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BACKGROUND The workload in healthcare is steadily increasing – healthcare professionals (HCP) report stress and a very demanding environment. As a result, mental health issues are on the rise among HCP, the proneness to errors in tasks could increase. The digitization of patient care is intended to counteract processes of demographic change, that could be in relation to high stress levels. It remains unclear whether the Health Information System(s) (HIS) and digital health technologies (DHT) used, relieve the professionals or even represent a further burden. The mental construct that describes this burden of technologies is Mental Workload (MWL). Work in the clinic can be viewed as working in safety-critical environments: Particularly in this sensitive setting, the measurement methods of MWL are relevant - mainly due to their strongly differing intrusiveness and sensitivity. The method of eye tracking could provide a useful way to measure MWL directly in the field. OBJECTIVE The systematic review addresses two different, but related objectives. 1. In which manner do DHT contribute to the overall MWL of health care workers: which aspects or factors of DHT contribute to an increase of MWL? 2. Which methods/ assessments are applied to measure MWL related to HIS/ Digital Technologies? 2.1. Which role does Eye tracking/ Pupillometry play in context of measure? 2.2. Which outcomes are being assessed via eye tracking? METHODS Following the PRISMA statement, we conducted a systematic review. Based on the research questions, we defined keywords that were combined to search terms. The review followed the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis and data synthesis. RESULTS The literature search process resulted in 25 included studies that have studied the resulting MWL of healthcare workers from using DHT in health care settings. The main results can be grouped by two categories: assessment methods and factors of DHT contributing to MWL. A major part of the studies applied subjective methods for the assessment of MWL (Most applied method: NASA TLX). Eye tracking didn’t play a relevant role. The factors contributing to a higher MWL were clustered by organizational and system factors. CONCLUSIONS Our review of 25 papers shows a diverse assessment approach of MWL related to DHT of HCPs as well as two groups of relevant contributing factors to MWL Although methodological biases were identified, we promote further research concentrating on adequate assessments for relevant settings. We also like to promote the evaluation of quality criteria. CLINICALTRIAL PROSPERO registration: CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271&ID=CRD42021233271 Protocol: JMIR Res Protoc 2021;10(8): e29126; https://doi.org/10.2196/29126

Background: Adverse events are ubiquitous in home ventilation and can jeopardise patient safety. Especially the interaction with life-sustaining medical devices such as the ventilator is a source of potential errors. The goal is to know the errors to be able to react adequately to them. With a systematic analysis of hazards and their causes, measures can be taken to prevent damage to patients.Methods: A systematic adverse event analysing process was conducted to identify the causes for adverse events (AE) in intensive home care. The process consisted of three analysis steps. 1) an input phase consisting of an expert interview, and a questionnaire. 2.) an analysing process into a cause-effect diagram that can lead to cause of adverse events and 3.) risk mitigation measures have been derived to avoid adverse events. Results: The nursing staff indicated transport of the patient and suction, de-cannulation as the most causal factors for adverse events. They would like to have support in the form of checklists for care activities and a reminder function for e.g. tube changes. In the cause-effect diagram, many causes are listed that are addressed in risk mitigation. Here, concrete measures such as devices and care competence but also improvements by the providers and manufacturers are demanded. The first step in dealing with adverse events is transparency and an open approach to errors and near misses. A systematic error analysis can prevent patient harm through a preventive approach.

Usability tests of medical devices are mainly conducted on-site, but remote tests can also be suitable for quick feedback. Using the online survey tool SoSci Survey and videos of a ventilator interface prototype, a usability test environment was developed which allows participation independent of time and place.

