Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

Semantics-based platform for context-aware and personalized robot interaction in the internet of robotic things

Robots are moving from well-controlled lab environments to the real world, where an increasing number of environments has been transformed into smart sensorized IoT spaces. Users will expect these robots to adapt to their preferences and needs, and even more so for social robots that engage in personal interactions. In this paper, we present declarative ontological models and a middleware platform for building services that generate interaction tasks for social robots in smart IoT environments. The platform implements a modular, data-driven workflow that allows developers of interaction services to determine the appropriate time, content and style of human-robot interaction tasks by reasoning on semantically enriched loT sensor data. The platform also abstracts the complexities of scheduling, planning and execution of these tasks, and can automatically adjust parameters to the personal profile and current context. We present motivational scenarios in three environments: a smart home, a smart office and a smart nursing home, detail the interfaces and executional paths in our platform and present a proof-of-concept implementation. (C) 2018 Elsevier Inc. All rights reserved

Crossing the digital divide : family caregivers' acceptance of technology

The purpose of this pilot project was to collect data on how electronic technology might be used to assist family members who are caring for a relative with dementia at home. In Phase 1, we conducted five focus groups with 26 caregivers of relatives with dementia to document the specific challenges faced by caregivers and assess their access to, and familiarity with, electronic technology. In Phase 2, a technology-based solution B the Xanboo Smart House Management System B was identified. The System allows monitoring of a residence through placement and control of video cameras and other enabled devices, including sensors that detect motion, the presence of water, or noise. Sensors may be set to provide a caregiver or other interested party with immediate notification by e-mail, pager, or text messaging cell phone. In Phase 3, a household was outfitted with The System and two focus groups comprised of 8 caregivers to relatives with dementia were conducted to evaluate its utility. The report concludes with an annotated bibliography on technology and aging, with special focus on caring for a relative with dementia. Key Findings: Caregivers and the relatives for whom they provide care are in an evolving struggle to maintain continuity of roles, relationships, and lifestyles. Challenges include the safety of the individual with dementia and keeping geographically distant family members aware of their relative s condition. Caregivers used a range of technologies in their day-to-day lives, including low- tech solutions to challenges in caregiving. Caregivers felt strongly that technological solutions were neither appropriate nor useful across all situations, and were cognizant of the inherent trade-off between safety on the one hand and dignity, respect, privacy, and desires for independence and autonomy on the other hand. Caregivers do not aspire to become technology whizzes ; rather, they are interested in easily obtained, affordable, easy to use, solutions to some of the challenges they face. An affordable, easy to use, off the shelf, monitoring system (The System) was identified. Caregivers attitudes regarding The System were generally quite positive. When prompted to identify barriers to using The System, caregivers identified the need for a computer and Internet access, and cost. Conclusions: The results from this pilot project suggest that there are affordable technologies that can assist family members in their efforts to care for relatives with dementia at home, and that these caregivers were amenable to the use of these technologies. Future efforts should evaluate the installation, use, and impact of The System in the homes of family caregivers to relatives with dementia

Usability of Open Data for Smart City Applications – Evaluation of Data, Development of Application and Creation of Visual Dashboards

Today different sources of information on urban areas are becoming openly available at various spatial and temporal resolutions and extents. They are crucial for driving towards “Smart Cities”. Many smart cityrelevant applications, to understand and predict certain phenomena such as mobility, air quality, etc., depend on large amounts of readily available good quality data. Many datasets related to such topics are already publicly available. However, the appropriate use of these datasets must be ensured by checking the quality of data in a systematic way. Under quality of data, one not only evaluate the number of missing or false data points but also determine data characteristics such as resolution, frequency and ease of use, etc. Therefore, the objectives of this paper are to evaluate the open data available in different portals (80 in total) with special consideration to these factors and to evaluate their usability in some of the smart city applications. In this regard, an extensive literature review is carried out. We observed that especially official government data portal often lack these qualities. This could have occurred due to the lack of concrete examples of how cities and citizens can profit from the applications created with the appropriate kind of data. Some civil servants might have experienced some levels of mistrust regarding the abstract ideas of ‘Smart City’ and ‘Open Data’. We therefore illustrate three possible applications, e.g. (a) use of high-resolution low- cost sensor data around Europe (b) GPS trajectories of a large number of taxis monitored inside the city and (c) land-use and accesability data from voluntered geographic information. In this regard, other open source spatial data portals (such as Open Street Map APIs) and open source software such as python and relevant libraries are also utilized. For each application, we elaborate the data characteristics and the detailed methodological steps (e.g., analytics methods) as well as communicate the results with an easy to operate dashboard having strong visualisation and analytical aids (maps, graphs, statistical summary, etc.). The dashboards help to understand the significance of open data and to support decision makers in creatingservices for the citizens with the context of “Smart City”. Finally, we conclude with the limitation and further recommendations to the city officials regarding their role of shaping the future of (smart) cities with the right open data policy

Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities

Research and development work relating to assistive technology 2010-11 (Department of Health) Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197

Workload-aware systems and interfaces for cognitive augmentation

In today's society, our cognition is constantly influenced by information intake, attention switching, and task interruptions. This increases the difficulty of a given task, adding to the existing workload and leading to compromised cognitive performances. The human body expresses the use of cognitive resources through physiological responses when confronted with a plethora of cognitive workload. This temporarily mobilizes additional resources to deal with the workload at the cost of accelerated mental exhaustion. We predict that recent developments in physiological sensing will increasingly create user interfaces that are aware of the user’s cognitive capacities, hence able to intervene when high or low states of cognitive workload are detected. In this thesis, we initially focus on determining opportune moments for cognitive assistance. Subsequently, we investigate suitable feedback modalities in a user-centric design process which are desirable for cognitive assistance. We present design requirements for how cognitive augmentation can be achieved using interfaces that sense cognitive workload. We then investigate different physiological sensing modalities to enable suitable real-time assessments of cognitive workload. We provide empirical evidence that the human brain is sensitive to fluctuations in cognitive resting states, hence making cognitive effort measurable. Firstly, we show that electroencephalography is a reliable modality to assess the mental workload generated during the user interface operation. Secondly, we use eye tracking to evaluate changes in eye movements and pupil dilation to quantify different workload states. The combination of machine learning and physiological sensing resulted in suitable real-time assessments of cognitive workload. The use of physiological sensing enables us to derive when cognitive augmentation is suitable. Based on our inquiries, we present applications that regulate cognitive workload in home and work settings. We deployed an assistive system in a field study to investigate the validity of our derived design requirements. Finding that workload is mitigated, we investigated how cognitive workload can be visualized to the user. We present an implementation of a biofeedback visualization that helps to improve the understanding of brain activity. A final study shows how cognitive workload measurements can be used to predict the efficiency of information intake through reading interfaces. Here, we conclude with use cases and applications which benefit from cognitive augmentation. This thesis investigates how assistive systems can be designed to implicitly sense and utilize cognitive workload for input and output. To do so, we measure cognitive workload in real-time by collecting behavioral and physiological data from users and analyze this data to support users through assistive systems that adapt their interface according to the currently measured workload. Our overall goal is to extend new and existing context-aware applications by the factor cognitive workload. We envision Workload-Aware Systems and Workload-Aware Interfaces as an extension in the context-aware paradigm. To this end, we conducted eight research inquiries during this thesis to investigate how to design and create workload-aware systems. Finally, we present our vision of future workload-aware systems and workload-aware interfaces. Due to the scarce availability of open physiological data sets, reference implementations, and methods, previous context-aware systems were limited in their ability to utilize cognitive workload for user interaction. Together with the collected data sets, we expect this thesis to pave the way for methodical and technical tools that integrate workload-awareness as a factor for context-aware systems.Tagtäglich werden unsere kognitiven Fähigkeiten durch die Verarbeitung von unzähligen Informationen in Anspruch genommen. Dies kann die Schwierigkeit einer Aufgabe durch mehr oder weniger Arbeitslast beeinflussen. Der menschliche Körper drückt die Nutzung kognitiver Ressourcen durch physiologische Reaktionen aus, wenn dieser mit kognitiver Arbeitsbelastung konfrontiert oder überfordert wird. Dadurch werden weitere Ressourcen mobilisiert, um die Arbeitsbelastung vorübergehend zu bewältigen. Wir prognostizieren, dass die derzeitige Entwicklung physiologischer Messverfahren kognitive Leistungsmessungen stets möglich machen wird, um die kognitive Arbeitslast des Nutzers jederzeit zu messen. Diese sind in der Lage, einzugreifen wenn eine zu hohe oder zu niedrige kognitive Belastung erkannt wird. Wir konzentrieren uns zunächst auf die Erkennung passender Momente für