapter/10.1007/978-3-658-38236-0_9}, }
@InProceedings{AI4Care_Meyer2025, author = {Meyer, Sanamjeet and Wilhelm, Sebastian and Wahl, Florian}, booktitle = {ITC4AWE 2025 International Conference on Information and Communication Technologies for Ageing Well and e-Health}, title = {Assessing Human Activity in Elderly People’s Homes using theDempster-Shafer Theory}, year = {2025}, pages = {291--301}, publisher = {SCITEPRESS - Science and Technology Publications}, abstract = {The increasing elderly population living alone, alongside caregiver shortages, has accelerated research in Ambient Assisted Living (AAL). A recent trend employs smart meters and Non-Intrusive Load Monitoring (NILM) to assess daily activities by analyzing device-specific power usage. This work explores the use ofDempster-Shafer Theory (DST) to enhance NILM-based anomaly detection in daily routines. Evaluated on the SynD dataset, our approach identifies deviations such as unexpected appliance use and inactivity. Results demonstrate DST’s potential for non-intrusive elderly monitoring, with future research focusing on real-world validation.}, comment = {entry: vwindorfer-bogner, on behalf of: Sebastian Wilhelm}, doi = {10.5220/0013354100003938}, groups = {Published, DIT Repository}, keywords = {Human Activity Recognition, Uncertainty Quantification, Ambient Assisted Living, Activities of Daily Living}, url = {https://www.insticc.org/node/TechnicalProgram/ict4awe/2025/presentationDetails/133541}, }
@InProceedings{AI4Care_Jakob2025a, author = {Jakob, Dietmar and Schmidt, Sebastian and Wahl, Florian}, booktitle = {2025 Future of Information and Communication Conference (FICC)}, title = {Planning and Installation of 5G Campus Networks in Hospitals in Rural Areas and Possible Use Cases: A Practical Example}, year = {2025}, organization = {uture of Information and Communication Conference}, pages = {684--705}, publisher = {Springer Nature Switzerland}, series = {Lecture Notes in Networks and Systems ((LNNS,volume 1284))}, abstract = {The introduction of 5G technologies will result in significant changes in various industry areas and the healthcare sector. High data rates, low latency times, and diverse connectivity are just some of the features of this technology. 5G campus networks are particularly suitable for hospitals to improve healthcare. This article focuses on the planning and installation of 5G campus networks and their implementation in two rural hospitals in Germany. Using predefined use cases such as patient monitoring, televising, patient routing, and transport services, the article examines how 5G technology can be used in hospitals. The key findings are that insufficient interfaces for today’s robot-assisted applications and high acquisition costs limit the usefulness of 5G networks. Nevertheless, hospitals can benefit from the technology’s real-time data transmission and reliability to speed up healthcare processes and make them more effective, especially if the described limitations might be overcome in the future. For this reason, this paper aims to provide interested hospitals and counties with best practices for successful implementation.}, comment = {entry: vwindorfer-bogner on behalf of: Dietmar Jakob}, doi = {10.1007/978-3-031-85363-0_42}, groups = {Published, DIT Repository}, isbn = {9783031853630}, issn = {2367-3389}, keywords = {5G technology,5G campus networks,Healthcare,Hostpitals,Clinics}, url = {https://doi.org/10.1007/978-3-031-85363-0_42}, }
@Article{AI4Care_Jakob2025, author = {Jakob, Dietmar and Wilhelm Sebastian and Gerl Armin and Diane Ahrens}, journal = {MDPI Digital}, title = {Adapting Voice Assistant Technology for Older Adults: A Comprehensive Study on Usability, Learning Patterns, and Acceptance}, year = {2025}, issn = {2673-6470}, month = jan, number = {1}, pages = {4}, volume = {5}, abstract = {This study investigates the integration, usability, and learning patterns associated with voice assistant technology among older adults, focusing on the “Amazon Echo Show 10, 3rd generation” as a case study. Conducted with 32 participants aged 55 and above in senior and complementary households, this research employs a mixed-method approach, incorporating qualitative interviews and quantitative voice command logging over a twelve-week period. Our findings reveal a high level of learnability and usability of the voice assistant, with 90% of participants finding the device easy to learn and use. The study further explores the patterns of voice assistant use, highlighting a preference for listening to music and seeking information, predominantly on weekends. Despite initial reservations, participants reported a high satisfaction level, with most not feeling monitored by the device. Key recommendations for manufacturers include prioritizing the design and user experience to cater to older adults’ needs, aiming to enhance their digital inclusion and participation. This study contributes to the human–computer interaction (HCI) field by providing insights into older adults’ interactions with voice assistant technology, emphasizing the importance of designing accessible and user-friendly digital solutions for the aging population.}, comment = {entry: vwindorfer-bogner on behalf of: Dietmar Jakob}, doi = {10.3390/digital5010004}, groups = {Published, DIT Repository}, keywords = {human-computer interaction,older adults,voice assistants,smart speaker}, publisher = {MDPI AG}, url = {https://doi.org/10.3390/digital5010004}, }