BACKGROUND Although nearly one-third of the world’s disease burden requires surgical care, only a small proportion of digital health applications are directly used in the surgical field. In the coming decades, the application of augmented reality (AR) with a new generation of optical-see-through head-mounted displays (OST-HMDs) like the HoloLens (Microsoft Corp) has the potential to bring digital health into the surgical field. However, for the application to be performed on a living person, proof of performance must first be provided due to regulatory requirements. In this regard, cadaver studies could provide initial evidence. OBJECTIVE The goal of the research was to develop an open-source system for AR-based surgery on human cadavers using freely available technologies. METHODS We tested our system using an easy-to-understand scenario in which fractured zygomatic arches of the face had to be repositioned with visual and auditory feedback to the investigators using a HoloLens. Results were verified with postoperative imaging and assessed in a blinded fashion by 2 investigators. The developed system and scenario were qualitatively evaluated by consensus interview and individual questionnaires. RESULTS The development and implementation of our system was feasible and could be realized in the course of a cadaver study. The AR system was found helpful by the investigators for spatial perception in addition to the combination of visual as well as auditory feedback. The surgical end point could be determined metrically as well as by assessment. CONCLUSIONS The development and application of an AR-based surgical system using freely available technologies to perform OST-HMD–guided surgical procedures in cadavers is feasible. Cadaver studies are suitable for OST-HMD–guided interventions to measure a surgical end point and provide an initial data foundation for future clinical trials. The availability of free systems for researchers could be helpful for a possible translation process from digital health to AR-based surgery using OST-HMDs in the operating theater via cadaver studies.

JMIR Serious Games 10(2), e34781 (2022). doi:10.2196/34781, Published by Toronto

Adverse events (AE) are ubiquitous in home mechanical ventilation (HMV) and can jeopardise patient safety. One particular source of error is human interaction with life-sustaining medical devices, such as the ventilator. The objective is to understand these errors and to be able to take appropriate action. With a systematic analysis of the hazards associated with HMV and their causes, measures can be taken to prevent damage to patient health.A systematic adverse events analysis process was conducted to identify the causes of AE in intensive home care. The analysis process consisted of three steps. 1) An input phase consisting of an expert interview and a questionnaire. 2) Analysis and categorisation of the data into a root-cause diagram to help identify the causes of AE. 3) Derivation of risk mitigation measures to help avoid AE.The nursing staff reported that patient transportation, suction and tracheostomy decannulation were the main factors that cause AE. They would welcome support measures such as checklists for care activities and a reminder function, for e.g. tube changes. Risk mitigation measures are given for many of the causes listed in the root-cause diagram. These include measures such as device and care competence, as well as improvements to be made by the equipment providers and manufacturers. The first step in addressing AE is transparency and an open approach to errors and near misses. A systematic error analysis can prevent patient harm through a preventive approach.Risks in HMV were identified based on a qualitative approach. The collected data was systematically mapped onto a root-cause diagram. Using the root-cause diagram, some of the causes were analysed for risk mitigation. For manufacturers, caregivers and care services requirements for intervention offers the possibility to create a checklist for particularly risky care activities.

The Medical Device Directive (MDD) will be replaced on 26.05.2020 by the new Medical Device Regulation (MDR). The European Parliament wants to create a transparent, solid, predictable and sustainable legal framework. One of the major upcoming changes effects the perspective on software as a medical device. This paper describes the fundamental relationships between the policy framework and the challenges faced by manufacturers and operators of medical devices, in particular medical software and artificial intelligence (AI) systems, who need to verify compliance. To address this topic, we review and discuss the main implications of medical device regulations on software as a medical device and digital health applications along the MDR structure. Furthermore, we address practical limitations of the implementation, such as the availability of notified bodies and costs of the approval procedure.