kognitive Unterstützung welche sich der gegenwärtigen kognitiven Arbeitslast bewusst sind. Anschließend untersuchen wir in einem nutzerzentrierten Designprozess geeignete Feedbackmechanismen, die zur kognitiven Assistenz beitragen. Wir präsentieren Designanforderungen, welche zeigen wie Schnittstellen eine kognitive Augmentierung durch die Messung kognitiver Arbeitslast erreichen können. Anschließend untersuchen wir verschiedene physiologische Messmodalitäten, welche Bewertungen der kognitiven Arbeitsbelastung in Realzeit ermöglichen. Zunächst validieren wir empirisch, dass das menschliche Gehirn auf kognitive Arbeitslast reagiert. Es zeigt sich, dass die Ableitung der kognitiven Arbeitsbelastung über Elektroenzephalographie eine geeignete Methode ist, um den kognitiven Anspruch neuartiger Assistenzsysteme zu evaluieren. Anschließend verwenden wir Eye-Tracking, um Veränderungen in den Augenbewegungen und dem Durchmesser der Pupille unter verschiedenen Intensitäten kognitiver Arbeitslast zu bewerten. Das Anwenden von maschinellem Lernen führt zu zuverlässigen Echtzeit-Bewertungen kognitiver Arbeitsbelastung. Auf der Grundlage der bisherigen Forschungsarbeiten stellen wir Anwendungen vor, welche die Kognition im häuslichen und beruflichen Umfeld unterstützen. Die physiologischen Messungen stellen fest, wann eine kognitive Augmentierung sich als günstig erweist. In einer Feldstudie setzen wir ein Assistenzsystem ein, um die erhobenen Designanforderungen zur Reduktion kognitiver Arbeitslast zu validieren. Unsere Ergebnisse zeigen, dass die Arbeitsbelastung durch den Einsatz von Assistenzsystemen reduziert wird. Im Anschluss untersuchen wir, wie kognitive Arbeitsbelastung visualisiert werden kann. Wir stellen eine Implementierung einer Biofeedback-Visualisierung vor, die das Nutzerverständnis zum Verlauf und zur Entstehung von kognitiver Arbeitslast unterstützt. Eine abschließende Studie zeigt, wie Messungen kognitiver Arbeitslast zur Vorhersage der aktuellen Leseeffizienz benutzt werden können. Wir schließen hierbei mit einer Reihe von Applikationen ab, welche sich kognitive Arbeitslast als Eingabe zunutze machen. Die vorliegende wissenschaftliche Arbeit befasst sich mit dem Design von Assistenzsystemen, welche die kognitive Arbeitslast der Nutzer implizit erfasst und diese bei der Durchführung alltäglicher Aufgaben unterstützt. Dabei werden physiologische Daten erfasst, um Rückschlüsse in Realzeit auf die derzeitige kognitive Arbeitsbelastung zu erlauben. Anschließend werden diese Daten analysiert, um dem Nutzer strategisch zu assistieren. Das Ziel dieser Arbeit ist die Erweiterung neuartiger und bestehender kontextbewusster Benutzerschnittstellen um den Faktor kognitive Arbeitslast. Daher werden in dieser Arbeit arbeitslastbewusste Systeme und arbeitslastbewusste Benutzerschnittstellen als eine zusätzliche Dimension innerhalb des Paradigmas kontextbewusster Systeme präsentiert. Wir stellen acht Forschungsstudien vor, um die Designanforderungen und die Implementierung von kognitiv arbeitslastbewussten Systemen zu untersuchen. Schließlich stellen wir unsere Vision von zukünftigen kognitiven arbeitslastbewussten Systemen und Benutzerschnittstellen vor. Durch die knappe Verfügbarkeit öffentlich zugänglicher Datensätze, Referenzimplementierungen, und Methoden, waren Kontextbewusste Systeme in der Auswertung kognitiver Arbeitslast bezüglich der Nutzerinteraktion limitiert. Ergänzt durch die in dieser Arbeit gesammelten Datensätze erwarten wir, dass diese Arbeit den Weg für methodische und technische Werkzeuge ebnet, welche kognitive Arbeitslast als Faktor in das Kontextbewusstsein von Computersystemen integriert

Initiatives for a Stronger Community

Although indicators show that the County as a whole is better off than it was a few short years ago, some of Erie County’s residents are not reaping the benefit of this upswing to the same extent as others. Moreover, poor health outcomes also continue to be more likely here than in other counties in New York State. Initiatives for a Stronger Community is the Poloncarz Administration’s health and human services action plan for Erie County government based on the idea that it is unacceptable for a newly revitalized Western New York to leave behind significant portions of our community when we can effect positive change in their lives. As such, the plan outlines specific measures that Erie County government will undertake to improve the quality of life for residents in need. Initiatives for a Stronger Community is grounded in compassion and premised on two fundamental principles: County government represents everyone (not just taxpayers); and Government is an essential partner, and where appropriate, it can and should lead. This plan reflect these key values. They are inclusive, work to address needs and create opportunities, embrace both leadership and partnership, and support the ongoing efforts of others to build a stronger community