Expectations are high with regards to smart home technology. In particular, smart home technology is expected to support or enable independent living by older adults. This raises the question: can smart home technology contribute to independent living, according to older adults themselves? This chapter aims to answer this question by reviewing and discussing older adults’ perspectives on independence and their views on smart home technology. Firstly, older adults’ opinions on independence and aging in place are discussed. Secondly, this chapter will review to what extent smart home technology can support older adults’ independence. Thirdly, it will be explained how community-dwelling older adults’ concept of independence entails three distinct types or modes, and how these modes are related to their perceptions and acceptance of technology. In the last section of this chapter, an overview of key points is presented, and recommendations for technology designers, policy makers, and care providers are postulated.
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Purpose People with dementia (PwD) often present Behavioral and Psychological Symptoms of Dementia, which include agitation, apathy, and wandering amongst others, also known as challenging behaviors (CBs). These CBs worsen the quality of life (QoL) of the PwD and are a major source/reason of (increased) caregiver burden. The intricate nature of the symptoms implies that there is no “one size fits all solution”, and necessitates tailored approaches for both PwDs and caregivers. To timely prevent these behaviors assistive technology can be utilized to guide caregivers by enabling remote monitoring of contextual, environmental, and behavioral parameters, and subsequently alarming nurses on early-stage behavioral changes prior to the presentation of CBs. Eventually, the system should propose an intervention/action to prevent escalation. In turn, improvement in QoL for both caregivers and PwD living in nursing homes (NHs) is expected. In the current project “MOnitoring Onbegrepen Gedrag bij Dementie met sensortechnologie” (MOOD-Sense), we aim to develop such a monitoring system. The strengths of this new monitoring system lie in its ability to align with the individual needs of the PwD, utilization of a combination of wearables and ambient sensors to obtain contextual data, such as location or sound, and predict or monitor CBs individually rather than in groups, thus facilitating person-centered care, based on ontological reasoning. The project is divided into three parts, Toolbox A, B and C. Toolbox A focuses on obtaining insight in which behaviors are challenging according to nurses and how they are described. Previous studies utilize clinical terminology to describe or classify behavior, we aim to employ concrete descriptions of behavior that are observable and independent of clinical terminology, aligning with nurses who are often the first to notice behavior and can be operationalized such that it can also be aligned with sensor data. As a result, an ontology will be developed based on the data such that sensor data can be integrated into the same conceptual information that standardizes the communication in our monitoring system. Toolbox B focuses on translating data coming from various sensors into the concepts expressed in the ontology, and timely communicate situations of interest to the caregivers. In Toolbox C the focus is exploring interventions/actions employed in practice to prevent CBs. Method In Toolbox A we used a qualitative approach to collect descriptions of CBs. For this purpose, we employed focus groups (FGs) with nursing staff who provide daily care to PwD. In Toolbox B pilot studies were conducted. A set of experiments using sensors in NHs were performed. During each pilot, multiple PwD with CBs in NHs were monitored with both ambient and wearables sensors. The pilots were iteratively approached, which means that insights from previous pilot studies were used to improve consecutive pilot studies. Lastly, the elaboration of Toolbox C is ongoing. Results and Discussion Regarding Toolbox A four FGs were conducted during the period from January 2023 to May 2024. Each FG was comprised of four nurses (n = 16). From the FGs we gained insights into behavioral descriptions and the context of CBs. Although data analysis has to be performed yet, there are indications that changes preceding CBs can be observed, such as frowning or clenching fists for agitation or aggression. Further results will be available soon. Regarding Toolbox B a monitoring system, based on sensors, is developed iteratively (see Figure 1) and piloted in three consecutive NHs from January 2021 to December 2023. Each pilot was comprised of two PwD (n = 6). Analysis of sensor data is ongoing.