Zusammenfassung Hintergrund Korperliche Aktivitat (KA) ist fur altere Menschen eine wichtige Voraussetzung fur ein gesundes und selbstbestimmtes Leben und schutzt praventiv vor zahlreichen chronischen Krankheiten. Dennoch bewegt sich ein hoher Anteil alterer Menschen nicht ausreichend im Alltag, wodurch neue praventive Strategien entstanden sind. Seit einigen Jahren gewinnen zunehmend auch Gesundheitstechnologien an Bedeutung und bieten ein Potenzial fur die Primarpravention zur Forderung KA. Ziel der Studie war die Analyse von Erfahrung und Akzeptanz im Umgang mit Technologien zur Unterstutzung der KA und zur Uberwachung von Gesundheitsparametern bei Menschen uber 65 Jahren. Neben der Identifizierung von Bedenken, Unsicherheiten und subjektiven Vorstellungen gegenuber Technologien, sollten Anforderungen an praventive Technologien abgeleitet werden. Methode Es wurden Interviews mit einem semi-strukturierten Leitfaden durchgefuhrt. Der Leitfaden beinhaltete die Themen „KA“ und „Technik“. Die Rekrutierung erfolgte uber einen offentlichen Aufruf durch z. B. Presse und Handzettel. Die Auswertung wurde inhaltsanalytisch mit induktiver und deduktiver Kategorienbildung durchgefuhrt. Zusatzlich erfolgte auf der Grundlage der Transkripte interdisziplinar eine Anforderungsanalyse, um Erfordernisse und Anforderungen fur praventive Technologien ableiten zu konnen. Ergebnisse Es konnte mit 33 Personen (19 weiblich) Interviews durchgefuhrt werden. Das durchschnittliche Alter lag bei 75 Jahren. Neun Teilnehmende mit einem Migrationshintergrund kamen aus vier Landern. Die Teilnehmenden waren insgesamt im Alltag aktiv. Als Barrieren konnten u. a. ein fehlender/mangelnder eigener Antrieb und Wetterbedingungen identifiziert werden. Viele Teilnehmende nutzten im Alltag Gesundheitstechnologien wie Aktivitatstracker und sind den Entwicklungen gegenuber eher aufgeschlossen. Dennoch wurden auch Bedenken wie zu dem Thema Datenschutz und -sicherheit geausert. Schlussfolgerung Mit einer heterogenen Zielgruppe konnten erste Erkenntnisse zu den Themen „KA“ und „Technik“ sowie Bedenken, Vorstellungen und Anforderungen fur zukunftige praventive Technologien abgeleitet werden. Damit ein zielgruppenspezifischer Zugang zu den unterschiedlichen Personengruppen gelingen kann, sind sowohl allgemeine (z. B. Aushange, Presse) als auch spezifische Strategien (z. B. Multiplikatoren) sowie ausreichend Zeit wichtig.

BACKGROUND The workload in healthcare is steadily increasing - physicians and nurses report stress as well as a very demanding environment with complex and multiple tasks. As a result, mental health issues are on the rise among health care professionals, the proneness to errors in tasks could increase. The digitization of patient care is intended to counteract processes of demographic change, which are partly the cause of higher stress levels. It remains unclear whether the health information systems (HIS) and digital health technologies (DHT) used relieve the professionals or even represent a further burden. The mental construct that describes this burden of technologies is Mental Workload (MWL). Work in the clinic can be viewed as working in safety-critical environments. Particularly in this sensitive setting, the measurement methods of MWL are relevant - mainly due to their strongly differing intrusiveness and sensitivity. The method of eye tracking could provide a useful way to be able to measure MWL directly in the field. OBJECTIVE The systematic review addresses two different, but related objectives. 1. In which manner do DHT contribute to the overall MWL of health care workers: 1.1. Can we observe a direct or indirect effect of DHT on MWL? 1.2. Which aspects or factors of DHT contribute to an increase of MWL? 2. Which methods/ assessments are applied to measure MWL related to HIS/ DHT? 2.1. Which role does eye tracking/ pupillometry play in context of measure? 2.2. Which outcomes are being assessed via eye tracking? METHODS Following the PRISMA statement, we conduct a systematic review. Based on the research question, we define keywords that we then combine in search terms. The review follows the following steps: literature search, article selection, data extraction, risk of bias assessment, data analysis and data synthesis. RESULTS As the systematic review is currently ongoing, no results are available yet. The preliminary searches have been completed, the piloting of the study selection process as well as the formal screening against eligibility criteria has started. We are currently analyzing the data and expect to complete the review in spring 2021. CONCLUSIONS We are expecting conclusions after finalizing the review. CLINICALTRIAL PROSPERO registration: CRD42021233271; https://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42021233271&ID=CRD42021233271

Applied ergonomics 98, 103544 (2022). doi:10.1016/j.apergo.2021.103544, Published by Elsevier Science, Amsterdam [u.a.]

The user interface of a mechanical ventilator is safety critical, as use errors can lead to patient harm. A systematic review was conducted to identify published usability issues and contributing factors that can lead to use errors. The findings were grouped in an Ishikawa diagram. Many of the problems mentioned based on inconsistent labeling and manufacturer-specific naming of ventilation modes. In the studies, usability was often measured quantitatively and did not allow any conclusions to be drawn about concrete problems.

Beatmungspflichtige Patientinnen und Patienten unterliegen besonderen Gefahren. Ein Ausfall, eine Fehlfunktion oder die Fehlbedienung eines Beatmungsgerates kann binnen kurzer Zeit zur Hypoxie und damit zu irreversiblen Schaden oder dem Tod fuhren. Daraus resultieren unterschiedliche Anforderungen an die Konstruktion und Herstellung von Beatmungsgeraten, aber auch an den Betrieb und die Anwendung von Beatmungsgeraten sowie das Umfeld der Anwendung.

