Ambient Assisted Living Technologies Research Articles

How deep is your trust? A comparative user requirements’ analysis of automation in medical and mobility technologies

In a changing world full of innovative technologies, trust and trust requirements are increasingly important for designing user-centred systems and ensuring their long-term implementation. In this study, we explored and compared the requirements of future users to build trust in the two contexts of medical and mobility technology by considering Ambient Assisted Living technologies (AAL) and Shared Autonomous Vehicles (SAV). We conducted an online survey study with N = 143 participants. The results show significant differences in the evaluation of individual trust requirements in the two contexts about data sharing, data privacy and security as well as customization. Using a cluster analysis, we identified distinct user groups and trust personalities in both contexts (medicine and mobility). The clusters differ in terms of innovation openness and risk readiness, initial trust, and presence of chronic illness. Correlation analyses revealed significant relationships between people’s initial perceived trust in technology in the two contexts and their assessment of trust requirements, as well as their behavioural intentions to use SAV or AAL systems. Our findings indicate that trust requirements are context-specific and influenced by individual characteristics. This knowledge can be used to inform developers and distributors of technologies to design, build, and manage systems that meet the needs of future users.

Somebody is watching me? Analyzing privacy preferences in using visual AAL technology considering human-, technology-, and context-related factors

AbstractChanging age structures, increasing demands for care, and personnel shortages require innovative approaches to enable support for older and frail people in their everyday life enhancing their well-being, safety, and independence. Visual Ambient Assisted Living (AAL) technologies represent a promising approach to tackle these challenges by detecting emergency situations, such as falls, abnormal behavior, and helplessness. Beyond this potential and possible advantages, the use of visual AAL technology is closely connected with concerns regarding privacy and data security. So far, privacy perceptions and requirements have neither been specifically nor quantitatively investigated regarding the usage of visual AAL technology. Therefore, this study (N = 139) applied an online survey and aimed at an investigation of (1) potential differences between human and technological invasions of privacy based on affective evaluations and perceived concerns, (2) activities being (not) allowed to be visually recorded in different contexts, and (3) selections of specific visual AAL technologies in different contexts. The results identified significant differences in the affective evaluation of human and technological privacy invasions as well as specifically perceived privacy concerns. Beyond that, the acceptance of visual recordings of activities depends on the context as well as on the sensitivity of the daily activities. The context also impacted the selection of specific visual AAL technology distinctly. The study enabled a first quantification of specific privacy perceptions, concerns, and requirements when visual AAL technology is used. The results are used to derive specific design and communication recommendations to address future users’ privacy needs in the conceptualization, development, and design of visual AAL technology.

Eyes on privacy: acceptance of video-based AAL impacted by activities being filmed.

The use of video-based ambient assisted living (AAL) technologies represents an innovative approach to supporting older adults living as independently and autonomously as possible in their homes. These visual devices have the potential to increase security, perceived safety, and relief for families and caregivers by detecting, among others, emergencies or serious health situations. Despite these potentials and advantages, using video-based technologies for monitoring different activities in everyday life evokes concerns about privacy intrusion and data security. For a sustainable design and adoption of such technical innovations, a detailed analysis of future users' acceptance, including perceived benefits and barriers is required and possible effects and privacy needs of different activities being filmed should be taken into account. Therefore, the present study investigated the acceptance and benefit-barrier-perception of using video-based AAL technologies for different activities of daily living based on a scenario-based online survey (N = 146). In the first step, the results identified distinct evaluation patterns for 25 activities of daily living with very high (e.g., changing clothes, showering) and very low privacy needs (e.g., gardening, eating, and drinking). In a second step, three exemplary activity types were compared regarding acceptance, perceived benefits, and barriers. The acceptance and the perceived benefits of using video-based AAL technologies revealed to be higher in household and social activities compared to intimate activities. The strongest barrier perception was found for intimate activities and mainly regarded privacy concerns. The results can be used to derive design and information recommendations for the conception, development, and communication of video-based AAL technologies in order to meet the requirements and needs of future users.

