Electromagnetic Interference Immunity Testing of Medical Equipment to Second- and Third-Generation Mobile Phones

Tang, C.K.; Chan, Kwok Hung; Fung, L.C.; Leung, S.W.

doi:10.1109/temc.2009.2021524

Cited by 43 publications

(18 citation statements)

References 9 publications

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“…In view of the advances of electromagnetic compatibility (EMC) technologies, some hospitals in Singapore and the U.K. relax the EMI restriction recommended in the EN60601-1-2 standard, and mobile phones are permitted to use in some areas of hospitals [11]. Tang and Chang in [12] discuss the EMI test in view of the recently developed EMC of medical equipment, and the test takes into account the EMI of GSM900, PCS1800, and 3G mobile communication systems. The testing results show that ECG monitors, radiographic systems, audio evoked potential systems, and ultrasonic fetal heart detectors are sensitive to EMI [12].…”

Section: Related Work Of Emi On Medical Sensorsmentioning

confidence: 99%

Internet of Vehicles for E-Health Applications: A Potential Game for Optimal Network Capacity

Lin

Tang

Labeau

et al. 2017

IEEE Systems Journal

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Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario rests at the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In view of EMI on medical sensors, we propose a power control algorithm under a noncooperative game theoretic framework to schedule data transmission. Our objective is to ensure that the noncooperative game of power control can achieve a network-level objective-the optimal network capacity, although the wireless users are selfish and only interested in optimizing their own channel capacity. To obtain this objective, we show that our proposed noncooperative game is a potential game and propose the best-response-dynamics algorithm which can ensure that the game strategy of each user is induced to the optimal solution to the problem of network-level optimal capacity. Numerical results illustrate that the proposed algorithm can achieve an enhancement of 8% of network performance than the existing algorithm against the variations of mobile hospital environments.Index Terms-E-health, game theory, mobile hospital, Nash equilibrium, power control. 1932-8184

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Section: Related Work Of Emi On Medical Sensorsmentioning

confidence: 99%

Internet of Vehicles for E-Health Applications: A Potential Game for Optimal Network Capacity

Lin

Tang

Labeau

et al. 2017

IEEE Systems Journal

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“…Bluetooth modules, GPRS or the internet are often used in the wireless transmission, and there exists different protocols among various devices, such as WAP and Wi-Fi [64]. It has been said that there are many similarities between mobile phone usage and the internet [65] so, with mobile phone as the control tool in telemedicine systems, new networks could be established for mobile phone communication, for example, 3G mobile communication systems, which also have lower electric radiation effect [66]. The evolution of current 3G wireless communication and mobile network technologies will be the main driving force for the future developments in telemedicine [7,67].…”

Section: Interaction Between Mobile Phones and Wireless Networkmentioning

confidence: 99%

Mobile phone-enabled control of medical care and handicapped assistance

Liu

2011

Expert Review of Medical Devices

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Mobile phones are now playing an ever more crucial role in people's daily lives. They are serving not only as a way of talking and delivering messages, but also for exchanging various information. Nevertheless, the functional limit of the phone is still far from being reached. Among the many promising applications, using mobile phones as an actuating element to control data or devices is useful in quite a few emerging medical care and handicapped assistance settings owing to its wireless communication feature. In this article, selected progresses of mobile phone-enabled controlling have been summarized, with more focus on evaluating its emerging roles in medical care. Several typical applications in the area are illustrated and some potential technical challenges and key issues worthy of pursuit are outlined. The intent of the article is to provide an elementary knowledge for people with different backgrounds, such as electrical or biomedical engineers, as well as people who are working on interdisciplinary areas. It is expected that medical care at any time and anywhere will be possible via the actuation platform provided by the mobile phone and mobile medicine will be pushed forward to a new height in the coming years.

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“…Wireless devices can cause electromagnetic interference (EMI) with critical-care electronic medical devices (EMDs) [4]- [11]. An EMD functions correctly provided that the electric field strength is less than the device's immunity level field strength.…”

Section: Introductionmentioning

confidence: 99%

“…In study [9], a Pulse Oximeter was almost perfectly immune to interference from a 30 V/m, 80% AM 1-kHz modulated signal. In [11], where spread-spectrum GSM900/PCS1800/3G signals were used for immunity testing, an ECG Monitor and an Ultrasonic Fetal Heart Detector B were among devices which experienced interference when exposed to electromagnetic field of values less than 1 V/m. In contrast, an audio-evoked potential system was seen to be immune up to 10 V/m.…”

Section: Introductionmentioning

confidence: 99%

EMI Risk Assessment in a Hospital Ward With One and Two Roaming Wireless Transmitters

Ardavan

Trueman

Schmitt

2015

IEEE Trans. Electromagn. Compat.

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To control electromagnetic interference, hospitals often specify that mobile transmitters may not be brought any closer than a minimum separation distance (MSD) to an electronic medical device. This paper investigates the risk that the field strength due to mobile transmitters exceeds the immunity level of a medical device. The spatial variation of the field strength can be characterized by the well-known Ricean probability distribution, using the Sabine method to evaluate the parameters. The mobility of transmitters is accounted for by assuming a function for the probability that a transmitter is present at each location throughout the hospital room. The risk of exceeding immunity is estimated with no restriction on the movement of mobile transmitters, and the reduction in risk is estimated when an MSD policy is enforced. Staff may not fully comply with the MSD, so the increase in risk with specified levels of non-compliance is found. It is shown that with some non-compliance the risk of exceeding immunity becomes constant with increasing MSD, and so specifying a larger MSD does not necessarily increase safety.

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Electromagnetic Interference Immunity Testing of Medical Equipment to Second- and Third-Generation Mobile Phones

Cited by 43 publications

References 9 publications

Internet of Vehicles for E-Health Applications: A Potential Game for Optimal Network Capacity

Internet of Vehicles for E-Health Applications: A Potential Game for Optimal Network Capacity

Mobile phone-enabled control of medical care and handicapped assistance

EMI Risk Assessment in a Hospital Ward With One and Two Roaming Wireless Transmitters

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