@Article{AI4Care_Lichtenauer2025, author = {Lichtenauer, Norbert and Wahl, Florian and Wilhelm, Sebastian}, journal = {26. Jahrestagung des Netzwerks Evidenzbasierte Medizin e. V.}, title = {Dissemination von Open Data: Erfahrungen zur Anonymisierung und Weiterverwendung von personenbezogenen Daten – qualitative Ergebnisse einer Expertenbefragung im Projekt EAsyAnon}, year = {2025}, month = mar, abstract = {Hintergrund/Fragestellung: Für den medizinische Fortschritt und für Innovationen wird der Zugang zu wissenschaftlichen Gesundheitsdaten als essenziell betrachtet (Deist et al. 2020 [1]). Gerade klinische, evidenzbasierte Entscheidungen benötigen idealerweise eine Big-Data Grundlage zur Unterstützung der Entscheidungsfindung (Rehman et al. 2022 [2]; Deist et al. 2020 [1]). Zugleich kann eine optimierte Nutzung von personenbezogenen Daten (pbD) die Gesundheitsversorgung sowie das individuelle Verständnis und die Prävention von Krankheiten grundlegend verändern (Fylan und Fylan 2021 [3]). Das Projekt EAsyAnon, welches vom Bundesministerium für Bildung und Forschung (BMBF) und der Europäischen Kommission (Next Generation) gefördert wird, möchte eine Software entwickeln, mit deren Hilfe pbD anonymisiert werden können und mit einem zweiteiligen Auditverfahren überprüft werden.
Methoden: Zur Bearbeitung der empirischen Begleitforschung im Projekt wurde ein Mixed Methods Ansatz gewählt (Levitt et al. 2018; Schoonenboom 2023). In einer qualitativen Teilstudie wurden Erfahrungen zur Anonymisierung von pbD und der weiteren Verwendung als Open Data eruiert. Hierzu wurden Expert:inneninterviews (n=19) durchgeführt und mit der strukturierenden Inhaltsanalyse nach Kuckartz ausgewertet (Kuckartz 2018).
Ergebnisse: Nach Auswertung der Interviews konnten insgesamt fünf Hauptkategorien und einundzwanzig Subkategorien ermittelt werden. Es zeigte sich, dass die Erfahrungen zur Anonymisierung und zur weiteren Verwendung als Open Data als rudimentär angesehen werden können. Dabei waren die Arten und Formen der in Frage kommenden personenbezogenen Daten äußerst heterogen. Die Teilnehmenden berichteten von Barrieren und Förderfaktoren, vor allem personeller, technischer und institutioneller Aspekte. Weiter wurden mögliche Unterstützungsleistungen beschrieben und ethische und rechtliche Implikationen diskutiert.
Schlussfolgerung: Die Dissemination von Anonymisierungskonzepten und einer breiten Verwendung und Nutzung von Open Data hat bislang kaum stattgefunden. Oftmals stellen personelle Hürden, technische Barrieren und institutionelle Hindernisse eine große Herausforderung dar, welche den Erfahrungshorizont zu Anonymisierungen und Open Data aktuell begrenzt. Neben klaren rechtlichen und ethischen Handlungsrahmen wie unter anderem im Gesundheitsdatennutzungsgesetz (GDNG) formuliert, braucht es gezielte Unterstützungen, um eine breitere Nutzung von anonymisierten, pbD zu ermöglichen.
Interessenkonflikte: Der/die Autor(en) hat/haben keine potenziellen Interessenkonflikte in Bezug auf die Forschung, Autorenschaft und/oder Veröffentlichung dieses Artikels.
Der/die Autor(en) erhielten finanzielle Unterstützung im Rahmen des Drittmittel Forschungsprojektes EAsyAnon, welches vom Bundesministerium für Bildung und Forschung (BMBF) und der Europäischen Kommission (Next Generation) gefördert wurde und die Kosten zur Open Access Publikation beinhalteten.}, comment = {entry: vwindorfer-bogner source: GScholar}, copyright = {Creative Commons Attribution 4.0 International}, doi = {10.3205/25ebm049}, groups = {Published}, keywords = {Medicine and health}, language = {de}, publisher = {German Medical Science GMS Publishing House}, }
@Article{AI4CARE_Sommer2025, author = {Sommer, Domenic and Lermer, Eva and Wahl, Florian and Lopera G., Luis I.}, journal = {BMC Health Service Research}, title = {Assistive technologies in healthcare: utilization and healthcare workers perceptions in Germany}, year = {2025}, issn = {1472-6963}, month = feb, number = {223}, volume = {225}, abstract = {Background According to the WHO, assistive technology (AT) is defined as the superset of technologies that improve or maintain the functioning of different senses, mobility, self-care, well-being, and inclusion of patients. ATs also include technologies for healthcare workers (HCWs) to reduce workloads and improve efficiency and patient care outcomes. Software ATs for HCWs include communication software, artificial intelligence (AI), text editors, planning tools, decision support systems, and health records. Hardware ATs for HCWs can range from communication devices, sensors, and specialized medical equipment to robots.