Many studies use eye-tracker to analyse the socio-technical system, also in medical research. Only a few articles describe the use of eye-tracker to examine human-computer interaction in a critical care environment, especially in the field of anaesthesia or surgery. Therefore, we have tested in a feasibility study head-mounted eye-tracker of three different manufactures in a simulated anesthesia surrounding with mankind patient simulators. The research question was to analyse whether the field scene camera of the eye-tracker can be used in the light conditions and changes in brightness of the operating room. In addition, it was tested whether the eye-tracker was still calibrated and held on the subject's head during the resuscitation movement. All eye-trackers tested had a good adaptation on changing light or changing distances.

BackgroundPeriodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture (EDC) tools in interviewer-administered data collection processes. ObjectiveThis study aimed to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of the health and demographic surveillance sites in northwest Ethiopia. MethodsA randomized controlled crossover health care information technology evaluation was conducted from May 10, 2016, to June 3, 2016, in a demographic and surveillance site. A total of 12 interviewers, as 2 individuals (one of them with a tablet computer and the other with a paper-based questionnaire) in 6 groups were assigned in the 6 towns of the surveillance premises. Data collectors switched the data collection method based on computer-generated random order. Data were cleaned using a MySQL program and transferred to SPSS (IBM SPSS Statistics for Windows, Version 24.0) and R statistical software (R version 3.4.3, the R Foundation for Statistical Computing Platform) for analysis. Descriptive and mixed ordinal logistic analyses were employed. The qualitative interview audio record from the system users was transcribed, coded, categorized, and linked to the International Organization for Standardization 9241-part 10 dialogue principles for system usability. The usability of this open data kit–based system was assessed using quantitative System Usability Scale (SUS) and matching of qualitative data with the isometric dialogue principles. ResultsFrom the submitted 1246 complete records of questionnaires in each tool, 41.89% (522/1246) of the paper and pen data capture (PPDC) and 30.89% (385/1246) of the EDC tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.60% for PPDC and EDC, respectively. The chances of more errors on the PPDC tool were multiplied by 1.015 for each additional question in the interview compared with EDC. The SUS score of the data collectors was 85.6. In the qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics. ConclusionsEDC possessed significantly better data quality and efficiency compared with PPDC, explained with fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. Implementation organization needs to consider consistent power source, decent internet connection, standby technical support, and security assurance for the mobile device users for planning full-fledged implementation and integration of the system in the surveillance site.

For elderly people, physical activity (PA) is an important prerequisite for a healthy and self-determined life and provides preventive protection against many chronic diseases. Since a high proportion of this group does not exercise sufficiently in everyday life, new preventive strategies have been developed. In recent years, health technologies have also become increasingly important and offer a potential for primary prevention to promote PA. The aim of this study was to analyze experience with and acceptance of the use of technologies to support PA and to monitor health parameters in people over the age of 65. In addition to identifying concerns, uncertainties and subjective ideas about technologies, requirements for preventive technology should be derived.Guided (semi-structured) interviews were conducted. Interviewing topics included "PA" and "technology". Recruitment took place through a public call and the distribution of flyers. The evaluation was carried out by content analysis with inductive and deductive category formation. In addition, an interdisciplinary requirements analysis was performed on the basis of the transcripts in order to derive needs and requirements for preventive technologies.The interviews were conducted with 33 persons (19 female). The average age was 75 years. Nine participants with a migration background originated from four countries. All participants were active in everyday life. The barriers identified included a lack of motivation and weather conditions. Many participants used health technologies in their everyday lives and were quite open to these developments. However, concern was expressed regarding topics such as data protection and security.Experience and acceptance in dealing with future preventive technologies as well as concerns, ideas and requirements could be inferred from discussions with the heterogeneous target group. General strategies (e.g. notices, press) as well as specific strategies (e.g. multipliers) and sufficient time are important to ensure a target group-specific access to different groups of people.