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Abstract Primary healthcare professionals face an increasing number of geriatrics patients, and patient care often involves different disciplines. eHealth offers opportunities to support interprofessional collaboration (IPC). This exploratory study aimed to gain insight in 1) IPC in community-based rehabilitation, 2) facilitators and barriers for technology-based IPC and 3) technological IPC solutions envisioned by the primary healthcare professionals An focus group with six primary healthcare professionals and a design thinking session with four participants were conducted. Data analysis was based upon an IPC model. Results indicate that facilitators and barriers for IPC can be clustered in three categories: human, organization and technology, and provide some requirements to develop suitable IPC technological solutions Primary healthcare professionals recognise the urgency of working collaboratively. Current barriers are understanding each other’s professional vocabulary, engaging the older adults, and using technology within the patient’s environment. Further research is needed to integrate IPC components in a technological solution
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PURPOSE: The early detection of a decline in daily functioning of independently living older people can aid health care professionals in providing preventive interventions. To monitor daily activity patterns and, thereby detect a decline in daily functioning, new technologies, such as sensors can be placed in the home environment. The purpose of this qualitative study was to determine the perspectives of older people regarding the use of sensor monitoring in their daily lives.DESIGN AND METHODS: We conducted indepth, semistructured interviews with 11 persons between 68 and 93 years who had a sensor monitoring system installed in their home. The data were analyzed using Interpretative Phenomenological Analysis.RESULTS: The interviewed older persons positively valued sensor monitoring and indicated that the technology served as a strategy to enable independent living. The participants perceived that the system contributed to their sense of safety as an important premise for independent living. Some of the participants stated that it helped them to remain active. The potential privacy violation was not an issue for the participants. The participants considered that health care professionals' continuous access to their sensor data and use of the data for their safety outweighed the privacy concerns.IMPLICATIONS: These results provide new evidence that older persons experience sensor monitoring as an opportunity or strategy that contributes to independent living and that does not disturb their natural way of living. Based on this study, the development of new strategies to provide older people with access to their sensor data must be further explored.
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From Springer description: "We present the design considerations of an autonomous wireless sensor and discuss the fabrication and testing of the various components including the energy harvester, the active sensing devices and the power management and sensor interface circuits. A common materials platform, namely, nanowires, enables us to fabricate state-of-the-art components at reduced volume and show chemical sensing within the available energy budget. We demonstrate a photovoltaic mini-module made of silicon nanowire solar cells, each of 0.5 mm2 area, which delivers a power of 260 μW and an open circuit voltage of 2 V at one sun illumination. Using nanowire platforms two sensing applications are presented. Combining functionalised suspended Si nanowires with a novel microfluidic fluid delivery system, fully integrated microfluidic–sensor devices are examined as sensors for streptavidin and pH, whereas, using a microchip modified with Pd nanowires provides a power efficient and fast early hydrogen gas detection method. Finally, an ultra-low power, efficient solar energy harvesting and sensing microsystem augmented with a 6 mAh rechargeable battery allows for less than 20 μW power consumption and 425 h sensor operation even without energy harvesting."
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Background:Owing to demographic trends and increasing health care costs, quick discharge with geriatric rehabilitation at home is advised and recommended for older adults. Telerehabilitation has been identified as a promising tool to support rehabilitation at home. However, there is insufficient knowledge about how to implement a validated home telerehabilitation system in other contexts. One of the major challenges for rehabilitation professionals is transitioning to a blended work process in which human coaching is supplemented via digital care.Objective:The study aimed to gain an in-depth understanding of the factors that influence the implementation of an evidence-based sensor monitoring intervention (SMI) for older adults by analyzing the perspectives of rehabilitation professionals working in 2 different health ecosystems and mapping SMI barriers and facilitators.Methods:We adopted a qualitative study design to conduct 2 focus groups, 1 in person in the Netherlands during winter of 2017 and 1 on the web via Zoom (Zoom Video Communications; owing to the COVID-19 pandemic) in Canada during winter of 2022, to explore rehabilitation providers’ perspectives about implementing SMI. Qualitative data obtained were analyzed using thematic analysis. Participants were a group of rehabilitation professionals in the Netherlands who have previously worked with the SMI and a group of rehabilitation professionals in the province of Manitoba (Canada) who have not previously worked with the SMI but who were introduced to the intervention through a 30-minute web-based presentation before the focus group.Results:The participants expressed different characteristics of the telerehabilitation intervention that contributed to making the intervention successful for at-home rehabilitation: focus on future participation goals, technology support provides the rehabilitation professionals with objective and additional insight into the daily functioning of the older adults at home, SMI can be used as a goal-setting tool, and SMI deepens their contact with older adults. The analysis showed facilitators of and barriers to the implementation of the telerehabilitation intervention. These included personal or client-related, therapist-related, and technology-related aspects.Conclusions:Rehabilitation professionals believed that telerehabilitation could be suitable for monitoring and supporting older adults’ rehabilitation at home. To better guide the implementation of telerehabilitation in the daily practice of rehabilitation professionals, the following steps are needed: ensuring that technology is feasible for communities with limited digital health literacy and cognitive impairments, developing instruction tools and guidelines, and training and coaching of rehabilitation professionals.
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Home rehabilitation after a hip operation can be daunting for the elderly. Lack of motivation to exercise and being insecure in the recovery process are common barriers. Personalized eHealth can help to ensure that the patient exercise efficiently, filling the gap between treatment in the practice with the physical therapist and practice at home.
