Location System and Monitoring of Vital Signs in Older Adults and People with Alzheimer

Jimenez, Deisy; Cordova, Patricio; Gordón, Carlos

doi:10.1109/icedeg.2018.8372345

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…In the context of the management of AD, the IoMT enables real-time monitoring, data analysis, and remote interventions. There are notable contributions from the following sources among the 46 articles included in this survey: [13], [55], [56], [57], [58], [59], [60], and [61], which specifically focus on the use and advancement of IoMT technology in the context of AD care. The Table 9 summarises major points from these publications.…”

Section: ) Internet Of Medical Thingsmentioning

confidence: 99%

“…In [60], Jiménez et al, suggested a theoretical framework for keeping an eye on people with dementia and Alzheimer's in their homes. By using sensors to collect contextual data, the framework allows for flexible and personalised moni- The system has technical limits and cannot guarantee the complete normal routine [56] (2021) Develop a cost-effective and user-friendly smart wearable device integrated with a software application for Alzheimer's patients.…”

Section: ) Internet Of Medical Thingsmentioning

confidence: 99%

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ICT-Based Solutions for Alzheimer’s Disease Care: A Systematic Review

Ali,

Turetta,

Demrozi

et al. 2024

IEEE Access

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In recent years, there has been a growing recognition of the significant challenges posed by Alzheimer's Disease (AD) and the need for innovative solutions to improve the quality of life for affected individuals. As AD prevalence continues to rise, technological advancements offer promising opportunities to address the multifaceted needs of patients and caregivers. This survey paper thoroughly investigates technological innovations in AD care, offering valuable insights into cutting-edge approaches that have the potential to positively impact the lives of affected individuals. By providing a holistic view of available assistive solutions, we review 2459 papers and select 46 relevant studies published between 2015 and 2023, specifically focusing on healthcare technologies and solutions, and utilized sensing methods. The former will include Telemedicine, E-Health, Smart Environment, Internet of Things (IoT), Ambient Assisted Living (AAL), Internet of Medical Things (IoMT), and Personalized Assistive Solutions (PAS), while the latter encompasses Wearable/Environmental, Radio/Audio, Video/Image, and Digital Platforms. Our comparative assessment of recent survey papers reveals the unique contribution of this study, as it comprehensively examines the intersection of multiple parameters. By summarizing insights from these studies, we identify gaps and recommend future directions for advancements in AD care.INDEX TERMS Ambient Assisted Living (AAL), Alzheimer's disease (AD), Internet of Medical Things (IoMT), Internet of Things (IoT), Systematic Literature review, Personalized Assistive Solutions.

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Section: ) Internet Of Medical Thingsmentioning

confidence: 99%

Section: ) Internet Of Medical Thingsmentioning

confidence: 99%

ICT-Based Solutions for Alzheimer’s Disease Care: A Systematic Review

Ali,

Turetta,

Demrozi

et al. 2024

IEEE Access

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“…Accordingly, patients diagnosed with these diseases face problems in daily living activities; for example, they lose their sense of location, which may lead to death in some environments. Consequently, these patients need constant assistance and special care [4]. In support of these patients, a wearable wireless sensor network (WSN) can locate their position by way of indoor localization by a system that can be used to track or determine the location of devices or objects in indoor environments.…”

Section: Introductionmentioning

confidence: 99%

Neural Network-Based Alzheimer’s Patient Localization for Wireless Sensor Network in an Indoor Environment

et al. 2020

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The number of older adults with Alzheimer's disease is increasing every year. The associated memory problems cause many difficulties for Alzheimer's patients and their caretakers; patients may even become lost in familiar surroundings. In this paper, a proposed localization system based on a wireless sensor network (WSN) and backpropagation based artificial neural network (BP-ANN) was practically implemented to detect and determine the position of an Alzheimer's patient in an indoor environment. The proposed system consisted of four ZigBee-based XBee S2C anchor nodes and one mobile node carried by the Alzheimer's patient. The received signal strength indicator (RSSI) of the anchor nodes was collected by the mobile node using a laptop supported by X-CTU software. The obtained RSSI values were used as input for training, testing, and validation processes of the BP-ANN, while two-dimension (2D) locations (x and y) were used as the output of the ANN. The results showed that the obtained mean localization errors were 0.964 and 0.921m for validation and testing phases, respectively, after applying the ANN. Based on a comparison with state-ofthe-art technology, we deduced that the proposed ANN method outperformed other techniques in previous studies in terms of mean localization error.

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