A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Testbed Implementation of M2M Solutions <s> Emerging healthcare applications rely on personal mobile devices to monitor and transmit patient vital signs to hospital-backend servers for further analysis. However, these devices have limited resources that must be used optimally in order to meet the application user requirements (e.g. safety, usability, reliability, performance). This paper reports on a case study of a Chronic Obstructive Pulmonary Disease telemonitoring application delivered by the mobihealth system. This system relies on a commercial mobile device with multiple (wireless) Network Interfaces (NI). Our study focuses on how NI activation strategies affect the application end-to-end data delay (important in case of an emergency situation) and the energy consumption of the device (important for device sustainability while a patient is mobile). Our results show the trade-off between end-to-end delay and battery life-time achieved by various NI activation strategies, in combination with application-data flow adaptation for realtime and near real-time data transmission. For a given mobile device, our study shows an increase in battery life-time of 40- 90 %, traded against higher end-to-end data delay. The insights of our studies can be used for application-data flow adaptation aiming to increase battery life-time and device sustainability for mobile patients; which effectively increases the healthcare application usability. <s> BIB001 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Testbed Implementation of M2M Solutions <s> This study presents a healthcare monitoring architecture coupled with wearable sensor systems and an environmental sensor network for monitoring elderly or chronic patients in their residence. The wearable sensor system, built into a fabric belt, consists of various medical sensors that collect a timely set of physiological health indicators transmitted via low energy wireless communication to mobile computing devices. Three application scenarios are implemented using the proposed network architecture. The group-based data collection and data transmission using the ad hoc mode promote outpatient healthcare services for only one medical staff member assigned to a set of patients. Adaptive security issues for data transmission are performed based on different wireless capabilities. This study also presents a monitoring application prototype for capturing sensor data from wireless sensor nodes. The implemented schemes were verified as performing efficiently and rapidly in the proposed network architecture. <s> BIB002 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Testbed Implementation of M2M Solutions <s> Standard Communication Protocol for Computer-assisted Electrocardiography (SCP-ECG) provides standardized communication among different ECG devices and medical information systems. This paper extends the use of this protocol in order to be included in health monitoring systems. It introduces new sections into SCP-ECG structure for transferring data for positioning, allergies, and five additional biosignals: noninvasive blood pressure (NiBP), body temperature (Temp), Carbon dioxide (CO(2)), blood oxygen saturation (SPO(2)), and pulse rate. It also introduces new tags in existing sections for transferring comprehensive demographic data. The proposed enhanced version is referred to as e-SCP-ECG(+) protocol. This paper also considers the pilot implementation of the new protocol as a software component in a Health Telemonitoring System. <s> BIB003 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Testbed Implementation of M2M Solutions <s> This paper describes a novel healthcare IT platform developed under the LOBIN project, which allows monitoring several physiological parameters, such as ECG, heart rate, body temperature, etc., and tracking the location of a group of patients within hospital environments. The combination of e-textile and wireless sensor networks provides an efficient way to support noninvasive and pervasive services demanded by future healthcare environments. This paper presents the architecture, system deployment as well as validation results from both laboratory tests and a pilot scheme developed with real users in collaboration with the Cardiology Unit at La Paz Hospital, Madrid, Spain. <s> BIB004 </s> A Survey on M2M Systems for mHealth: A Wireless Communications Perspective <s> Testbed Implementation of M2M Solutions <s> This paper presents a prototype machine-to-machine (M2M) healthcare solution that combines mobile and IPv6 techniques in a wireless sensor network to monitor the health condition of patients and provide a wide range of effective, comprehensive, and convenient healthcare services. A low-power embedded wearable sensor measures the health parameters dynamically, and is connected, according to the concept of IPv6 over low-power wireless personal area network, to the M2M node for wireless transmission through the internet or external IP-enabled networks via the M2M gateway. A visualization module of the server program graphically displays the recorded biomedical signals on Android mobile devices used by patients and doctors at the end of the networks in real-time. Our approach for a global M2M healthcare solution is managed to process the large amount of biomedical signals through the extended network combining IPv6 technique and mobile technology for daily lifestyle to users appropriately. <s> BIB005
Research on end-to-end connectivity is not limited to a theoretical-only level. During the last years, research efforts have been devoted to the actual implementation of M2M networks. In this section, we present the most representative examples of implemented end-to-end solutions for mHealth applications. In BIB003 , the authors introduce a new file format for the transfer of sensory data and implement a pilot testbed for an end-to-end patient monitoring application. Their contribution is twofold. First, they present an enhanced version of a standard protocol for communication among ECG devices, by proposing an adaptive data structure that can handle multiple vital signals, as well as data for positioning, allergies and demographic information on patients. The definition of a standardized data structure is an important step towards the integration of the medical data measured by the WBAN sensors with various mHealth information systems for monitoring or administrative purposes, belonging to hospitals, individual care-givers, home-care, etc. Second, they implement a testbed of an M2M healthcare application for the