Assistance from the Ambient Intelligence: Cyber–physical​ system applications in smart buildings for cognitively declined occupants

Caregivers have traditionally provided assistance and care to patients with cognitive decline, but this has resulted in financial and emotional burdens for both caregivers and patients, impacting their quality of life. To address this issue, Ambient Assistive Living (AAL) technologies that incorporate Internet of Things (IoT) and Artificial Intelligence (AI) can replace or complement caregivers by enabling intelligent learning in smart buildings. This review evaluates the intelligence complements provided by smart buildings enabled with such capabilities to increase the quality of life and autonomy of cognitively declined occupants. Existing contributions primarily focus on learning occupants’ behavior to identify assistive services and solutions, which are delivered through technological interventions or caregivers. However, there are several key research gaps that need to be addressed. The most important is the lack of adequate implementation of technological interventions to fully support the occupants’ autonomy and independence. Other gaps include challenges in usability and acceptability, ethical concerns, systems’ comprehensiveness, and the need for human-in-the-loop. To address these gaps, a conceptual framework is proposed as future research directions for the applications of smart buildings supporting cognitively declined occupants. The framework aims to facilitate the implementation of technological interventions that can enhance occupants’ autonomy and independence, address usability and acceptability challenges, and ensure ethical considerations and system comprehensiveness. This review provides insights into the current state-of-the-art of AAL technologies and highlights research directions for improving the quality of life and autonomy of cognitively declined occupants.

The Impact of Heterogeneity in Consumers’ Socio-Demographic Characteristics on the Acceptance of Ambient Assisted Living Technology for Older Adults Monitoring in the Home Context

With the accelerating pace of global aging, ambient assisted living (AAL) technology is expected to ease the conflict between medical supply and demand resources in long-term home care. The key to the general adoption of AAL technology is to capture the differentiated product demand of a consumer class that is heterogeneous in socio-demographics and preferences. In this study, we proposed a tailored technology acceptance model to examine the factors affecting AAL technology acceptance from multi-consumer perspectives based on a sample of 451 respondents obtaining the differences in influence paths of AAL technology acceptance for different consumer groups. Almost all subgroups regarded perceived usefulness as having a decisive role. Family caregivers, women, and single-generational households were more concerned about perceived ease of use than matched groups, and higher educated groups and multi-generational households took price value as the priority objective. This research provides guidelines for promoting AAL technology in management practices.

SMART HOME DATA VISUALIZATION FOR PROACTIVE HEALTH MONITORING OF COMMUNITY DWELLING OLDER ADULTS

Abstract The role of Ambient Assistive Living and smart home technologies, which utilize unobtrusive sensors to detect changes in health, is becoming increasingly important in the delivery of healthcare services to older adults. However, these technologies must be designed to meaningfully incorporate into clinicians’ decision making. Research has shown when clinicians are engaged in the design process of smart home systems, the accuracy and efficacy of the systems are improved. We present the process undertaken by a team of nurse researchers and computer science engineers to design clinically meaningful behavior markers derived from smart home sensor data that can be used by nurses to proactively identify changes in patient status. During the first phase of design, nurse researchers qualitatively analyzed time series from smart home sensors installed in the homes of community dwelling older adults and identified patterns in these data related to significant health changes. From this analysis, we assembled a candidate list of 15 sensor-based behavior metrics, such as percent time spent in each room or frequency of bathroom use. During the second phase of design, we will build on lessons we learned from participatory design to create behavior markers and visualizations that are inspired by clinical experience. These include visualizing behavior change over time, highlighting behavioral anomalies at multiple time scales, and calculating markers that are not directly observable such as time spent out of home. Lessons learned from clinicians using the data visualizations to proactively screen for health changes in near real time will also be discussed.

AAL and Internet of Medical Things for Monitoring Type-2 Diabetic Patients.

Due to an aging population, assisted-care options are required so that senior citizens may maintain their independence at home for a longer time and rely less on caretakers. Ambient Assisted Living (AAL) encourages the creation of solutions that can help to optimize the environment for senior citizens with assistance while greatly reducing their challenges. A framework based on the Internet of Medical Things (IoMT) is used in the current study for the implementation of AAL technology to help patients with Type-2 diabetes. A glucose oxide sensor is used to monitor diabetic elderly people continuously. Spectrogram images are created from the recorded data from the sensor to assess and detect aberrant glucose levels. DenseNet-169 examines and analyzes the spectrogram pictures, and messages are sent to caregivers when aberrant glucose levels are detected. The current work describes both the spectrogram image analysis and the signal-to-spectrogram generating method. The study presents a future perspective model for a mobile application for real-time patient monitoring. Benchmark metrics evaluate the application's performances, including sensitivity, specificity, accuracy, and F1-score. Several cross--validations are used to evaluate the model's performance. The findings demonstrate that the proposed model can correctly identify patients with abnormal blood glucose levels.

