Using off-the-Shelf Medical Devices for Biomedical Signal Monitoring in a Telemedicine System for Emergency Medical Services

Thelén, Sebastian; Czaplik, Michael; Meisen, Philipp; Schilberg, Daniel; Jeschke, Sabina

doi:10.1109/jbhi.2014.2361775

Cited by 32 publications

(12 citation statements)

References 17 publications

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“…In emergency medical services (EMS), system can send an emergency request when a patient is in a critical situation. There are several EMS available where the emergency request (instant message)/ multimedia services (transmission of voice and video calls) can be sent via the cellular networks (4G/LTE,3G) [2], [3].…”

Section: Introductionmentioning

confidence: 99%

Enhanced Session Initiation Protocols for Emergency Healthcare Applications

Saha¹,

Odelu

Prasath³

2019

Communications in Computer and Information Science

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In medical emergencies, an instant and secure messaging is an important service to provide quality healthcare services. A session initiation protocol (SIP) is an IP-based multimedia and telephony communication protocol used to provide instant messaging services. Thus, design of secure and efficient SIP for quality medical services is an emerging problem. In this paper, we first explore the security limitations of the existing SIPs proposed by Sureshkumar et al. and Zhang et al. in the literature. Our analysis shows that most of the existing schemes fail to protect the user credentials when unexpectedly the sessionspecific ephemeral secrets revealed to an adversary by the session exposure attacks. We then present a possible improvement over Sureshkumar et al.'s scheme without increasing the computational cost. We compare the proposed improvement for computational overheads and security features with the various related existing schemes in the literature.

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Section: Introductionmentioning

confidence: 99%

Enhanced Session Initiation Protocols for Emergency Healthcare Applications

Saha¹,

Odelu

Prasath³

2019

Communications in Computer and Information Science

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“…In the past decades, various mobile telemedicine systems [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ] have been proposed to improve the quality of EMS using information and communication technology (ICT). Kyriacou et al [ 8 ] proposed a multi-purpose healthcare telemedicine system.…”

Section: Introductionmentioning

confidence: 99%

“…Mandellos et al [ 10 ] proposed a mobile telemedicine system for a pre-hospital treatment via GSM network; however, the interruption rate of connection was high. Thelen et al [ 11 ] implemented an integrated telemedicine system for real-time patient monitoring by employing commercially available off-the-shelf devices and software. The signal delays of ECG and SaO 2 waveforms were measured via simulated 2 G/3 G networks, and a median of 4.9 s end-to-end signal delay was reported, which exceeded the maximum acceptable delay of 4 s suggested by [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

“…Overall 539 cases were supported with this system during a five-month study period, and the results verified the feasibility of the system. However, the studies [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ] did not use any wireless biosensors and a traffic guiding system. The wireless biosensors can enable a remote accessibility and ease the wiring issues in the ambulance.…”

Section: Introductionmentioning

confidence: 99%

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Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

Tan

Gochoo

Chen

et al. 2017

Sensors

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This study presents a new ubiquitous emergency medical service system (UEMS) that consists of a ubiquitous tele-diagnosis interface and a traffic guiding subsystem. The UEMS addresses unresolved issues of emergency medical services by managing the sensor wires for eliminating inconvenience for both patients and paramedics in an ambulance, providing ubiquitous accessibility of patients’ biosignals in remote areas where the ambulance cannot arrive directly, and offering availability of real-time traffic information which can make the ambulance reach the destination within the shortest time. In the proposed system, patient’s biosignals and real-time video, acquired by wireless biosensors and a webcam, can be simultaneously transmitted to an emergency room for pre-hospital treatment via WiMax/3.5 G networks. Performances of WiMax and 3.5 G, in terms of initialization time, data rate, and average end-to-end delay are evaluated and compared. A driver can choose the route of the shortest time among the suggested routes by Google Maps after inspecting the current traffic conditions based on real-time CCTV camera streams and traffic information. The destination address can be inputted vocally for easiness and safety in driving. A series of field test results validates the feasibility of the proposed system for application in real-life scenarios.

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“…WiFi and Bluetooth are the most popular wireless media for wireless remote monitoring. For example, Thelen et al used Bluetooth for emergency medical services [ 2 ]. To overcome the disadvantage of Bluetooth’s limited coverage, a WiFi-based medical monitor system was developed [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

LBMR: Load-Balanced Multipath Routing for Wireless Data-Intensive Transmission in Real-Time Medical Monitoring

Tseng

2016

IJERPH

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In wireless networks, low-power Zigbee is an excellent network solution for wireless medical monitoring systems. Medical monitoring generally involves transmission of a large amount of data and easily causes bottleneck problems. Although Zigbee’s AODV mesh routing provides extensible multi-hop data transmission to extend network coverage, it originally does not, and needs to support some form of load balancing mechanism to avoid bottlenecks. To guarantee a more reliable multi-hop data transmission for life-critical medical applications, we have developed a multipath solution, called Load-Balanced Multipath Routing (LBMR) to replace Zigbee’s routing mechanism. LBMR consists of three main parts: Layer Routing Construction (LRC), a Load Estimation Algorithm (LEA), and a Route Maintenance (RM) mechanism. LRC assigns nodes into different layers based on the node’s distance to the medical data gateway. Nodes can have multiple next-hops delivering medical data toward the gateway. All neighboring layer-nodes exchange flow information containing current load, which is the used by the LEA to estimate future load of next-hops to the gateway. With LBMR, nodes can choose the neighbors with the least load as the next-hops and thus can achieve load balancing and avoid bottlenecks. Furthermore, RM can detect route failures in real-time and perform route redirection to ensure routing robustness. Since LRC and LEA prevent bottlenecks while RM ensures routing fault tolerance, LBMR provides a highly reliable routing service for medical monitoring. To evaluate these accomplishments, we compare LBMR with Zigbee’s AODV and another multipath protocol, AOMDV. The simulation results demonstrate LBMR achieves better load balancing, less unreachable nodes, and better packet delivery ratio than either AODV or AOMDV.

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Using off-the-Shelf Medical Devices for Biomedical Signal Monitoring in a Telemedicine System for Emergency Medical Services

Cited by 32 publications

References 17 publications

Enhanced Session Initiation Protocols for Emergency Healthcare Applications

Enhanced Session Initiation Protocols for Emergency Healthcare Applications

Ubiquitous Emergency Medical Service System Based on Wireless Biosensors, Traffic Information, and Wireless Communication Technologies: Development and Evaluation

LBMR: Load-Balanced Multipath Routing for Wireless Data-Intensive Transmission in Real-Time Medical Monitoring

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