2021
DOI: 10.1109/jsen.2020.2977352
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A Sensor-Based Data Analytics for Patient Monitoring in Connected Healthcare Applications

Abstract: Nowadays, keeping a strong and good health is one of the main concern of the general public or governments. The Internet of Things (IoT) has been emerged as an efficient solution to build smart healthcare systems deployed either at hospitals or in-home. Such networks rely on biomedical sensors which are used in electronics-based medical equipment to remotely collect vital signs of patients (pressure, temperature, hart rate, oxygen saturation etc.). Generally, these biosensors are implemented on or inside the p… Show more

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Cited by 52 publications
(20 citation statements)
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“…There is a lack of financial resources and greater multidisciplinarity and contacts between health governance and technological research centers. [77,78,[139][140][141][142][143][144][145][146][147] 4…”
Section: Discussion and Future Challengesmentioning
confidence: 99%
See 1 more Smart Citation
“…There is a lack of financial resources and greater multidisciplinarity and contacts between health governance and technological research centers. [77,78,[139][140][141][142][143][144][145][146][147] 4…”
Section: Discussion and Future Challengesmentioning
confidence: 99%
“…2021, 21, x FOR PEER REVIEW 16 of 39IoT Application Solutions[77,78,[139][140][141][142][143][144][145][146][147]:• Intelligent systems, sensors, IoT, technologically advanced medical devices, communications networks, etc., represent a significant improvement in the synergies between medical centers in vulnerable countries and advanced healthcare centers in developed countries.•In recent months, it has been proven that technological systems and IoT applications are of great importance in the research, application, and prevention of diseases and pandemics worldwide, when it comes to vaccine and drug manufacturing, logistics, population vaccination planning and management, data management, and patient monitoring at home, among other efforts.•Traffic accident prevention and control systems have an ally in technological systems and advanced IoT applications, for example, in user applications that inform and warn of vehicle congestion in cities and highways, accident warnings, alarm systems in adverse weather situations, among others.•Development of efficient and high-quality vaccines, where sensor applications, IoT, and intelligent systems play a great role. Technology, in all its fields, has a fundamental mission for the effective development and distribution of vaccines to the entire population, with applications to data management, including patient data, vaccination control, health and safety, among others.•In the area of air and soil pollution and the detection of chemical elements in the environment, there are multiple applications of sensors and intelligent systems that detect, transmit, manage, and prevent such problems.…”
mentioning
confidence: 99%
“…AI algorithms promise to be extremely important in assisting remote patient monitoring applications. Harb et al [9] proposed a patient monitoring scheme that utilizes big data analytics to achieve three features: emergency detection, adapting sensing frequency, and real-time patient health prediction. First, they utilized a periodic patient monitoring model and an early warning score to determine the patient's criticality level.…”
Section: Remote Patient Monitoringmentioning
confidence: 99%
“…The recent COVID-19 pandemic and the associated transition of patient care outside the hospital have boosted the development of systems for the remote monitoring of patient vitals signs [1][2][3], a task that has also been favored by the advancement of wearable technologies [4][5][6][7][8][9] and the Internet of Things (IoT). These two technologies have contributed to the widespread adoption of smart healthcare solutions (soft transducer), deployed either at hospitals or at home [10,11]. In fact, on the one hand, the integration of IoT with wearable devices enables the doctor to remotely monitor the patients' health.…”
Section: Introductionmentioning
confidence: 99%
“…Data Set Creation: First, the reference data set for the anomaly detection was imported from [41]. The 50 subjects included are 80% men (40) and 20% women (10), with an age range ranging from 26 to 35 years old. Oxygen saturation, heart rate and identification are indicated for each user.…”
mentioning
confidence: 99%