A Model for Research of Transitions among Different Care Settings in Smart Lifetime Neighbourhoods

Neighbourhoods in EU member states are ageing, increasingly becoming the subjects of geo-gerontology and supply network analyses. Geo-gerontological aspects of the care and supply networks are becoming essential in the processes of deinstitutionalisation of long-term care and services and are crucial for the successful development and implementation of Ambient Assisted Living technologies (AAL_T). A growing number of older adults suffer from declining functional capacities and, thereby, experience decreased mobility and increasing frailty, which can lead to difficulties in carrying out essential activities of daily living as well as increased exposure to the risk of falls. Aid in managing one's daily life needs to be provided on time and in a properly built environment. Ambient intelligence for real-time monitoring of daily activities and supporting older residents with AAL_T will become essential means by which ageing cities will be able to maintain and improve the quality of life for older adults with declining functional capacities. This development will further influence the delineation of service areas and the timing of services. AAL_T and ambient intelligence will enable older adults to live longer in their dwellings and specialised facilities in the community and postpone or even avoid relocation to a nursing home altogether. Development in AAL_T has raised the possibility of developing more efficient services if the functional area of service networks is optimised. Based on these developments, we propose the adaptation of a multi-state competing risk model based on time to failure as modelled in reliability engineering to model and control the trajectories of declining functional capacities and related events that lead to the ill-health and disabilities. In this model, the built environment and timing in service networks are supposed to be embedded. The final goal of such a model is to support decision making that would extend the physically and mentally active life of seniors and enable them to live autonomously and be engaged with their communities. This paper aims to review the development of condition monitoring systems in ambient technologies, shape the model and propose a future research agenda.

What Characterizes Safety of Ambient Assisted Living Technologies?

Ambient assisted living (AAL) technologies aim at increasing an individual's safety at home by early recognizing risks or events that might otherwise harm the individual. A clear definition of safety in the context of AAL is still missing and facets of safety still have to be shaped. The objective of this paper is to characterize the facets of AAL-related safety, to identify opportunities and challenges of AAL regarding safety and to identify open research issues in this context. Papers reporting aspects of AAL-related safety were selected in a literature search. Out of 395 citations retrieved, 28 studies were included in the current review. Two main facets of safety were identified: user safety and system safety. System safety concerns an AAL system's reliability, correctness and data quality. User safety reflects impact on physical and mental health of an individual. Privacy, data safety and security issues, sensor quality and integration of sensor data, as well as technical failures of sensors and systems are reported challenges. To conclude, there is a research gap regarding methods and metrics for measuring user and system safety in the context of AAL technologies.

Acceptance of Technologies for Aging in Place: A Conceptual Model.

BackgroundOlder adults want to preserve their health and autonomy and stay in their own home environment for as long as possible. This is also of interest to policy makers who try to cope with growing staff shortages and increasing health care expenses. Ambient assisted living (AAL) technologies can support the desire for independence and aging in place. However, the implementation of these technologies is much slower than expected. This has been attributed to the lack of focus on user acceptance and user needs.ObjectiveThe aim of this study is to develop a theoretically grounded understanding of the acceptance of AAL technologies among older adults and to compare the relative importance of different acceptance factors.MethodsA conceptual model of AAL acceptance was developed using the theory of planned behavior as a theoretical starting point. A web-based survey of 1296 older adults was conducted in the Netherlands to validate the theoretical model. Structural equation modeling was used to analyze the hypothesized relationships.ResultsOur conceptual model showed a good fit with the observed data (root mean square error of approximation 0.04; standardized root mean square residual 0.06; comparative fit index 0.93; Tucker-Lewis index 0.92) and explained 69% of the variance in intention to use. All but 2 of the hypothesized paths were significant at the P<.001 level. Overall, older adults were relatively open to the idea of using AAL technologies in the future (mean 3.34, SD 0.73).ConclusionsThis study contributes to a more user-centered and theoretically grounded discourse in AAL research. Understanding the underlying behavioral, normative, and control beliefs that contribute to the decision to use or reject AAL technologies helps developers to make informed design decisions based on users’ needs and concerns. These insights on acceptance factors can be valuable for the broader field of eHealth development and implementation.

