Introducing a low-cost Ambient Monitoring System for Activity Recognition

Chiriac, Sebastian; Saurer, Bruno Rosales; Stummer, Gabi; Kunze, Christophe

doi:10.4108/icst.pervasivehealth.2011.246003

Cited by 8 publications

(3 citation statements)

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“…Within smart homes, various technologies can be employed to monitor fuels and sensors for automating daily tasks [87] plus safety review policies [88] for systems. The CONFIDENCE system [89,90] uses radio tags for location and speed of travel, eCAALYX [12] creates easily understood TV User Interfaces (UIs) for the elderly, ROSETTA [91] accesses video coverage and accelerometers, and CODAMOTION [12] utilises infra-red.…”

Section: General Health Monitoringmentioning

confidence: 99%

A Review and Classification of Assisted Living Systems

2018

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Europe's social agenda for the "active elderly" is based upon a series of programs that provide a flexible infrastructure for their lives so that they are motivated, engaged in lifelong learning, and contributing to society. Economically speaking, Europe must engage in active aging research in order to avoid unsustainable health costs, and ambient assisted living (AAL) systems provide a platform for the elderly to remain living independently. This paper reviews research conducted within the area of AAL, and offers a taxonomy within which such systems may be classified. This classification distinguishes itself from others in that it categorises AAL systems in a top-down fashion, with the most important categories placed immediately to the left. In this paper, each section is explored further, and AAL systems are the focus. Entire AAL systems still cannot be fully evaluated, but their constituent technical parts can be assessed. The activities of daily living (ADLs) component was given further priority due to its potential for system evaluation, based on its ability to recognise ADLs with reasonable accuracy.Information 2018, 9, 182 2 of 24 ensure that future system features include the minimum requirements necessary for AAL research and commercial usage, thus ensuring that the elderly and their families have systems capable of meeting their current and future ADL needs. Previous reviews have taken different approaches, yet all failed to provide a framework within which all AAL systems could be classified according to their primary function [5,6]. Some applied specific guidelines to predominantly single-use systems, compared platform performance, or personalised healthcare systems. The evolution of AAL technology [7] has taken us through three generations, from wearable devices that respond to an emergency, to automatic response home sensors, to a third generation combining less-intrusive monitoring with preventive functionalities. Another review approach of surveying ambient environment services [8] under event-, context-, or device-aware services was categorised in terms of a service-oriented, user-centered, and event-aware monitoring service. This review technique compared various ambient services of response time, success rate, low/high-level failures, power consumption, and service reliability/adaption, yet offered no classification. A comprehensive literature review [9] on platforms and systems [10] provided no taxonomy for researchers, and excluded ambient intelligence (AmI) research that is pivotal within robotics and wearable computing. A recent review paper [11] described AAL as the culmination of the following five technologies: sensors, context awareness, machine learning, and artificial intelligence, announcing the importance of device interoperability, yet offering no template for achieving this goal. AALIANCE [12] proffered a roadmap for AAL system standardisation and a possible future evolutionary structure for systems, yet this aspirational template lacks the necessary structure to accommodate curr...

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Section: General Health Monitoringmentioning

confidence: 99%

A Review and Classification of Assisted Living Systems

2018

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“…Human-computer interaction (HCI) and ambient intelligence research have contributed substantially to enabling data collection at this high level of disaggregation through the development of advanced sensing technology and disaggregation algorithms. The key motivations behind these developments include developing and testing eco-feedback technology (Sundramoorthy et al 2011;Froehlich et al 2011a), improvement of health-care systems through activity sensing (Martín et al 2013;Chiriac et al 2011;Kushiro et al 2009), and smart homes (Ding et al 2011;Rodgers et al 2010).…”

Section: Goods Supplied Through Public Mainsmentioning

confidence: 99%

Perspectives on quantifying and influencing household metabolism

Harder

Dombi

Peters

2016

Journal of Environmental Planning and Management

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Household metabolism is a concept that is concerned with the analysis of stocks and flows of energy, matter, and information at the household scale. This paper starts by providing a brief overview of the concept of household metabolism. Rather than attempting an in-depth review and analysis of this field, the article subsequently maps the contributions and perspectives of a broad variety of research traditions that have an interface with the concept of household metabolism. Next, this paper highlights a number of controversial issues connected to household metabolism, and studies at the interface of household metabolism. Finally, this paper argues that the concept of household metabolism can provide valuable help in diagnosing misalignments between enacted system dynamics and expressed societal goals, and can help to design research that facilitates their alignment.

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“…We clustered the nursing diagnosis in four main areas: health, mobility, cognition and social interaction (TABLE I). As a next step, we matched the specified sensors with the selected home automation system presented in [10]. The matched sensors with their location are the basis for the deployment of sensors in the home environment.…”

Section: Background and Related Workmentioning

confidence: 99%

Towards combining validation concepts for short and long-term ambient health monitoring

Chiriac¹,

Röll²,

Parada³

et al. 2012

Proceedings of the 6th International Conference on Pervasive Computing Technologies for Healthcare

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Existing health monitoring systems detect either acute health issues or long-term deterioration of health. This paper presents a validation concept for sensors and algorithms that detect emergencies and monitor long term health development. The reviewed ambient monitoring system combines a short term rule based and a long term scoring approach that are validated in a study with 100 households. The resulting dataset is complemented by diaries and participation of care givers. Care givers monitor the health state through questionnaires and by rating generated alerts and warnings. The validation benefits from this multilateral approach and points towards a further integration of long and short-term monitoring.

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Introducing a low-cost Ambient Monitoring System for Activity Recognition

Cited by 8 publications

References 0 publications

A Review and Classification of Assisted Living Systems

A Review and Classification of Assisted Living Systems

Perspectives on quantifying and influencing household metabolism

Towards combining validation concepts for short and long-term ambient health monitoring

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