A novel cluster head selection technique for edge-computing based IoMT systems

Han, Tao; Li-juan, Zhang; Pirbhulal, Sandeep; Wu, Wanqing; Albuquerque, Victor Hugo C. de

doi:10.1016/j.comnet.2019.04.021

Cited by 88 publications

(38 citation statements)

References 23 publications

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“…Although some studies were made on the medical system platform and acquisition system (Han et al, 2019;Pirbhulal et al, 2019;Sun et al, 2020), it helped less with the improvement of ABR morphology. Towards effectively solving the problem on the quality of ABR signals, the RSR method was proposed to improve the morphology and reliability of current ABR FIGURE 8 | The correlation coefficients between the ABR waveform with varying averaging time and the final ABR waveform (averaged for 2,000 times) under the stimulation conditions of 20 Hz, 60 dB (A) and 20 Hz, 55 dB (B).…”

Section: Discussionmentioning

confidence: 99%

The Effects of Random Stimulation Rate on Measurements of Auditory Brainstem Response

Wang

Zhu

Samuel

et al. 2020

Front. Hum. Neurosci.

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Electroencephalography (EEG) signal is an electrophysiological recording from electrodes placed on the scalp to reflect the electrical activities of the brain. Auditory brainstem response (ABR) is one type of EEG signals in response to an auditory stimulus, and it has been widely used to evaluate the potential disorders of the auditory function within the brain. Currently, the ABR measurements in the clinic usually adopt a fixed stimulation rate (FSR) technique in which the late evoked response could contaminate the ABR signals and deteriorate the waveform differentiation after averaging, thus compromising the overall auditory function assessment task. To resolve this issue, this study proposed a random stimulation rate (RSR) method by integrating a random interval between two adjacent stimuli. The results showed that the proposed RSR method was consistently repeatable and reliable in multiple trials of repeated measurements, and there was a large amplitude of successive late evoked response that would contaminate the ABR signals for conventional FSR methods. The ABR waveforms of the RSR method showed better wave I-V morphology across different stimulation rates and stimulus levels, and the improved ABR morphology played an important role in early diagnoses of auditory pathway abnormities. The correlation coefficients as functions of averaging time showed that the ABR waveform of the RSR method stabilizes significantly faster, and therefore, it could be used to speed up current ABR measurements with more reliable testing results. The study suggests that the proposed method would potentially aid the adequate reconstruction of ABR signals towards a more effective means of hearing loss screening, brain function diagnoses, and potential brain-computer interface.

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Section: Discussionmentioning

confidence: 99%

The Effects of Random Stimulation Rate on Measurements of Auditory Brainstem Response

Wang

Zhu

Samuel

et al. 2020

Front. Hum. Neurosci.

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“…Authors in [55] developed a clustering model for medical applications (CMMA) to increase the reliability and lifetime of communication and reduce the energy consumption of edge-based IoMT systems. The remaining energy, delay, distance from the base station, capacity, and queue of the IoMT devices were considered when choosing a cluster head.…”

Section: Edge-and Cloud-based Smart Health Carementioning

confidence: 99%

A Comprehensive Survey of the Internet of Things (IoT) and AI-Based Smart Healthcare

2021

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“…In addition, they found that the GPS location uncertainty reported through a smartphone generally depends on the surroundings or the measurement environment. Han et al (2019) proposed a new clustering model for medical applications (CMMA) to select the cluster head and provide energy-efficient communication in the telemedicine scenario. Specifically, the system chooses the device with the higher remaining energy level and closer to the base station.…”

Section: State Of the Art On Sensors And Technologies For Detecting Pmentioning

confidence: 99%

An overview of technologies and devices against COVID-19 pandemic diffusion: virus detection and monitoring solutions

Fazio

Sponziello

Cafagna

et al. 2021

International Journal on Smart Sensing and Intelligent Systems

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The year 2020 will remain in the history for the diffusion of the COVID-19 virus, originating a pandemic on a world scale with over a million deaths. From the onset of the pandemic, the scientific community has made numerous efforts to design systems to detect the infected subjects in ever-faster times, allowing both to intervene on them, to avoid dangerous complications, and to contain the pandemic spreading. In this paper, we present an overview of different innovative technologies and devices fielded against the SARS-CoV-2 virus. The various technologies applicable to the rapid and reliable detection of the COVID-19 virus have been explored. Specifically, several magnetic, electrochemical, and plasmonic biosensors have been proposed in the scientific literature, as an alternative to nucleic acid-based real-time reverse transcription Polymerase Chain Reaction (PCR) (RT-qPCR) assays, overcoming the limitations featuring this typology of tests (the need for expensive instruments and reagents, as well as of specialized staff, and their reliability). Furthermore, we investigated the IoT solutions and devices, reported on the market and in the scientific literature, to contain the pandemic spreading, by avoiding the contagion, acquiring the parameters of suspected users, and monitoring them during the quarantine period.

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A novel cluster head selection technique for edge-computing based IoMT systems

Cited by 88 publications

References 23 publications

The Effects of Random Stimulation Rate on Measurements of Auditory Brainstem Response

The Effects of Random Stimulation Rate on Measurements of Auditory Brainstem Response

A Comprehensive Survey of the Internet of Things (IoT) and AI-Based Smart Healthcare

An overview of technologies and devices against COVID-19 pandemic diffusion: virus detection and monitoring solutions

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