Planning Digital Transformation of Care in Rural Areas

Abstract Over the next 30 years, one in three inhabitants of Europe and the USA will be 65 years old or older and nearly half will be 50+. The forms and structure of consumption will change, and the needs of older workers will change the production environment, as well as the requirements of distribution. Older people will become not only an engine of consumption in the silver economy but also valuable human resources, which will require them to adapt to the needs of their working environment. Older adults are exposed to risks of events leading to ill health and disability or even death. The rural population is even further away from service centres, which further prevents timely care and preventive care when needed. Smart silver villages using wireless sensors networks embedded in cyber-physical systems using Internet of Things (IoT) as an infrastructure, along with big data and machine learning can support older adults to stay independent longer in their community and mitigate the risk of events leading to ill health and disability. Ambient Assisted Living technologies offer older adults real-time control of activities in their villages and are expected to improve the control of decline in functional capacities of older adults and therefore, improve their quality of life. Ambient intelligence could enable older adults to live safer and thus, longer, in their villages and postpone or even prevent their relocation to a nursing home. Older adults suffer from frailty and decline in physical and cognitive functional capacities and therefore, experience decreased mobility, which can lead to difficulties with activities of daily living. The central gap found in the literature review is a lack of the common dataset for forecasting the needs of older adults and measurement of quality of technologies embedded in smart villages. We need a proper recording of patterns of decline in functional capacities which can cause events leading to ill health and disability. Development of technologies in the last 20 years has created possibilities for developing various models, tools and techniques for supporting older adults to live safer lives and be more well-connected in their communities. Based on these developments, we propose the multi-state competing risk model for control of events leading to ill health and disabilities and show how to forecast the growth of these needs. This approach is especially important for rural areas where the distances and time delays between detection and reaction are too long.

Using Ambient Assisted Living to Monitor Older Adults With Alzheimer Disease: Single-Case Study to Validate the Monitoring Report.

BackgroundMany older adults choose to live independently in their homes for as long as possible, despite psychosocial and medical conditions that compromise their independence in daily living and safety. Faced with unprecedented challenges in allocating resources, home care administrators are increasingly open to using monitoring technologies known as ambient assisted living (AAL) to better support care recipients. To be effective, these technologies should be able to report clinically relevant changes to support decision making at an individual level.ObjectiveThe aim of this study is to examine the concurrent validity of AAL monitoring reports and information gathered by care professionals using triangulation.MethodsThis longitudinal single-case study spans over 490 days of monitoring a 90-year-old woman with Alzheimer disease receiving support from local health care services. A clinical nurse in charge of her health and social care was interviewed 3 times during the project. Linear mixed models for repeated measures were used to analyze each daily activity (ie, sleep, outing activities, periods of low mobility, cooking-related activities, hygiene-related activities). Significant changes observed in data from monitoring reports were compared with information gathered by the care professional to explore concurrent validity.ResultsOver time, the monitoring reports showed evolving trends in the care recipient’s daily activities. Significant activity changes occurred over time regarding sleep, outings, cooking, mobility, and hygiene-related activities. Although the nurse observed some trends, the monitoring reports highlighted information that the nurse had not yet identified. Most trends detected in the monitoring reports were consistent with the clinical information gathered by the nurse. In addition, the AAL system detected changes in daily trends following an intervention specific to meal preparation.ConclusionsOverall, trends identified by AAL monitoring are consistent with clinical reports. They help answer the nurse’s questions and help the nurse develop interventions to maintain the care recipient at home. These findings suggest the vast potential of AAL technologies to support health care services and aging in place by providing valid and clinically relevant information over time regarding activities of daily living. Such data are essential when other sources yield incomplete information for decision making.

Reference architectures for ambient assisted living: a scoping review protocol

IntroductionFor the first time in human history, the number of older people will be higher than the number of children. The prevalence of chronic diseases, such as hypertension, cardiovascular disease,...

Decision-making framework for using ambient assisted living

PurposeTechnology plays an important role in assisting elderly people to live independently, longer and improve their quality of life and health, in supporting their daily activities, etc. The ageing population becomes a global phenomenon. The population of Saudi Arabia continues to age (>60 years of age) currently (5%) compared to other group ages. In 2050, it will increase rapidly to 20.9% of the Saudi population. The current research aims at examining the barriers that health-care providers in the Kingdom of Saudi Arabia are experiencing in the adoption of ambient assisted living (AAL) technologies among the elderly. The study aims to identify a challenging issue with the increasing the number of elderly among the population in the country, which has highlighted the need to use AAL technology to improve the quality of life among the elderly.Design/methodology/approachThis study involved a community of practice (CoP) study as a method of data collection where data collected were presented and discussed in line with the existing literature review findings.FindingsIn total, 14 factors were identified in this study and discussed in the context of Saudi Arabia, which resulted in developing a decision-making framework for using AAL by health-care providers. Those factors are essential in boosting the usage of technology in improving elderly health in Saudi Arabia.Research limitations/implicationsThis study includes implications for developing a decision-making framework for using AAL.Social implicationsThis study clarifies that technology can connect elderly people with society.Originality/valueIn total, 14 factors were identified in this study and discussed in the context of Saudi Arabia.