Summary Introduction: As many medical workflows depend vastly on IT support, great demands are placed on the availability and accuracy of the applications involved. The cases of IT failure through ransomware at the beginning of 2016 are impressive examples of the dependence of clinical processes on IT. Although IT risk management attempts to reduce the risk of IT blackouts, the probability of partial/total data loss, or even worse, data falsification, is not zero. The objective of this paper is to present the state of the art with respect to strategies, processes, and governance to deal with the failure of IT systems. Methods: This article is conducted as a narrative review. Results: Worst case scenarios are needed, dealing with methods as to how to survive the downtime of clinical systems, for example through alternative workflows. These workflows have to be trained regularly. We categorize the most important types of IT system failure, assess the usefulness of classic counter measures, and state that most risk management approaches fall short on exactly this matter. Conclusion: To ensure that continuous, evidence-based improvements to the recommendations for IT emergency concepts are made, it is essential that IT blackouts and IT disasters are reported, analyzed, and critically discussed. This requires changing from a culture of shame and blame to one of error and safety in healthcare IT. This change is finding its way into other disciplines in medicine. In addition, systematically planned and analyzed simulations of IT disaster may assist in IT emergency concept development.

BACKGROUND Periodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture (EDC) tools in interviewer-administered data collection processes. OBJECTIVE This study aimed to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of the health and demographic surveillance sites in northwest Ethiopia. METHODS A randomized controlled crossover health care information technology evaluation was conducted from May 10, 2016, to June 3, 2016, in a demographic and surveillance site. A total of 12 interviewers, as 2 individuals (one of them with a tablet computer and the other with a paper-based questionnaire) in 6 groups were assigned in the 6 towns of the surveillance premises. Data collectors switched the data collection method based on computer-generated random order. Data were cleaned using a MySQL program and transferred to SPSS (IBM SPSS Statistics for Windows, Version 24.0) and R statistical software (R version 3.4.3, the R Foundation for Statistical Computing Platform) for analysis. Descriptive and mixed ordinal logistic analyses were employed. The qualitative interview audio record from the system users was transcribed, coded, categorized, and linked to the International Organization for Standardization 9241-part 10 dialogue principles for system usability. The usability of this open data kit–based system was assessed using quantitative System Usability Scale (SUS) and matching of qualitative data with the isometric dialogue principles. RESULTS From the submitted 1246 complete records of questionnaires in each tool, 41.89% (522/1246) of the paper and pen data capture (PPDC) and 30.89% (385/1246) of the EDC tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.60% for PPDC and EDC, respectively. The chances of more errors on the PPDC tool were multiplied by 1.015 for each additional question in the interview compared with EDC. The SUS score of the data collectors was 85.6. In the qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics. CONCLUSIONS EDC possessed significantly better data quality and efficiency compared with PPDC, explained with fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. Implementation organization needs to consider consistent power source, decent internet connection, standby technical support, and security assurance for the mobile device users for planning full-fledged implementation and integration of the system in the surveillance site.

Medizinprodukte und Gesundheitsanwendungen z. B. aus dem E-Health-Bereich sind heutzutage allgegenwartig. Aus ihrer Nutzung konnen sich potenzielle Risiken fur den Anwender (z. B. dem Patienten) ergeben. Der Gesetzgeber hat daher mit dem Medizinproduktegesetz und den zugehorigen Normen regulatorische Anforderungen an die Software und die Mensch-Maschine-Interaktion von Medizinprodukten gestellt. Die regulatorischen Anforderungen legen alle Schritte von der Zweckbestimmung des Produkts bis zum Inverkehrbringen fest. Hierfur sind eine eingehende Dokumentation und die Einhaltung des strukturierten Vorgehens beim Software-Lebenszyklusprozess und der Gebrauchstauglichkeit notwendig. Die potenziellen Benutzungsfehler in der Mensch-Maschine- Interaktion werden durch einen verschrankten Usability- und Risikomanagementprozess normativ festgelegt und eingefordert. Daher werden die wichtigsten normativen Anforderungen zum Usability Engineering nach DIN EN 62366 und dem Risikomanagement nach DIN EN ISO 14971 praxisnah vermittelt.