remote monitoring of patients suffering from heart problems. The patient is equipped with a WBAN formed by a number of wearable sensors, a Global Positioning System (GPS) device and a PDA. The PDA aggregates the sensory and geolocation data, as well as any additional information inserted manually by the patient, and plays the role of the M2M gateway. On the one hand, it employs Bluetooth technology to communicate with the WBAN nodes and, on the other hand, it has mobile ADSL capabilities to forward the data to the remote server located at a hospital facility. To the other end of the system, a portable data acquisition system is considered, consisting of a medical monitor device, a GPS and a laptop with Internet connectivity. Finally, a software application has been developed for the processing and visualization of the data retrieved by the healthcare provider. The pilot testing of the proposed solution on real patients has revealed some very interesting conclusions. From the doctors' perspective, the use of the M2M mHealth system has been an overall positive experience, facilitating the patient monitoring and the collection of data. The patients, on the other hand, have given a more neutral evaluation. Even though they have generally been satisfied by the experience, they have shown more concerns on the wearability of the sensors, the user friendliness of the software application and the data collection process. A two-tier architecture is considered in BIB001 to implement a remote monitoring application for patients with Chronic Obstructive Pulmonary Disease (COPD). Bluetooth is used as the WBAN technology for the communication between the sensors and the coordinating node (e.g., a PDA). Apart from the Bluetooth network interface, the coordinating node can support two additional long-range wireless technologies for Internet connectivity with a remote medical server: cellular General Packet Radio Service (GPRS) and WiFi. The authors perform an interesting experiment by measuring system performance metrics of these two upper-tier technologies. The study clearly shows that GPRS and WLAN have complementary power and delay profiles: the energy consumption of GPRS is low but high delays may be observed, whereas WiFi has higher energy cost but lower delays. Based on the observed results, the authors provide guidelines for the design of an adaptive protocol that switches between the two long-range technologies depending on the scenario: (i) WiFi is the recommended technology, when available, especially in emergency situations due to the low data latency. In these cases, the GPRS interface should remain on but at an idle state, employed only to receive incoming calls if needed; (ii) if the WiFi connection is not available, the WiFi network interface should be switched off completely and GPRS should be employed for communication. A prototype M2M solution built on Android mobile devices is presented in BIB005 . At the patient's side, wearable sensors are employed to measure physiological data such as ECG and oxygen saturation. The sensor nodes are connected to M2M nodes, which are, in turn, wirelessly connected to the Internet through the M2M gateway. The sensor network employs the IEEE 802.15.4 protocol along with the IPv6 addressing mechanism. At the other end of the M2M system, a server PC collects and processes the sensor data, which are ultimately made available to the medical personnel through a user-friendly Android application. By combining Ipv6 techniques over mobile communication technology, this testbed implementation has provided a practical, scalable and flexible way to make a large amount of biomedical signals accessible online. In some works, ambient sensor networks for environmental monitoring are employed in conjunction with WBANs, in order to provide additional information on the patient's whereabouts, such as temperature, humidity and light conditions. Along this line, a three-tier network architecture, depicted in Figure 6 , is proposed in BIB002 , for the remote monitoring of elderly or chronic patients in their residence. The lower tier consists of two systems: (i) a patient-worn fabric belt, which integrates the medical sensors and is equipped with a Bluetooth transceiver; and (ii) the ambient wireless sensors that form a ZigBee network and are deployed in the patient's surroundings (e.g., in the patient's home or in a nursing house). In the middle tier, an ad hoc network of powerful mobile computing devices (e.g., laptops, PDAs, etc.) gathers the medical and ambient sensory data and forwards them to the higher tier. The middle-tier devices must have multiple network interfaces: Bluetooth and ZigBee to communicate with the lower tier and WLAN or cellular capabilities for connection with the higher layer. Finally, the higher tier is structured on the Internet and includes the application databases and servers that are accessed by the healthcare providers. The study involves a real implementation of the proposed architecture and tackles several security issues that arise along the three tiers. The proposed framework offers a flexible and secure solution for the monitoring of multiple patients that can be applied to different scenarios, including home, hospital and nursing home environments. Sensor networks can also be employed for patient localization purposes. In BIB004 , the authors propose a system architecture based on two independent subsystems for the monitoring and location tracking of patients within hospital environments, as shown in Figure 7 . The healthcare monitoring subsystem consists of smart shirts with integrated medical sensors, each equipped with a wireless IEEE 802.15.4 module. The location subsystem has two components: (i) a deployment of wireless IEEE 802.15.4 nodes that are installed in known locations within the hospital infrastructure and broadcast periodic beacon frames; and (ii) IEEE 802.15.4 end devices, held by the patients, that collect signal strength information from the received beacons. Both subsystems transmit their respective data (i.e., medical sensory data and signal strength information) to a gateway through an IEEE 802.15.4-based ad hoc distribution network. The gateway has wired Internet connectivity and forwards the data to the management server and the monitoring mHealth application. The proposed system has been tested with success in a hospital, achieving high reliability, sufficient battery lifetime of the sensors and real-time data reconstruction. In terms of usability, the obtained feedback of the medical personnel has been taken into account to improve the software interface. 