Improving the Healthcare Effectiveness: The Possible Role of EHR, IoMT and Blockchain

New types of patient health records aim to help physicians shift from a medical practice, often based on their personal experience, towards one of evidence based medicine, thus improving the communication among patients and care providers and increasing the availability of personal medical information. These new records, allowing patients and care providers to share medical data and clinical information, and access them whenever they need, can be considered enabling Ambient Assisted Living technologies. Furthermore, new personal disease monitoring tools support specialists in their tasks, as an example allowing acquisition, transmission and analysis of medical images. The growing interest around these new technologies poses serious questions regarding data integrity and transaction security. The huge amount of sensitive data stored in these new records surely attracts the interest of malicious hackers, therefore it is necessary to guarantee the integrity and the maximum security of servers and transactions. Blockchain technology can be an important turning point in the development of personal health records. This paper discusses some issues regarding the management and protection of health data exchanged through new medical or diagnostic devices.

Effects of an assisted living platform amongst frail older adults and their caregivers: 6 months vs. 9 months follow-up across a pilot field study

Ambient Assistive Living (AAL) technologies provide promising solutions to support aging-in-place but still lack ecological validation. Frail older Individuals (FIs) are at high risk of losing their autonomy but are also acknowledged to be an optimal target population for dependency prevention based on environmental supports. In this context, a recent study revealed some promising short-term benefits of an AAL platform in supporting FIs’ everyday functioning and releasing caregiver burden. Research aim: Complementarily to this first study, we aimed to address near and far effects of an AAL platform on FIs’ everyday functioning and caregiver burden. Method: HomeAssist is an AAL platform providing environmental support thanks to services including activity verification, safety alerts, reminders, communication and leisure activities. HomeAssist efficacy has been evaluated in a field study including a nine-month deployment in the home of sixteen cognitively healthy (MMSE > 25) FIs living alone. Several efficacy measures were taken and compared to a control group (n=16), matched by age, gender, cognitive functioning and frailty condition. These measures included FIs’ autonomy (self-reported and reported by a caregiver) and caregiver burden (for supporting FIs’ autonomy and professional burnout) and were assessed at baseline, six, and nine months later. Results: Our results indicated that: (1) FIs’ autonomy reported by caregivers is improved over time for the equipped group, with a greater extent after 9 months; (2) FIs’ self-perception of everyday functioning remained constant after 9 months for the equipped group, whereas it slightly decreased for the control group; and (3) caregivers reported less burden across time in the equipped group compared to control group; while HomeAssist intervention did not significantly impact professional burden. Conclusion: Taken together, this suggests that near effects of HomeAssist are not only due to novelty, but rather benefits from HomeAssist intervention.

INFERRING ADL BEHAVIORS FROM HIGH DENSITY, AMBIENT, INTERNET OF THINGS SENSOR DATA USING MACHINE LEARNING

To address the growing desire for older adults to age-in-place, there has been an influx of research and development in telehealth services that utilize smart home and ambient assisted living (AAL) technology. AAL technology is designed to care for, remotely monitor, and support healthy aging. The challenge with AAL technology is to accurately classify an older adults’ activities and provide a baseline for detecting changes in physical and cognitive state. We employ (1) rules-based, (2) Latent Dirichlet Allocation (LDA) and (3) auto-encoders (a type of neural network) to infer activities of daily living and instrumented activities of daily living behavior from low-level Internet of Things sensor data. We apply our techniques to a large dataset over 5 older adults in independent living apartments, for over 5 months with 30 to 50 ambient sensors per apartment. Findings highlighted three main themes: (1) lessons learned, (2) an evaluation of the various approaches employed, and (3) a semi-automated methodology to label large volumes of raw sensor data.

Nothing Else Matters! Trade-Offs Between Perceived Benefits and Barriers of AAL Technology Usage.

