Electromagnetic Compatibility of 400 MHz Radio Communications in Hospitals: Safety Management of Wireless Medical Telemetry

Ishida, Kai; Wu, Ifong; Gototh, Kaoru; Matsumoto, Yasushi

doi:10.1007/s10916-020-01629-z

Cited by 9 publications

(4 citation statements)

References 14 publications

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“…13(a)), and an increase in the noise oor owing to the electromagnetic noise generated from the LED lamp is shown (Fig. 13(b)) [11].…”

Section: Cpusmentioning

confidence: 92%

Electromagnetic Compatibility Issues in 400-MHz-Band Wireless Medical Telemetry Systems and Their Management Using Simplified Methods for Safe Operation

Ishida,

Fujii,

Hanada

2023

Preprint

Self Cite

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Wireless medical telemetry systems (WMTSs) are typical radio communication–based medical devices that monitor various biological parameters, such as electrocardiograms and respiration rates. In Japan, the assigned frequency band for WMTSs is 400 MHz. However, the issues accounting for poor reception in WMTS constitute major concerns. For example, the 400 MHz frequency band is also shared by other radio communication systems. Further, the intermodulation (IM) effect significantly reduces reception in WMTS. Additionally, the electromagnetic noises generated from electrical devices, such as light-emitting diode lamps and security cameras, can exceed the 400 MHz frequency band as these devices employ the switched-mode power supply and/or central processing unit and radiate wideband emissions. In this study, we analyzed the effects of the electromagnetic interferences caused by other radio communication systems, the IM effect, and the noises generated from electrical devices on WMTS and discussed their management. Moreover, we proposed and evaluated simplified and facile methods for evaluating the electromagnetic environment.

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“…13(a)), and an increase in the noise oor owing to the electromagnetic noise generated from the LED lamp is shown (Fig. 13(b)) [11].…”

Section: Cpusmentioning

confidence: 92%

Electromagnetic Compatibility Issues in 400-MHz-Band Wireless Medical Telemetry Systems and Their Management Using Simplified Methods for Safe Operation

Ishida,

Fujii,

Hanada

2023

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Furthermore, in order to investigate the safety and electromagnetic compatibility between wireless systems and medical devices, refs. [11][12][13] show the safety and electromagnetic interference within medical devices caused by wireless communication devices. Moreover, and based on international standards and reports, ref.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, ref. [13] experimented with electromagnetic interference coming from noisy lights within wireless medical telemetry and proposes a method to overcome this issue. Ref.…”

Section: Introductionmentioning

confidence: 99%

A Review of Recent Innovations in Remote Health Monitoring

Dalloul,

Miramirkhani,

Kouhalvandi

2023

Micromachines

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The development of remote health monitoring systems has focused on enhancing healthcare services’ efficiency and quality, particularly in chronic disease management and elderly care. These systems employ a range of sensors and wearable devices to track patients’ health status and offer real-time feedback to healthcare providers. This facilitates prompt interventions and reduces hospitalization rates. The aim of this study is to explore the latest developments in the realm of remote health monitoring systems. In this paper, we explore a wide range of domains, spanning antenna designs, small implantable antennas, on-body wearable solutions, and adaptable detection and imaging systems. Our research also delves into the methodological approaches used in monitoring systems, including the analysis of channel characteristics, advancements in wireless capsule endoscopy, and insightful investigations into sensing and imaging techniques. These advancements hold the potential to improve the accuracy and efficiency of monitoring, ultimately contributing to enhanced health outcomes for patients.

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“…Notably, managing the WMT frequency band is necessary to establish a good reception of WMT [2]. For measuring the electromagnetic environment, we can detect poor receptions, electromagnetic interference (EMI) caused by various kinds of electrical devices, and malfunction of radio-receiving equipment to evaluate the electromagnetic environment.…”

Section: Introductionmentioning

confidence: 99%

Novel Estimation Technique for the Carrier-to-Noise Ratio of Wireless Medical Telemetry Using Software-Defined Radio with Machine-Learning

Ishida

2022

Preprint

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In this study, we developed a novel machine-learning model to estimate the carrier-to-noise ratio (CNR) of wireless medical telemetry (WMT) using time-domain waveform data measured by a low-cost software-defined radio. If the CNR can be estimated automatically, the management of the electromagnetic environment of WMT can be easier. Therefore, we proposed a machine-learning method for estimating CNR. According to the performance evaluation results by 5-segment cross-validation on 704 types of measured data, CNR was estimated with 99.5% R-square and 0.844 dB mean absolute error using a gradient boosting regression tree. The gradient boosting decision tree classifiers predicted whether the CNR exceeded 30 dB with 99.5% accuracy. The proposed method is effective for investigating electromagnetic environments in clinical settings.

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Electromagnetic Compatibility of 400 MHz Radio Communications in Hospitals: Safety Management of Wireless Medical Telemetry

Cited by 9 publications

References 14 publications

Electromagnetic Compatibility Issues in 400-MHz-Band Wireless Medical Telemetry Systems and Their Management Using Simplified Methods for Safe Operation

Electromagnetic Compatibility Issues in 400-MHz-Band Wireless Medical Telemetry Systems and Their Management Using Simplified Methods for Safe Operation

A Review of Recent Innovations in Remote Health Monitoring

Novel Estimation Technique for the Carrier-to-Noise Ratio of Wireless Medical Telemetry Using Software-Defined Radio with Machine-Learning

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