Technological Approach for Early and Unobtrusive Detection of Possible Health Changes Toward More Effective Treatment

Kaddachi, Firas; Aloulou, Hamdi; Abdulrazak, Bessam; Fraisse, Philippe; Mokhtari, Mounir

doi:10.1007/978-3-319-94523-1_5

Cited by 6 publications

(13 citation statements)

References 25 publications

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“…ADL monitoring systems can be arranged into three categories ( Table 4 ): Environmental only ( n = 36): systems using only environmentally based technology, such as motion sensors and video cameras [ 10 , 19 , 20 , 23 , 24 , 25 , 26 , 28 , 37 , 40 , 41 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 ]. Wearable only ( n = 2): systems using only body-worn technology, such as accelerometers [ 39 , 51 ].…”

Section: Resultsmentioning

confidence: 99%

“…Within each system category, varying combinations of technology types are used to create the separate systems. Where there are multiple references for each sensor combination, for example the combination of door + motion [ 41 , 43 , 45 , 48 , 61 , 64 ], the separate systems have been used to recognise different ADL.…”

Section: Resultsmentioning

confidence: 99%

“…Figure 4 visualizes the environment-only category due to the large variation of technology combinations within this category. Most of the environment-only category systems used either one type of technology ( n = 10) [ 10 , 23 , 24 , 51 , 53 , 54 , 56 , 57 , 58 ] or a combination of two types of technology ( n = 10) [ 37 , 41 , 43 , 45 , 48 , 52 , 61 , 64 , 66 , 69 ]. Of the 24 systems using a combination of two or more types of technology, only one did not include motion sensors [ 52 ] and only two systems used a combination of seven technology types [ 60 , 68 ].…”

Section: Resultsmentioning

confidence: 99%

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Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults

Camp

Lewis

Hunter

et al. 2020

IJERPH

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The use of technology has been suggested as a means of allowing continued autonomous living for older adults, while reducing the burden on caregivers and aiding decision-making relating to healthcare. However, more clarity is needed relating to the Activities of Daily Living (ADL) recognised, and the types of technology included within current monitoring approaches. This review aims to identify these differences and highlight the current gaps in these systems. A scoping review was conducted in accordance with PRISMA-ScR, drawing on PubMed, Scopus, and Google Scholar. Articles and commercially available systems were selected if they focused on ADL recognition of older adults within their home environment. Thirty-nine ADL recognition systems were identified, nine of which were commercially available. One system incorporated environmental and wearable technology, two used only wearable technology, and 34 used only environmental technologies. Overall, 14 ADL were identified but there was variation in the specific ADL recognised by each system. Although the use of technology to monitor ADL of older adults is becoming more prevalent, there is a large variation in the ADL recognised, how ADL are defined, and the types of technology used within monitoring systems. Key stakeholders, such as older adults and healthcare workers, should be consulted in future work to ensure that future developments are functional and useable.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults

Camp

Lewis

Hunter

et al. 2020

IJERPH

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“…Later, we have integrated the "ChangeTracker" service to identify possible participants' behavior changes. Different statistical, probabilistic, and machine-learning algorithms have been tested [37]. These change detection techniques do not provide the same performance in terms of change detection precision.…”

Section: Technology Validationmentioning

confidence: 99%

Pilot Site Deployment of an IoT Solution for Older Adults’ Early Behavior Change Detection

Aloulou

Mokhtari

Abdulrazak

2020

Sensors

Self Cite

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The world demography is continuously changing. During the last decade, we noticed a regular variation in the world demography leading to a nearly balanced society share between the young and aging population. This increasing older adult population is facing many problems. In fact, the transition to the aging period is associated with physical, psychological, cognitive, and societal changes. Negative behavior changes are considered as indicators of older adults’ frailty. This is why it is important to detect such behavior changes early in order to prevent isolation, sedentary lifestyle, and even diseases, and therefore delay the frailty period. This paper exhibits a proof-of-concept pilot site deployment of an Internet of Thing (IoT) solution for the continuous monitoring and detection of older adults’ behavior changes. The objective is to help geriatricians detect sedentary lifestyle and health-related problems at an early stage.

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“…Moreover, our approach allows complex applications to be built using pre-existing deployments, instead of trying to build and deploy a whole new system that spans various tasks (such as, in the case of digital health, environmental and patient-specific factors). This is encouraging for digital health IoT applications where multimodal sensing is of increasing significance [19], [20], but also for IoT applications in general as they share spaces in smart cities, homes, agricultural and manufacturing plants, etc.…”

Section: Discussionmentioning

confidence: 97%

An Ontological Framework for Opportunistic Composition of IoT Systems

Nundloll

Elkhatib

Elhabbash

et al. 2020

2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT)

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As the number of connected devices rapidly increases, largely thanks to uptake of IoT technologies, there is significant stimulus to enable opportunistic interactions between different systems that encounter each other at run time. However, this is complicated by diversity in IoT technologies and implementation details that are not known in advance. To achieve such unplanned interactions, we use the concept of a holon to represent a system's services and requirements at a high level. A holon is a self-describing system that appears as a whole when viewed from above whilst potentially comprising multiple subsystems when viewed from below. In order to realise this world view and facilitate opportunistic system interactions, we propose the idea of using ontologies to define and program a holon. Ontologies offer the ability to classify the concepts of a domain, and use this formalised knowledge to infer new knowledge through reasoning. In this paper, we design a holon ontology and associated code generation tools. We also explore a case study of how programming holons using this approach can aid an IoT system to self-describe and reason about other systems it encounters. As such, developers can develop system composition logic at a high-level without any preconceived notions about low-level implementation details.

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Technological Approach for Early and Unobtrusive Detection of Possible Health Changes Toward More Effective Treatment

Cited by 6 publications

References 25 publications

Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults

Technology Used to Recognize Activities of Daily Living in Community-Dwelling Older Adults

Pilot Site Deployment of an IoT Solution for Older Adults’ Early Behavior Change Detection

An Ontological Framework for Opportunistic Composition of IoT Systems

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