Aims With this indicative study, we explore HCW utilization, perceptions, and adoption barriers of ATs. We emphasize ATs role in enhancing HCWs’ efficiency and effectiveness in healthcare delivery.
Methods A cross-sectional online survey was conducted through August 2024 with HCWs in Bavaria via a network recruiting approach. We used convenience sampling but ensured that only HCWs were part of our study population. Our survey included (i) usage, (ii) usefulness, and (iii) perceptions regarding ATs. The survey comprised 11 close-ended and three open-ended questions, including story stems evaluated by a deductive qualitative template analysis. Our mixed-method evaluation also employed descriptive and bivariate statistics.
Results Three hundred seventy-one HCWs (♂63.9 %, ♀36.1 %) participated in our survey, primarily 133 administrators, 116 nurses, and 34 doctors. More than half of the study participants (58.6 %) reported having advanced technical skills. Regarding usage, communication platforms (82.2 %) and communication devices (86 %) were the most commonly used ATs. Advanced ATs such as body-worn sensors, medical devices with interfaces, identification devices, and robots were underutilized in our sample. ATs were reported to be helpful in all job roles but need improvements in capacity and integration. Key barriers to adoption included outdated infrastructure, interoperability, and a lack of training.
Conclusion Our study suggests that HCWs may want to incorporate ATs into their workflows as they see how, in theory, these technologies would improve HCW’s efficiency, resulting in better patient care. However, to realize this potential, efforts in ATs integration and accessibility are essential. Given this study’s modest sample size and generalizability limitations, further research is needed to explore the adoption, implementation, and impact of ATs in healthcare.}, comment = {entry: vwindorfer-bogner source: GScholar}, doi = {https://doi.org/10.1186/s12913-024-12162-x}, groups = {Published}, keywords = {Assistive technologies,Healthcare workers,Human-computer interaction,Information and communication technologies,Artificial intelligence}, publisher = {Springer Science and Business Media LLC}, }
@InProceedings{AI4Care_Sommer2024d, author = {Sommer, Domenic, and Fischer, Stefan and Wahl, Florian}, booktitle = {HCI International 2024 Posters. HCII 2024. Communications in Computer and Information Science}, title = {Investigating Hospital Service Robots: A Observation Study About Relieving Information Needs at the Hospital Reception}, year = {2024}, pages = {pp 395–404}, publisher = {Springer Nature Switzerland}, volume = {21}, abstract = {Hospital receptions (HRs) are a vital area to meet information needs. Deploying Service Robots (SRs) is increasingly important in HR due to staff shortages and increasing healthcare demands in Germany. To evaluate the effectiveness of SR in HR, we conducted a consecutive study during one week in September 2023 in a rural Bavarian hospital. The study involved 1,703 interactions, primarily handled by HR staff (89.9 %), with SRs addressing 10.1 %. HR was mainly requested from 10:00 to 15:00 and the SR between 13:00 to 19:00. Each interaction was mainly under one minute. The requests were predominantly regarding orientation by both the SR and the hospital staff. Our results indicate that SR can reduce workload, saving 2.15 working hours during the study. The findings suggest SRs’ utility in information provision yet highlight the need for more comprehensive studies with advanced SRs in healthcare to optimize their role in information management.}, comment = {entry: vwindorfer-bogner source: GScholar}, doi = {https://doi.org/10.1007/978-3-031-61932-8_45}, groups = {Published}, isbn = {9783031619328}, issn = {1865-0937}, keywords = {Service robots,HCI,Information needs,Hospital reception}, }
@InProceedings{AI4CARE_Schmidt2024, author = {Schmidt, Sebastian and Sommer, Domenic and Greiler, Tobias and Wahl, Florian}, booktitle = {ICT4AWE 2024 - 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health}, title = {hospOS: A Platform for Service Robot Orchestration in Hospitals}, year = {2024}, month = apr, pages = {221-228}, publisher = {SCITEPRESS - Science and Technology Publications}, abstract = {In a time where an ageing population, nurses shortage and manual labor routines are limiting rural healthcare, Service Robots (SR) are emerging. While SR could increase hospital staff efficiency, their healthcare use remains limited. Barriers are the robot’s task-specific inflexibility and a lack of interoperability. Existing SR are usually closed systems and focus on a single robot designed to fulfill all functional requirements, which results in complex and expensive solutions. In contrast, we propose to utilize and combine existing SR for various tasks. We argue