A Smart Sensor in the IoMT for Stress Level Detection

Rachakonda, Laavanya; Sundaravadivel, Prabha; Mohanty, Saraju P.; Kougianos, Elias; Ganapathiraju, Madhavi K.

doi:10.1109/ises.2018.00039

Cited by 29 publications

(11 citation statements)

References 26 publications

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“…In order to improve the acquisition of patients' physiological parameters, a kind of graphene wearable medical sensor with high sensitivity and linearity is proposed in [16]. In [17], a new type of sensor is used, which can real-time monitor people's pressure level through their body temperature, movement speed and body perspiration, so as to reduce the risk of human health. In recent years, the optimization of WSN is also the focus of many researchers.…”

Section: ) Wireless Sensor Network (Wsn)mentioning

confidence: 99%

Edge-Cloud Computing and Artificial Intelligence in Internet of Medical Things: Architecture, Technology and Application

et al. 2020

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With the booming development of medical informatization and the ubiquitous connections in the fifth generation mobile communication technology (5G) era, the heterogeneity and explosive growth of medical data have brought huge challenges to data access, security and privacy, as well as information processing in Internet of Medical Things (IoMT). This article provides a comprehensive review of how to realize the timely processing and analysis of medical big data and the sinking of high-quality medical resources under the constraints of the existing medical environment and medical-related equipment. We mainly focus on the advantages brought by the cloud computing, edge computing and artificial intelligence technologies to the IoMT. We also explore how to rationalize the use of medical resources and the security and privacy of medical data, so that high-quality medical services can be provided to patients. Finally, we discuss the current challenges and possible future research directions in the edge-cloud computing and artificial intelligence related IoMT. INDEX TERMS Internet of medical things (IoMT), deep learning, edge of computing, computation offloading.

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Section: ) Wireless Sensor Network (Wsn)mentioning

confidence: 99%

Edge-Cloud Computing and Artificial Intelligence in Internet of Medical Things: Architecture, Technology and Application

et al. 2020

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“…In [59], an IoMT smart sensor for stress-level detection is presented. This is a novel stress-detection system called iStress.…”

Section: Iomt Bms For Brain Diseasesmentioning

confidence: 99%

IoMT-based biomedical measurement systems for healthcare monitoring: a review

Imran

Balestrieri²,

Lamonaca

2021

ACTA IMEKO

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<p class="Abstract"><span lang="EN-US">Biomedical measurement systems (BMS) have provided new solutions for healthcare monitoring and the diagnosis of various chronic diseases. With a growing demand for BMS in the field of medical applications, researchers are focusing on advancing these systems, including Internet of Medical Things (IoMT)-based BMS, with the aim of improving bioprocesses, healthcare systems and technologies for biomedical equipment. This paper presents an overview of recent activities towards the development of IoMT-based BMS for various healthcare applications. Different methods and approaches used in the development of these systems are presented and discussed, taking into account some metrological aspects related to the requirement for accuracy, reliability and calibration. The presented IoMT-based BMS are applied to healthcare applications concerning, in particular, heart, brain and blood sugar diseases as well as internal body sound and blood pressure measurements. Finally, the paper provides a discussion about the shortcomings and challenges that need to be addressed along with some possible directions for future research activities.</span></p>

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“…A possible representation of IoMT device iStress using a PFSM presents a possible representation of the stress-detection device named iStress proposed in ref. [62] using a PFSM: The operation of the device was considered as the continuous iteration of the diagram shown. In the start node, it was very likely (p = 0.90) that the data from the three primary sensors were read, namely the accelerometer, the humidity, and the temperature sensors.…”

Section: Archetypes Of Data-aware Smart Contracts and Pfsm Compositionmentioning

confidence: 99%

Blockchain and IoMT against Physical Abuse: Bullying in Schools as a Case Study

Ersotelos

Bottarelli

Al-Khateeb

et al. 2020

JSAN

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By law, schools are required to protect the well-being of students against problems such as on-campus bullying and physical abuse. In the UK, a report by the Office for Education (OfE) showed 17% of young people had been bullied during 2017–2018. This problem continues to prevail with consequences including depression, anxiety, suicidal thoughts, and eating disorders. Additionally, recent evidence suggests this type of victimisation could intensify existing health complications. This study investigates the opportunities provided by Internet of Medical Things (IoMT) data towards next-generation safeguarding. A new model is developed based on blockchain technology to enable real-time intervention triggered by IoMT data that can be used to detect stressful events, e.g., when bullying takes place. The model utilises private permissioned blockchain to manage IoMT data to achieve quicker and better decision-making while revolutionising aspects related to compliance, double-entry, confidentiality, and privacy. The feasibility of the model and the interaction between the sensors and the blockchain was simulated. To facilitate a close approximation of an actual IoMT environment, we clustered and decomposed existing medical sensors to their attributes, including their function, for a variety of scenarios. Then, we demonstrated the performance and capabilities of the emulator under different loads of sensor-generated data. We argue to the suitability of this emulator for schools and medical centres to conduct feasibility studies to address sensor data with disruptive data processing and management technologies.

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A Smart Sensor in the IoMT for Stress Level Detection

Cited by 29 publications

References 26 publications

Edge-Cloud Computing and Artificial Intelligence in Internet of Medical Things: Architecture, Technology and Application

Edge-Cloud Computing and Artificial Intelligence in Internet of Medical Things: Architecture, Technology and Application

IoMT-based biomedical measurement systems for healthcare monitoring: a review

Blockchain and IoMT against Physical Abuse: Bullying in Schools as a Case Study

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