IoT-Based Wearable Devices for Patients Suffering from Alzheimer Disease

Abstract

The disorder of Alzheimer’s (AD) is defined as a gradual deterioration of cognitive functions, such as the failure of spatial cognition and short-term memory. Besides difficulties in memory, a person with this disease encounters visual processing difficulties and even awareness and identifying of their beloved ones. Nowadays, recent technologies made this possible to connect everything that exists around us on Earth through the Internet, this is what the Internet of Things (IoT) made possible which can capture and save a massive amount of data that are considered very important and useful information which then can be valuable in training of the various state-of-the-art machine and deep learning algorithms. Assistive mobile health applications and IoT-based wearable devices are helping and supporting the ongoing health screening of a patient with AD. In the early stages of AD, the wearable devices and IoT approach aim to keep AD patients mentally active in all of life’s daily activities, independent from their caregivers or any family member of the patient. These technological solutions have great potential in improving the quality of life of an AD patient as this helps to reduce pressure on healthcare and to minimize the operational cost. The purpose of this study is to explore the State-of-the-Art wearable technologies for people with AD. Significance, challenges, and limitations that arise and what will be the future of these technological solutions and their acceptance. Therefore, this study also provides the challenges and gaps in the current literature review and future directions for other researchers working in the area of developing wearable devices.

The Use of Artificial Intelligence for Smart Decision-Making in Smart Cities: A Moderated Mediated Model of Technology Anxiety and Internal Threats of IoT

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Mathematical Framework for Wearable Devices in the Internet of Things Using Deep Learning

“…In Equation (5), the number of occurrences shows that control measures using wearable IoT devices, which are built using Equation (6), must be put in place if a person has been infected [ 12 ]. …”

“…An automatic monitoring system employing Artificial Intelligence (AI) is introduced as environmental factors change, encouraging cyber–physical systems’ development. Even where a step count strategy is used, it is possible to improve the quality of service for all end users of all wireless IoT devices, by using a defined mathematical approach [ 12 ].…”

Internet-of-Things-based Multi-sensor Structure for Geriatric Healthcare

“…(1) Thus, the workload of medical staff will be increased to take care of elderly patients. (2) The doctor-patient ratio of a hospital is the most used benchmark for hospital manpower allocation. The doctor-patient ratio in Japan or related European countries is about 1:7, and the doctor-patient ratio in Taiwan is 1:13, which is high.…”