that with the growing integration of SR in healthcare, a SR management system has become a necessity. We propose hospOS, a centralised system for SR orchestration in healthcare facilities. hospOS addresses this gap by providing a modular, flexible, user-friendly platform that seamlessly integrates SR into hospital IT infrastructures, alleviating the shortage of care workers and thus improving patient care. The platform is built with a focus on interoperability, modularity, and compliance with regulations. We evaluated hospOS in two rural hospitals by realising three example use cases: Telemedicine, transport, and orientation services. This paper offers an architecture blueprint and discusses the functionalities, and potential benefits of hospOS, along with its implementation in healthcare scenarios. The results from deployments indicate improvements in service delivery and operational management.}, comment = {entry: vwindorfer-bogner source: GScholar}, doi = {10.5220/0012692200003699}, groups = {Published, DIT Repository}, keywords = {Sytem Integration,HCI,Human-Centered Computing,Human-Robot interaction,HRI,Robot Orchestration,Robot Mission Planning,Healthcare,Interoperability,Ambient Technology}, url = {https://www.researchgate.net/publication/380312458_hospOS_A_Platform_for_Service_Robot_Orchestration_in_Hospitals}, }
@InProceedings{AI4CARE_Jakob2024, author = {Jakob, Dietmar and Kuchler, Johannes and Ahrens, Diane and Wahl, Florian}, booktitle = {Human Aspects of IT for the Aged Population10th International Conference, ITAP 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings, Part I}, title = {Activities to Encourage Older Adults’ Skills in the Use of Digital Technologies on the Example of Multigenerational Houses in Germany}, year = {2024}, editor = {Qin Gao, Jia Zhou}, month = jun, publisher = {Springer Nature Switzerland}, abstract = {Against the backdrop of demographic change and advancing digitalization, digital skills are indispensable for older adults. Nevertheless, using digital technologies is not a matter of course for this group. Due to their structures and regional networking, multigenerational houses (MGHs) are suitable platforms for promoting media skills for older adults.
Training programs consisting of courses and media consultation hours for older adults to strengthen their digital skills were initiated and carried out in Bavarian MGHs. The aim was to understand better the mechanisms, potential, and challenges of promoting digital skills among older adults in MGHs. To this end, expert interviews were conducted with managers of seven selected MGHs in April 2023.
The results show that older adults respond positively to the training programs and see considerable added value. Providing programs to promote media skills in MGHs can help to reduce the digital divide and enable older adults to participate better in a digitally shaped society.}, doi = {https://doi.org/10.1007/978-3-031-61543-6}, groups = {Published, DIT Repository}, isbn = {9783031615436}, issn = {1611-3349}, journal = {Lecture Notes in Computer Science}, keywords = {Interaction design and evaluation for older adults,Design methodology involving older adults,Promoting health among older adults,Strengthening connectedness in older adults,Building elder-friendly environments and smart-home technologies}, }
@Article{AI4CARE_Sommer2024b, author = {Sommer, Domenic and Schmidbauer, Lukas and Wahl, Florian}, journal = {BMC Nursing}, title = {Nurses’ perceptions, experience and knowledge regarding artificial intelligence: results from a cross-sectional online survey in German}, year = {2024}, issn = {1472-6955}, month = mar, number = {1}, volume = {23}, abstract = {Background Nursing faces increasing pressure due to changing demographics and a shortage of skilled workers. Artificial intelligence (AI) offers an opportunity to relieve nurses and reduce pressure. The perception of AI by nurses is crucial for successful implementation. Due to a limited research state, our study aims to investigate nurses’ knowledge and perceptions of AI.
Methods In June 2023, we conducted a cross-sectional online survey of nurses in Bavaria, Germany. A convenience sample via care facilities was used for the questionnaire oriented on existing AI surveys. Data analysis was performed descriptively, and we used a template analysis to evaluate free-text answers.
Results 114 (♀67.5 %, ♂32.5 %) nurses participated. Results show that knowledge about AI is limited, as only 25.2 % can be described as AI experts. German nurses strongly associate AI with (i) computers and hardware, (ii) programming-based software, (iii) a database tool, (iv) learning, and (v) making decisions. Two-thirds of nurses report AI as an opportunity. Concerns arise as AI is seen as uncontrollable or threat. Administration staff are seen as the biggest profiteers.
