EMC and wireless healthcare

Tang

et al. 2017

IEEE Systems Journal

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

Section: Related Work Of Emi On Medical Sensorsmentioning

confidence: 99%

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

Tang

et al. 2017

IEEE Systems Journal

“…However, the test in [16] did not take into account the quality of service (QoS) of data which are transmitted between patient devices and doctor devices. The strategies of restricting the use of mobile phones, such as switching off mobile phones, are not applicable for the scenario of a wireless healthcare monitoring system [17]. In wireless healthcare monitoring systems, doctors and patients need to employ wireless devices to transmit data and establish communication, and the restriction on the level of transmit power may cause a lower level of QoS of data transmission, which would lead to the loss of medical data.…”

Section: Related Work Of Emi On Medical Sensorsmentioning

confidence: 99%

Optimal Network QoS over the Internet of Vehicles for E-Health Applications

Yao

Mobile Information Systems

et al. 2016

Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario is the electromagnetic interference (EMI) caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In consideration of EMI on medical sensors, we study the optimization of quality of service (QoS) within the whole Internet of vehicles for E-health and propose a novel model to optimize the QoS by allocating the transmit power of each user. Our results show that the optimal power control policy depends on the objective of optimization problems: a greedy policy is optimal to maximize the summation of QoS of each user, whereas a fair policy is optimal to maximize the product of QoS of each user. Algorithms are taken to derive the optimal policies, and numerical results of optimizing QoS are presented for both objectives and QoS constraints.

“…However, the measurement in [16] has not considered the QoS of data transmitted by patient devices and healthcare staff devices. The policy on mobile phone utilization, such as turning off mobile phone, cannot be applicable for patient devices and healthcare staff devices in a wireless healthcare monitoring system [17]. In wireless healthcare monitoring systems, healthcare staff and patients should employ wireless devices for data transmission and communication, and the restriction on transmit power may reduce the quality of service (QoS) of data transmission, which may increase the risk of medical data loss.…”

Section: Related Work Of Emi On Medical Sensorsmentioning

confidence: 99%

Internet of Vehicles for E-Health Applications in View of EMI on Medical Sensors

et al. 2015

Journal of Sensors

Wireless technologies are pervasive to support ubiquitous healthcare applications. However, RF transmission in wireless technologies can lead to electromagnetic interference (EMI) on medical sensors under a healthcare scenario, and a high level of EMI may lead to a critical malfunction of medical sensors. In view of EMI to medical sensors, we propose a joint power and rate control algorithm under game theoretic framework to schedule data transmission at each of wireless sensors. The objective of such a game is to maximize the utility of each wireless user subject to the EMI constraints for medical sensors. We show that the proposed game has a unique Nash equilibrium and our joint power and rate control algorithm would converge to the Nash equilibrium. Numerical results illustrate that the proposed algorithm can achieve robust performance against the variations of mobile hospital environments.