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In this project we take a look at the laws and regulations surrounding data collection using sensors in assistive technology and the literature on concerns of people about this technology. We also look into the Smart Teddy device and how it operates. An analysis required by the General Data Protection Regulation (GDPR) [5] will reveal the risks in terms of privacy and security in this project and how to mitigate them. https://nl.linkedin.com/in/haniers
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Background:Neuropsychiatric symptoms (NPS) are common in affected individuals and can be challenging for (in)formal caregivers. Therefore, they are also referred to as challenging behaviors (CBs). Sensor technology measuring context and behavior can be assistive to effectively manage CBs in an objective fashion. Sensors can help support healthcare professionals, such as nurses, by enabling remote monitoring and alarming on early-stage behavioral changes associated with CBs. This might/ will improve the quality of life (QoL) for both caregivers and clients living in a nursing homes (NH).In the project “MOnitoring Onbegrepen Gedrag bij Dementie met sensortechnologie” (MOOD-Sense), we aim to develop such a monitoring system. Our research focuses on two questions 1) How to develop and implement a monitoring system within the context of nursing homes with parameters on environment, physiology, and behavior, identify and process relevant precursors of challenging behavior with this monitoring system and 2) gain insight in which behaviors are challenging according to nurses and how they are described. This will be represented in an ontology such that sensor data can be translated into the same conceptual information.Methods:The first research question will be examined with a set of experiments in the field (in NH) with an iterative approach. Insights from previous experiments on usability and added value of sensors will be used to improve successive experiments. During each experiment, multiple participants (clients with dementia and CBs) are monitored with both ambient and wearable sensors. For the second research question a qualitative approach is employed, using focus groups (FG) and consensus methods. These FGs will be held amongst nursing staff who are involved in daily care tasks for people with dementia. Subsequently, consensus methods are used to align behavioral descriptors/labels.Results:early findings will be presented at the symposiumDiscussion:Within this project we expect to find precursors of challenging behavior in a personalized fashion based on nurse’s expert knowledge and sensor data. In order to develop a monitoring system that can be embedded within NH’s, real-time alarming, in-situ behavior recognition and trustworthiness are part of our technological requirements. Just-in-time interventions may then be deployed to prevent behavior escalation or the persistence of undesirable situations.
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Background: Recent technological developments such as wearable sensors and tablets with a mobile internet connection hold promise for providing electronic health home-based programs with remote coaching for patients following total hip arthroplasty. It can be hypothesized that such a home-based rehabilitation program can offer an effective alternative to usual care.Objective: The aim of this study was to determine the effectiveness of a home-based rehabilitation program driven by a tablet app and remote coaching for patients following total hip arthroplasty.Methods: Existing data of two studies were combined, in which patients of a single-arm intervention study were matched with historical controls of an observational study. Patients aged 18-65 years who had undergone total hip arthroplasty as a treatment for primary or secondary osteoarthritis were included. The intervention consisted of a 12-week home-based rehabilitation program with video instructions on a tablet and remote coaching (intervention group). Patients were asked to do strengthening and walking exercises at least 5 days a week. Data of the intervention group were compared with those of patients who received usual care (control group). Effectiveness was measured at four moments (preoperatively, and 4 weeks, 12 weeks, and 6 months postoperatively) by means of functional tests (Timed Up & Go test and the Five Times Sit-to Stand Test) and self-reported questionnaires (Hip disability and Osteoarthritis Outcome Score [HOOS] and Short Form 36 [SF-36]). Each patient of the intervention group was matched with two patients of the control group. Patient characteristics were summarized with descriptive statistics. The 1:2 matching situation was analyzed with a conditional logistic regression. Effect sizes were calculated by Cohen d.Results: Overall, 15 patients of the intervention group were included in this study, and 15 and 12 subjects from the control group were matched to the intervention group, respectively. The intervention group performed functional tests significantly faster at 12 weeks and 6 months postoperatively. The intervention group also scored significantly higher on the subscales "function in sport and recreational activities" and "hip-related quality of life" of HOOS, and on the subscale "physical role limitations" of SF-36 at 12 weeks and 6 months postoperatively. Large effect sizes were found on functional tests at 12 weeks and at 6 months (Cohen d=0.5-1.2), endorsed by effect sizes on the self-reported outcomes.Conclusions: Our results clearly demonstrate larger effects in the intervention group compared to the historical controls. These results imply that a home-based rehabilitation program delivered by means of internet technology after total hip arthroplasty can be more effective than usual care.Keywords: home-based rehabilitation program; internet; osteoarthritis; physiotherapy; rehabilitation; remote coaching; tablet app; total hip arthroplasty; total hip replacement; usual care.
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