Conclusion Even though there is a lack of clear understanding of AI technology among nurses, the majority recognizes the benefits that AI can bring in terms of relief or support. We suggest that nurses should be better prepared for AI in the future, e.g., through training and continuing education measures. Nurses are the working group that uses AI and are crucial for implementing nursing AI.}, comment = {entry: vwindorfer-bogner source: GScholar}, doi = {https://doi.org/10.1186/s12912-024-01884-2}, groups = {Published}, keywords = {Nurse,Artificial intelligence,Healthcare,Nursing education,Germany}, publisher = {Springer Science and Business Media LLC}, }
@PhdThesis{AI4CARE_Wilhelm2025b, author = {Wilhelm, Sebastian}, school = {Universität Passau, Fakultät für Informatik und Mathematik}, title = {Emergency Detection in Private Households Utilizing Existing Data Sources for Human Activity Event Recognition}, year = {2025}, abstract = {In an aging society, the need for efficient emergency detection systems in smart homes is becoming increasingly important. Over 30% of those aged 65 and older experience at least one fall per year, often resulting in the inability to rise without assistance, leading to ‘long lies’ lasting hours or even days. Systems for detecting such emergency events usually rely on wearable sensors or specific installations of ambient sensors, which can be intrusive and complex, hindering acceptance. This thesis proposes a novel approach that utilizes existing digital data sources within the residential infrastructure to detect human activities and identify potential emergencies.
A survey identifies 44 potential data sources in private households for recognizing human activity. However, extracting activity information often requires complex preprocessing. In this thesis, methodologies are developed for three of these data sources to highlight practical applications: Smart Power Meters, Smart Water Meters, and Home Weather Stations. It is shown that detecting human activities using these sources is feasible in a practical environment, although accuracy and reliability vary. Notably, Smart Water Meters demonstrate high reliability, with a precision of 0.86 and a recall of 1.00, making them particularly suitable for emergency detection.
Existing emergency detection methods are not designed to handle uncertain activity data. This thesis introduces a novel approach based on probabilistic activity information, employing an Inactivity Score that provides a probabilistic weighting of inactivity periods based on the reliability of sensor measurements. By analyzing historical Inactivity Scores, anomalies that potentially represent an emergency can be identified. Evaluations across seven datasets show this approach outperforms existing methods, achieving a mean time to detect emergencies of approximately 05:23:28 hours and producing 0.09 false positives per day under noise-free conditions. Moreover, unlike related approaches, the proposed method remains effective with noisy data.
This thesis demonstrates that emergencies in private households can be detected using existing data sources from the home infrastructure, offering a cost-effective and non-intrusive solution to enhance the safety and autonomy of the elderly at home.}, comment = {entry by: vwindorfer-bogner on behalf of sebastian wilhelm}, groups = {Published}, url = {https://opus4.kobv.de/opus4-uni-passau/frontdoor/index/index/docId/1599}, }
@Article{Lichtenauer2025a, author = {Lichtenauer, Norbert and Guggumos, Johann and Kampmann, Matthias and Kis, Juliane and Laumer, Florian and März, Elena and Wahl, Florian and Wilhelm, Sebastian}, journal = {Data}, title = {Expert Experiences in Anonymizing Personal Data and Its Use as Open Data: Qualitative Insights}, year = {2025}, issn = {2306-5729}, month = jul, number = {7}, pages = {105}, volume = {10}, abstract = {Introduction: The effective and meaningful use of anonymized personal data, including open data, is globally significant across various sectors. Enhancing data utilization aims to generate substantial societal benefits and added value through innovations, products, and services. However, several legal, ethical, and technical challenges currently hinder the development and broader adoption of open data. Furthermore, the availability of technical support tools with high usability is especially desirable to facilitate the anonymization process effectively. Methods: As part of the EAsyAnon research project, preliminary insights were gathered through a scoping review that identified factors promoting or impeding the anonymization and use of personal data. Based on these findings, a structured interview guide was developed. Following a pretest, 19 interviews were conducted with diverse stakeholders from healthcare institutions, research organizations, public authorities, and private companies. The collected data were analyzed using Kuckartz’s structural content analysis methodology, supported by qualitative analysis software. Results: The content