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By Alexandra Cristobal-Huerta 1, † , Angel Torrado-Carvajal 1, 2, † , Cristina Rodriguez-Sanchez 1 , Juan Antonio Hernandez-Tamames 1 , Maria Luaces 3 and Susana Borromeo 1, 2, *
Current m-Health scenarios in the smart living era, as the interpretation of the smart city at each person’s level, present several challenges associated with interoperability between different clinical devices and applications. The Continua Health Alliance establishes design guidelines to standardize application communication to guarantee interoperability among medical devices. In this paper, we describe the implementation of two IEEE agents for oxygen saturation level (SpO2) measurements and electrocardiogram (ECG) data acquisition, respectively, and a smartphone IEEE manager for validation. We developed both IEEE agents over the Bluetooth Health Device Profile following the Continua guidelines and they are part of a telemonitoring system. This system was evaluated in a sample composed of 10 volunteers (mean age 29.8 ± 7.1 y/o; 5 females) under supervision of an expert cardiologist. The evaluation consisted of measuring the SpO2 and ECG signal sitting and at rest, before and after exercising for 15 min. Physiological measurements were assessed and compared against commercial devices, and our expert physician did not find any relevant differences in the ECG signal. Additionally, the system was assessed when acquiring and processing different heart rate data to prove that warnings were generated when the heart rate was under/above the thresholds for bradycardia and tachycardia, respectively.
M-Health was first introduced as “Unwired e-med” in the IEEE Transactions on Information Technology in Biomedicine journal in 2000 [1]. Over the past 20 years, the development and advancements in information and communication technologies (ICTs) and connectivity has impacted m-Health directly. In this sense, smart living is the interpretation of the smart city but at the level of each person’s home, creating a new lifestyle thanks to the inclusion of these ICT improvements in their own personal spaces. This new way of living involves, among others, the fields of health, safety, home automation, and smart services, where new technologies are present in the complete cycle of patient treatment. Concretely, new scenarios have emerged where healthcare professionals have access to the Hospital Information System (HIS) anywhere and anytime [2, 3].
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In this framework, new technologies should be present in the complete cycle of patient treatment and ICTs can improve healthcare in developed economies by minimizing unnecessary visits to a hospital [4, 5, 6]. These techniques and devices for early measurement of parameters allow for the continuous and ubiquitous monitoring of patients through medical decision support applications (alarms, shared diagnosis, DSS (Decision Support systems), etc.), helping in the diagnosis, monitoring, and intervention of patients. The deployment of these applications improves the ubiquity of healthcare providers in hospitals, increasing the time they spend with patients [6, 7, 8, 9, 10]. However, the new paradigm of health care in urban environments brings with it the implementation of ICT-intensive devices with smaller, higher-performance electronic sensors, and systems with greater interactivity to improve health management. This requires the optimization of interoperable medical sensor networks with terminals to fasten responses in emergency situations where a rapid actuation could be crucial, impacting directly on the efficient use of the infrastructure and reducing costs related to clinical environments.
In this scenario, where many prototypes of m-health systems based on the Body Area Network (BAN) are becoming popular, the main drawback these systems face in the smart living approach is the lack of interoperability among medical devices [11], which could promote a homogeneous e-health ecosystem [12]. Furthermore, the current situation presents several challenges associated to the certification and regulation of these devices and their software to be interoperable [13]. Clinical applications must adapt to a paradigm in which results are repeatable and reliable. In this context, standards are crucial to the advancement of smart cities and smart living to help smooth the implementation of innovative technologies and deliver a reliable framework for practitioners. In addition, the interfaces must follow these standards to be integrated in a hospital infrastructure without many changes. Thus, the development and maintenance processes must be agile [14].
ISO/IEEE 11073 “Health informatics—Point-of-care medical device and Personal Health Device (PHD) communication standards” is a family of standards that enable communication between medical, healthcare, and wellness devices with external computer systems. These standards are based on a single framework, ISO/IEEE 11073-20601, and several device specializations (Figure 1). They provide automatic and detailed electronic data capture of client-related and vital signs information and of device operational data. The IEEE 11073 Personal Health Devices (PHD) initiative was designed to accommodate the capabilities of low-power embedded devices and very low-power wireless technologies. Additionally, the use of transport technologies was designed to adapt them to this interface, resulting in the base protocol IEEE 11073-20601. Bluetooth, USB, ZigBee, and NFC each developed a standard (most recently NFC), and these are profiled by the Continua Alliance guidelines to apply these standards and guarantee interoperability between medical devices. This methodology establishes a product certification program, as well as collaboration with government regulatory agencies.
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Continua Health Alliance’s design guidelines are focused on the Interface to Personal Area Network health devices (PAN-IF) and the Interface between Disease Management Services (DMS), Wireless Area Network (WAN) devices (xHR Senders), and Electronic Health Record (EHR) devices (xHR Receivers) (xHRN-IF). Continua follows the Open Systems Interconnection (OSI) model to establish the protocols to use for interoperability in the PAN-IF. The protocols used in the different OSI layers can be seen in Figure 1 [15].