Ambient assisted living (AAL) technologies present one approach to counter the challenges of demographic change in terms of an aging population, rising care needs, and lacking care personnel by supporting (older) people in need of care and enabling a longer and more independent staying at own home. Although the number of studies focusing on AAL users' acceptance and perception has increased in the last years, trade-off decisions—the weighing of perceived benefits and barriers of technology usage—have not been studied so far. Nevertheless, this is of high relevance: A realistic evaluation of adoption behaviors in different stakeholders (patients, care personnel) requires an understanding of exactly the weighing process of benefits against the barriers in line with the decision of the final willingness to use AAL technology. The current study applied a conjoint analysis approach and investigates people's decision behavior to use an AAL system for a family member in need of care. Study participants (n = 140) had to decide between realistic care scenarios consisting of different options of two benefits (increase in safety, relief of caring burden of relatives) and two barriers (access to personal data and data handling) of technology usage. Results revealed data access and privacy to be most relevant for the decision to use AAL technology at home. However, care experience essentially influenced the decision patterns. For the care experienced group, data access should be limited to most trusted persons and close relatives, rather than to medical professionals. The most important reasons to use AAL are the emotional relief and the felt safety for the person in care. For care novices, in contrast, data access should be in the exclusive responsibility of medical professionals. The reasons that militate in favor of using AAL technology are the increase in process efficiency and medical safety. The results are useful to develop user-tailored technology concepts and derive user-specific communication guidelines within and across clinical and home care contexts.

Health Technology Assessment: The Role of Total Cost of Ownership

Abstract Background: Recently the European Union, through its Horizon 2020 fund has awarded numerous research projects tasked with the development of cloud-based health technology solutions. A number of these projects have a specific focus on ambient assisted living (AAL) technologies; solutions that offer a unique opportunity to improve the quality of life of persons with mild cognitive impairments. The diffusion of these solutions across a European wide cloud infrastructure presents a novel opportunity to reduce economic pressures currently experienced by European health systems. However, no route to market framework currently exists for a European wide healthcare delivery system. Objectives: The goal of the paper is to conduct the review and develop the literature around technology assessment for AAL technologies and route to market frameworks. Methods/Approach: We highlight the role of Total Cost of Ownership (TCO) when conducting a technology assessment by reviewing existent literature. Results: We discuss three TCO models that can support the assessment of AAL technologies. Conclusions: There is a gap in the analysis of TCO models in the context of AAL technologies particularly in public and private sector collaborations. TCO process should be developed into a key award criterion when conducting AAL technology assessment and procurements, thus aiding long term strategic decision making.

Ambient Assisted Living as Support for Aging in Place: Quantitative Users’ Acceptance Study on Ultrasonic Whistles

BackgroundGiven the fact of an aging society, new supply measures and living concepts are needed, especially as health impairments along with care dependency increase with age. As many elderly people wish to stay at home for as long as possible, ambient assisted living (AAL) represents a support for aging in place.ObjectiveAAL combines medical and care technology within living environments and is, therefore, a promising approach to cope with demographic change in terms of fast-growing care needs and fewer skilled workers. Ultrasonic whistles represent one innovative technical possibility for such supportive housing solutions. Central fields of application are home automation, emergency service, and positioning. As AAL technologies affect sensitive areas of life, it is of great interest under which conditions they are accepted or rejected, taking individual user requirements into account. Hence, the aim of this study was to investigate users’ perception and evaluation of ultrasonic whistles.MethodsIn this study, we examined the acceptance of ultrasonic whistles in home care by function and room using a Web-based questionnaire. Besides an evaluation of the overall usefulness, we focused on the intention to use ultrasonic whistles; 270 participants assessed home automation, emergency service, and positioning as specific functions of ultrasonic whistles. Furthermore, bathroom, bedroom, and living room were evaluated as specific usage locations (rooms). With regard to the user’s perspective, the focus was set on age and attitudes toward aging of care receivers.ResultsThis study revealed a significant influence of function (F2,269=60.444; P<.001), room (F2,269=41.388; P<.001), and the interaction of function and room (F4,269=8.701; P<.001) on the acceptance of ultrasonic whistles. The use of emergency services within the bathroom represented the most accepted alternative, whereas positioning within the living room received the comparably lowest evaluations. Although user diversity played a minor role for acceptance overall, the assessment of single applications differed among user groups, particularly with regard to age differences (F20,500=1.988; P<.01) in the evaluation of specific installation options such as automated doors.ConclusionsThe study revealed profound insights into the user-centered assessment of ultrasonic whistles in home care and discovered function and room as influencing acceptance parameters. Concerning user characteristics, age, and attitude toward aging partly affected these evaluations, forming the basis for and showing the importance of further investigations in this context.