analysis yielded five overarching categories and 21 subcategories. These encompassed stakeholder experiences related to anonymization and open data processes, the various types and formats of personal data, identified barriers and enabling factors, support services, and the ethical and legal considerations associated with anonymization. Discussion: The findings highlight significant uncertainty among stakeholders regarding the anonymization of personal data. Although the importance and potential applications of open data for innovation and continuous improvement are widely acknowledged and supported, numerous challenges persist at both the macro and micro levels. The results emphasize a clear need for targeted support measures to address these challenges effectively.}, comment = {entry: vwindorfer-bogner on behalf of sebastian wilhelm}, doi = {10.3390/data10070105}, groups = {Published, DIT Repository}, keywords = {open data; anonymization; personal data; data use; data value creation}, publisher = {MDPI AG}, }
@Article{Buchner_2025, author = {Buchner, Benedikt and Schmidt, Sebastian and Wilhelm, Sebastian}, journal = {Datenschutz und Datensicherheit - DuD}, title = {Service-Roboter im Krankenhaus: Zur datenschutzrechtlichen Bewertung von sprachgesteuerten Systemen}, year = {2025}, issn = {1862-2607}, month = aug, number = {8}, pages = {527--532}, volume = {49}, abstract = {Sprachgesteuerte Systeme eröffnen vielfältige Einsatzmöglichkeiten im Krankenhaus, werfen jedoch komplexe datenschutzrechtliche Fragen auf. Dieser Artikel analysiert die rechtliche Zulässigkeit der Sprachsteuerungsfunktion von Service-Robotern in bayerischen Krankenhäusern. Im Fokus stehen die Vorgaben der DS-GVO, des BDSG und des BayKrG sowie die Frage, ob Sprachdaten als personenbezogene und ggf. besonders sensible Daten einzuordnen sind. An einem konkreten Anwendungsfall wird untersucht, inwieweit der Einsatz von Robotern mit Sprachsteuerung im öffentlichen Bereich eines Krankenhauses im Rahmen von Serviceaufgaben zulässig ist. Der Beitrag zeigt eine Argumentationskette für eine rechtskonforme und praktikable Nutzung unter Beachtung technischer Maßnahmen wie lokaler Verarbeitung und unmittelbarer Löschung der Audioaufzeichnungen auf.}, comment = {entry by: vwindorfer-Bogner on behalf of: sebastian wilhelm}, doi = {10.1007/s11623-025-2133-0}, groups = {Published, DIT Repository}, publisher = {Springer Science and Business Media LLC}, url = {https://link.springer.com/article/10.1007/s11623-025-2133-0}, }
@InProceedings{AI4CARE_Wahl_2022, author = {Wahl, Florian and Breslein, Matthias and Elser, Benedikt}, title = {On-demand forklift hailing system for Intralogistics 4.0}, year = {2022}, pages = {878--886}, publisher = {Elsevier BV}, volume = {200}, abstract = {The shift to I4.0 is happening. While large companies have a range of solutions to implement that change, small and medium-sized enterprises (SME) fall short on solutions tailored for their specific needs. To support SMEs in their transformation toward I4.0, we propose a lightweight system to hail forklifts in a production facility of a medium-sized enterprise. Existing shop floor workflows are implemented within the system and allow machine operators to hail forklift drivers using an embedded or a web-based client. Forklift drivers receive driving instructions on their smartphones. Shift managers can monitor intralogistic activities on a dashboard. Management can extract relevant production and forklift KPIs from the system. In a two-week evaluation phase, we installed our system in a production facility for injection moulded plastic parts. We equipped 12 machines and two forklifts and registered a total of 690 jobs. We found half of the jobs were picked up in 4:05 min and 80% of all jobs were completed in less than 40:02 min.}, comment = {entry: vwindorfer-bogner source: GScholar}, doi = {10.1016/j.procs.2022.01.285}, groups = {Published}, issn = {1877-0509}, journal = {3rd International Conference on Industry 4.0 and Smart Manufacturing; Procedia Computer Science,}, keywords = {smart manufacturingindustry 4.0smart production}, url = {https://www.sciencedirect.com/science/article/pii/S1877050922002940?via=ihub}, }
@InProceedings{AI4CARE_Wahl_2018, author = {Wahl, Florian and Amft, Oliver}, title = {Data and Expert Models for Sleep Timing and Chronotype Estimation from Smartphone Context Data and Simulations}, year = {2018}, month = sep, number = {3}, pages = {1--28}, publisher = {Association for Computing Machinery (ACM)}, volume = {2}, abstract = {We present a sleep timing estimation approach that combines data-driven estimators with an expert model and uses smartphone context data. Our data-driven methodology comprises a classifier trained on features from smartphone sensors. Another classifier uses time as input. Expert knowledge is incorporated via the human circadian and homeostatic two process model. We investigate the two process model as output filter on classifier results and as fusion method to combine sensor and time