Continua has constrained the lower-level protocol standards for Bluetooth and USB communications with the use of specific profiles for health devices. For the higher layers, Continua uses the ISO/IEEE 11073 standards family, concretely the IEEE 11073-20601-Optimized Exchange Protocol and ISO/IEEE 11073-104xx-device specializations to provide application-level interoperability.
The ISO/IEEE 11073 series of standards is based on an object-oriented system management paradigm. The system model is divided into three principal components: the domain information model (DIM), the service model, and the communication model.
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The DIM describes an agent as a set of objects with attributes, which represent the behavior of the data that can be sent to the manager. The communication between the agent and the manager is defined by the ISO/IEEE 11073-20601 standard. The service model defines the messages that an agent and a manager interchange following Abstract Syntax Notation One (ASN.1). These messages are encoded in Medical Device Encoding Rules (MDER), described in the ISO/IEEE 11073-20101 standard. The communication model supports the topology of one or more agents communicating over logical point-to-point connections to a single manager. A connection state machine, specified in ISO/IEEE 11073-20601, defines the system behavior for each connection.
Above the IEEE 11073-20601 exchange protocol, are the device specializations that describe specific details about how a type of agent works and the objects and attributes that it has. For the system implemented in this paper, the pulse oximeter (IEEE 11073-10404) and the recently basic ECG (IEEE 11073-10406) specializations were used.
The aim of this paper is to investigate the feasibility of the SpO2 and ECG medical devices, following the Continua guidelines [16], for increasing the adherence of patients to a cardiac rehabilitation treatment. Cardiac rehabilitation patients have cardiovascular problems. Vital signs such as heart rate (HR) and oxygen saturation are used as predictors of recovery after surgery or in patients with coronary artery disease (CAD) who underwent rehabilitation [17, 18]. When they are being evaluated or undergo physical training, it is essential to monitor their blood pressure and heart rate (HR) both at rest and the increase during the exercise they are doing, measuring baseline blood pressure and heart rate and peak effort. In addition, SpO2 is measured because if it drops below 90%, training must be stopped. Therefore, the measure of SpO2 and HR is mandatory for any patient undergoing cardiac rehabilitation treatment or high-risk patients [19]. In the next sections, we describe our system architecture consisting of two modules. The hardware module includes a description of the signal acquisition, processing, and transmission, corresponding with the IEEE agent-node that transmits personal health
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Continua Health Alliance’s design guidelines are focused on the Interface to Personal Area Network health devices (PAN-IF) and the Interface between Disease Management Services (DMS), Wireless Area Network (WAN) devices (xHR Senders), and Electronic Health Record (EHR) devices (xHR Receivers) (xHRN-IF). Continua follows the Open Systems Interconnection (OSI) model to establish the protocols to use for interoperability in the PAN-IF. The protocols used in the different OSI layers can be seen in Figure 1 [15].
Continua has constrained the lower-level protocol standards for Bluetooth and USB communications with the use of specific profiles for health devices. For the higher layers, Continua uses the ISO/IEEE 11073 standards family, concretely the IEEE 11073-20601-Optimized Exchange Protocol and ISO/IEEE 11073-104xx-device specializations to provide application-level interoperability.
The ISO/IEEE 11073 series of standards is based on an object-oriented system management paradigm. The system model is divided into three principal components: the domain information model (DIM), the service model, and the communication model.
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The DIM describes an agent as a set of objects with attributes, which represent the behavior of the data that can be sent to the manager. The communication between the agent and the manager is defined by the ISO/IEEE 11073-20601 standard. The service model defines the messages that an agent and a manager interchange following Abstract Syntax Notation One (ASN.1). These messages are encoded in Medical Device Encoding Rules (MDER), described in the ISO/IEEE 11073-20101 standard. The communication model supports the topology of one or more agents communicating over logical point-to-point connections to a single manager. A connection state machine, specified in ISO/IEEE 11073-20601, defines the system behavior for each connection.
Above the IEEE 11073-20601 exchange protocol, are the device specializations that describe specific details about how a type of agent works and the objects and attributes that it has. For the system implemented in this paper, the pulse oximeter (IEEE 11073-10404) and the recently basic ECG (IEEE 11073-10406) specializations were used.
The aim of this paper is to investigate the feasibility of the SpO2 and ECG medical devices, following the Continua guidelines [16], for increasing the adherence of patients to a cardiac rehabilitation treatment. Cardiac rehabilitation patients have cardiovascular problems. Vital signs such as heart rate (HR) and oxygen saturation are used as predictors of recovery after surgery or in patients with coronary artery disease (CAD) who underwent rehabilitation [17, 18]. When they are being evaluated or undergo physical training, it is essential to monitor their blood pressure and heart rate (HR) both at rest and the increase during the exercise they are doing, measuring baseline blood pressure and heart rate and peak effort. In addition, SpO2 is measured because if it drops below 90%, training must be stopped. Therefore, the measure of SpO2 and HR is mandatory for any patient undergoing cardiac rehabilitation treatment or high-risk patients [19]. In the next sections, we describe our system architecture consisting of two modules. The hardware module includes a description of the signal acquisition, processing, and transmission, corresponding with the IEEE agent-node that transmits personal health
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