Human-centered design of a smart “wireless sensor network environment” enhanced with movement analysis system and indoor positioning qualifications

Paolini, Giacomo; Masotti, Diego; Costanzo, Alessandra; Borelli, Elena; Chiari, Lorenzo; Imbesi, Silvia; Marchi, Michèle; Mincolelli, Giuseppe

doi:10.1109/imws-amp.2017.8247434

Cited by 10 publications

(7 citation statements)

References 7 publications

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“…For the calculation of the absolute reader-tag distance [ 46 ], the maximum value of RSSI (Received Signal Strength Indicator) at the Σ-channel was considered. The adopted formula uses both the value of RSSI at a reference distance and a path-loss model representing the radio channel of the environment under test.…”

Section: Methodsmentioning

confidence: 99%

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HABITAT: An IoT Solution for Independent Elderly

Borelli

Paolini

Antoniazzi

et al. 2019

Sensors

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In this work, a flexible and extensive digital platform for Smart Homes is presented, exploiting the most advanced technologies of the Internet of Things, such as Radio Frequency Identification, wearable electronics, Wireless Sensor Networks, and Artificial Intelligence. Thus, the main novelty of the paper is the system-level description of the platform flexibility allowing the interoperability of different smart devices. This research was developed within the framework of the operative project HABITAT (Home Assistance Based on the Internet of Things for the Autonomy of Everybody), aiming at developing smart devices to support elderly people both in their own houses and in retirement homes, and embedding them in everyday life objects, thus reducing the expenses for healthcare due to the lower need for personal assistance, and providing a better life quality to the elderly users.

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Section: Methodsmentioning

confidence: 99%

“… Possible solution for the installation of two cooperative readers in a typical indoor scenario. Additionally, two possible positions of the tag are represented (blue, on a shoulder; red, on the belt) [ 46 ]. …”

Section: Figurementioning

confidence: 99%

HABITAT: An IoT Solution for Independent Elderly

Borelli

Paolini

Antoniazzi

et al. 2019

Sensors

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“…In addition to wandering pattern detection, movement analysis in smart environments has also assisted detecting early signs of cognitive related disorders. Paolini et al [119] set a smart environment for early detection of AD based on localization and movement analysis. RFID reader technology was used for indoor localization analysis, and a wearable inertial sensor system including accelerometer and gyroscope was used for movement analysis.…”

Section: Computer -Assisted Interpretation Of Brain Scansmentioning

confidence: 99%

Applications of Artificial Intelligence to aid detection of dementia: a narrative review on current capabilities and future directions

Li¹,

Wang²,

Lawler³

et al. 2021

Preprint

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With populations ageing, the number of people with dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases are due to Alzheimer's disease (AD) pathology and there A PREPRINT -APRIL 30, 2021 is a 10-20 year 'pre-clinical' period before significant cognitive decline occurs. We urgently need, cost effective, objective methods to detect AD, and other dementias, at an early stage. Risk factor modification could prevent 40% of cases and drug trials would have greater chances of success if participants are recruited at an earlier stage. Currently, detection of dementia is largely by pen and paper cognitive tests but these are time consuming and insensitive to pre-clinical phases. Specialist brain scans and body fluid biomarkers can detect the earliest stages of dementia but are too invasive or expensive for widespread use. With the advancement of technology, Artificial Intelligence (AI) shows promising results in assisting with detection of early-stage dementia. Existing AI-aided methods and potential future research directions are reviewed and discussed.

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“…The indoor localization system is based on Radio-Frequency IDentification (RFID) and it is composed by two device categories: reader sensors for localization of people and smart object in the environment and recognition tags (Paolini et al, 2017). The recognition tags for artefacts are embedded into their electronic circuits, whilst the tags for people are wearable and should be worn on the upper part of the body to facilitate identification.…”

Section: Indoor Localization System and Inertial Sensormentioning

confidence: 99%

New Domestic Healthcare. Co-designing Assistive Technologies for Autonomous Ageing at Home

et al. 2019

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Ageing is connected with increased chronic psychological and physical disabilities, which are today delayed to older ages than in the past. The constant growth in number of older people in our society creates a larger demand of goods and services related to home care, due to the willingness of the elderly to live at home remaining autonomous as long as possible. Using a Human Centred Design method, this research aims to support ageing in place and to extend independence of older people through appropriate technological strategies for families, reducing both costs and risk factors of caregiving. Quality Function Deployment tool and Co-Design technique are the main approaches that have led the design process, including older people in every decision-making step. The final result is an assistive IoT ecosystem, which provides at the same time a customizable healthcare service to the elderly and a home care management system to their caregivers.

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Human-centered design of a smart “wireless sensor network environment” enhanced with movement analysis system and indoor positioning qualifications

Cited by 10 publications

References 7 publications

HABITAT: An IoT Solution for Independent Elderly

HABITAT: An IoT Solution for Independent Elderly

Applications of Artificial Intelligence to aid detection of dementia: a narrative review on current capabilities and future directions

New Domestic Healthcare. Co-designing Assistive Technologies for Autonomous Ageing at Home

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