classifiers. We analyse sleep timing estimation performance, in data from a two-week free-living study of 13 participants and sensor data simulations of arbitrary sleep schedules, amounting to 98280 nights. Five intuitive sleep parameters were derived to control the simulation. Moreover, we investigate model personalisation, by retraining classifiers based on participant feedback. The joint data and expert model yields an average relative estimation error of -2±62 min for sleep onset and -5±70 min for wake (absolute errors 40±48 min and 42±57 min, mean median absolute deviation 22 min and 15 min), which significantly outperforms data-driven methods. Moreover, the data and expert models combination remains robust under varying sleep schedules. Personalising data models with user feedback from the last two days showed the largest performance gain of 57% for sleep onset and 59% for wake up. Our power-efficient smartphone app makes convenient everyday sleep monitoring finally realistic.}, comment = {entry: vwindorfer-bogner source: GScholar}, doi = {10.1145/3264949}, groups = {Published}, issn = {2474-9567}, journal = {Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies}, }
@Article{Kulko_2023, author = {Kulko, Roman-David and Pletl, Alexander and Mempel, Heike and Wahl, Florian and Elser, Benedikt}, journal = {Sensors}, title = {OpenVNT: An Open Platform for VIS-NIR Technology}, year = {2023}, issn = {1424-8220}, month = mar, number = {6}, pages = {3151}, volume = {23}, abstract = {Spectrometers measure diffuse reflectance and create a “molecular fingerprint” of the material under investigation. Ruggedized, small scale devices for “in-field” use cases exist. Such devices might for example be used by companies in the food supply chain for inward inspection of goods. However, their application for the industrial Internet of Things workflows or scientific research is limited due to their proprietary nature. We propose an open platform for visible and near-infrared technology (OpenVNT), an open platform for capturing, transmitting, and analysing spectral measurements. It is built for use in the field, as it is battery-powered and transmits data wireless. To achieve high accuracy, the OpenVNT instrument contains two spectrometers covering a wavelength range of 400–1700 nm. We conducted a study on white grapes to compare the performance of the OpenVNT instrument against the Felix Instruments F750, an established commercial instrument. Using a refractometer as ground truth, we built and validated models to estimate the Brix value. As a quality measure, we used coefficient of determination of the cross-validation (𝑅2𝐶𝑉) between the instrument estimation and ground truth. With 0.94 for the OpenVNT and 0.97 for the F750, a comparable 𝑅2𝐶𝑉 was achieved for both instruments. OpenVNT matches the performance of commercially available instruments at one tenth of the price. We provide an open bill of materials, building instructions, firmware, and analysis software to enable research and industrial IOT solutions without the limitations of walled garden platforms.}, comment = {entry by: vwindorfer-bogner source: GScholar}, doi = {10.3390/s23063151}, groups = {Published}, keywords = {visible and near infrared spectroscopy; open source; instrumentation; spectrometer; chemometrics; nondestructive evaluation; fruit quality}, publisher = {MDPI AG}, }
@Article{AI4CARE_Wahl_2017, author = {Wahl, Florian and Zhang, Rui and Freund, Martin and Amft, Oliver}, journal = {Computer}, title = {Personalizing 3D-Printed Smart Eyeglasses to Augment Daily Life}, year = {2017}, issn = {0018-9162}, month = feb, number = {2}, pages = {26--35}, volume = {50}, comment = {entry by vwindorfer-bogner
source: GScholar}, doi = {10.1109/MC.2017.44}, groups = {Published}, keywords = {Solid Modeling, Data Models, Lenses, Smart Devices, Monitoring, Biomedical Monitoring, Ubiquitous Computing, Human Factors, Human Augmentation, Mobile, Ubiquitous Computing, Wearable Computers, Wearables, Smart EyeglassesAbstract}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, }@Article{AI4CARE_Sommer_2024a, author = {Sommer, Domenic and Kasbauer, Jakob and Jakob, Dietmar and Schmidt, Sebastian and Wahl, Florian}, journal = {Nursing Reports}, title = {Potential of Assistive Robots in Clinical Nursing: An Observational Study of Nurses’ Transportation Tasks in Rural Clinics of Bavaria, Germany}, year = {2024}, issn = {2039-4403}, month = jan, number = {1}, pages = {267--286}, volume = {14}, abstract = {Transportation tasks in nursing are common, often overlooked, and directly impact patient care time in the context of staff shortages and an aging society. Current studies lack a specific focus on transportation tasks, a gap our research aims to fill. By providing detailed data on transportation needs in nursing, our study establishes a crucial foundation for the development and integration of assistive robots in clinical settings. In July and September 2023, we conducted weekly observations of nurses to assess clinical