Sicherheitskritische Mensch-Computer-Interaktion ist nicht nur derzeit, sondern auch zukunftig ein auserst relevantes Thema. Hierbei kann ein Lehr- und Fachbuch, wie dieses, immer nur einen punktuellen Stand abdecken. Dennoch kann der Versuch unternommen werden, aktuelle Trends zu identifizieren und einen Ausblick in die Zukunft zu wagen. Genau das mochte dieses Kapitel erreichen: Es sollen zukunftige Entwicklungen vorausgesagt und versucht werden, diese korrekt einzuordnen. Das ist an dieser Stelle nicht nur durch den Herausgeber, sondern durch Abfrage bei zahlreichen am Lehrbuch beteiligten Autoren geschehen. Neben einem Ausblick auf Grundlagen und Methoden werden dementsprechend auch sicherheitskritische interaktive Systeme und sicherheitskritische kooperative Systeme abgedeckt.

E-Health als Oberbegriff fur vernetzte und mobile IT im Gesundheitswesen kann zur Sektor ubergreifenden Gesundheitsversorgung beitragen und neue Versorgungsformen etablieren. Technische Innovationen wie z. B. Telemedizin, Ambient Assisted Living (AAL) oder die hausliche Intensivpflege setzen wieder Prozessinnovationen in Gang, die zu einer Erweiterung von Leistungen fuhren und eine umfassende Versorgung gewahrleisten konnen. Innerhalb der E-Health-Domane konnen die Grenzen zwischen Medizin, Pflege und den Gesundheitsleistungen jenseits der Sozialversicherung verschwimmen.

Achieving a good understanding of the socio-technical system in critical or emergency situations is important for patient safety. Research in human-computer interaction in the field of anesthesia or surgery has the potential to improve usability of the user interfaces and enhance patient safety. Therefore eye-tracking is a technology for analyzing gaze patterns. It can also measure what is being perceived by the physician during medical procedures. The aim of this review is the applicability of eye-tracker in the domain of simulated or real environments of anesthesia, surgery or intensive care. We carried out a literature research in PubMed. Two independent researchers screened the titles and abstracts. The remaining 8 full-papers were analyzed based on the applicability of eye-trackers. The articles contain topics like training of surgeons, novice vs. experts or the cognitive workload. None of the publications address our goal. The applicability or limitations of the eye-tracker technology were stated incidentally.

Motivated by the demographic change, many new medical applications are installed in the user's home environment. These applications make use of ambient sensors, enabling new forms of medical care. Personal Health Records (PHRs) are an instrument for the storage, presentation and communication of health related data provided by these applications. But there are still open issues regarding the cooperation between PHRs and the new applications. On the basis of two medical application scenarios, we developed a new model which defines the appropriate level of abstraction of data generated by medical applications to be stored inside the PHR. The model also determines which part of these data is relevant for the clinical decision making process, and how these data should be communicated to physicians. This paper describes the 3DLC model, which uses three dimensions (clinical decision, frequency and context dependence) to determine the type of the data. We further introduce a prototype PHR system that is able to fulfil the requirements of our scenarios.

The integration and commissioning of Ambient Assisted Living (AAL) systems are time consuming and complicated. The lack of interoperability of available AAL system components has to be considered as an obstacle especially for innovative SMEs. In order to ease integration and commissioning of systems, knowledge based methods should be taken into account to enable innovative characteristics such as design automation, self-configuration and self-management. Semantic technologies are suitable instruments for mastering the problems of interoperability of heterogeneous and distributed systems. As an important prerequisite for the emergence of knowledge-based assistance functions a standard for an unambiguous representation of AAL relevant knowledge has to be developed. In this article, the development of an AAL ontology is proposed as a formal basis for knowledge-based system functions. A prototype of an AAL specific ontology engineering process is presented through the modeling example of a formal representation of a sensor block that is part of an AAL Integration Profile proposed by the RAALI project consortium.

The Integration and commissioning of AAL systems are time consuming and complicated. The lack of interoperability of available components for Ambient Assisted Living has to be considered as an obstacle for innovative SMEs. In order to ease integration and commissioning of systems knowledge based methods should be taken into account to enable innovative characteristics of AAL systems such as design automation, self-configuration and self-management. Hence, semantic technologies are suitable instruments which offer the capability for mastering the problems of interoperability of heterogeneous and distributed systems. As an important prerequisite for the emergence of knowledge-based assistance functions a standard for unambiguous representation of AAL-relevant knowledge has to be developed. In this paper, the development of an AAL-ontology is proposed as a formal basis for knowledge-based system functions. A prototype of an AAL specific ontology engineering process is presented through the modeling example of a formal representation of a sensor block which is part of an AAL-Integration Profile proposed by the RAALI consortium.