transportation needs. We aim to understand the economic impact and the methods nurses use for transportation tasks. We conducted a participant observation using a standardized app-based form over a seven-day observation period in two rural clinics. N = 1830 transports were made by nurses and examined by descriptive analysis. Non-medical supplies account for 27.05% (n = 495) of all transports, followed by medical supplies at 17.32% (n = 317), pharmacotherapy at 14.10% (n = 258) and other other categories like meals or drinks contributing 12.68% (n = 232). Most transports had a factual transport time of under a minute, with patient transport and lab samples displaying more variability. In total, 77.15% of all transports were made by hand. Requirements to collect items or connect transports with patient care were included in 5% of all transports. Our economic evaluation highlighted meals as the most costly transport, with 9596.16 € per year in the observed clinics. Budget-friendly robots would amortize these costs over one year by transporting meals. We support understanding nurses’ transportation needs via further research on assistive robots to validate our findings and determine the feasibility of transport robots.}, comment = {entry by: vwindorfer-bogner source: GScholar}, doi = {10.3390/nursrep14010021}, groups = {Published}, keywords = {logistics,nursing task analysis,intra-hospital transfer,time and motion study,assistive}, publisher = {MDPI AG}, url = {https://www.mdpi.com/2039-4403/14/1/21}, }
@Article{Sommer_2023, author = {Sommer, Domenic and Kasbauer, Jakob and Jakob, Dietmar and Schmidt, Sebastian and Wahl, Florian}, title = {Investigating Transportation Needs in Clinical Nursing – Observational Task Assessment in Rural Clinics}, year = {2023}, month = oct, doi = {10.20944/preprints202310.1755.v1}, publisher = {MDPI AG}, }
@Article{Sommer_2024c, author = {Sommer, Domenic and Pletl, Eva and Fischer, Stefan}, journal = {Pflegezeitschrift}, title = {Hereinspaziert: Zugangskontrollen durch Roboter}, year = {2024}, issn = {2520-1816}, month = jul, number = {8}, pages = {56--59}, volume = {77}, comment = {entry by: vwindorfer-bogner on behalf of Domenic Sommer}, doi = {10.1007/s41906-024-2645-5}, groups = {Published}, keywords = {Pandemien,Covid-19,Sicherheit,Serviceroboter,5G Campusnetze,Infektionsschutz}, publisher = {Springer Science and Business Media LLC}, }
@Article{AI4CARE_Sommer2024f, author = {Sommer, Domenic and Riedel, Stefan and Schmidt, Sebastian}, journal = {Pflegezeitschrift}, title = {Smarte Helfer: Serviceroboter im Einsatz}, year = {2024}, issn = {2520-1816}, month = apr, number = {5}, pages = {54--58}, volume = {77}, abstract = {Demografischer Wandel, Fachkräftemangel und Pandemien führen zu einer hohen Belastung der Pflegenden und zu Zeitknappheit in der direkten Patientenversorgung. Gleichzeitig verbringen Pflegende einen großen Teil ihrer Arbeitszeit mit nicht originär pflegerischen Tätigkeiten (z.B. Transport). Da aber die Pflege am Patientenbett besonders wichtig ist, bedarf es alternativer Ansätze. Eine Lösung ist die Übernahme repetitiver Transportaufgaben durch Serviceroboter. Durch die Vermeidung unnötiger Laufstrecken oder die Unterstützung beim Transport schwerer Lasten können physische Belastungen reduziert werden. Welche Potenziale für Roboter in der Pflege existieren, untersuchte die vorliegende Beobachtungs- und Interviewstudie an zwei ländlichen Kliniken in Niederbayern.}, comment = {entry by: vwindorfer-bogner on behalf of: Domenic Sommer}, doi = {10.1007/s41906-024-2608-x}, groups = {Published}, keywords = {Fachkräftemangel,Serviceroboter,Assistive Technologien,Logistik}, publisher = {Springer Science and Business Media LLC}, }
@Article{AI4CARE_Sommer_2025, author = {Sommer, Domenic and Riedel, Stefan and Schmidt, Sebastian}, journal = {Die Urologie}, title = {Smarte Helfer: Serviceroboter im Einsatz}, year = {2025}, issn = {2731-7072}, month = feb, number = {5}, pages = {54--58}, volume = {77}, abstract = {Demografischer Wandel, Fachkräftemangel und Pandemien führen zu einer hohen Belastung der Pflegenden und zu Zeitknappheit in der direkten Patientenversorgung. Gleichzeitig verbringen Pflegende einen großen Teil ihrer Arbeitszeit mit nicht originär pflegerischen Tätigkeiten (z.B. Transport). Da aber die Pflege am Patientenbett besonders wichtig ist, bedarf es alternativer Ansätze. Eine Lösung ist die Übernahme repetitiver Transportaufgaben durch Serviceroboter. Durch die Vermeidung unnötiger Laufstrecken oder die Unterstützung beim Transport schwerer Lasten können physische Belastungen reduziert werden. Welche Potenziale für Roboter in der Pflege existieren, untersuchte die vorliegende Beobachtungs- und Interviewstudie an zwei ländlichen Kliniken in Niederbayern.}, comment = {entry by: vwindorfer-bogner on behalf of: Domenic Sommer}, doi = {10.1007/s00120-025-02537-1}, groups = {Published}, keywords = {Fachkräftemangel,Serviceroboter,Assistive Technologien,Logistik}, publisher = {Springer Science and Business Media LLC}, }