On Designing an Ubiquitous Sensor Network for Health Monitoring Bertrand Massot∗ , Norbert Noury∗ , Claudine Gehin∗ , Eric McAdams∗ ∗ Biomedical
Sensors Group, Lyon Institute of Nanotechnology UMR CNRS 5270 INL - INSA Lyon, University of Lyon, Villeurbanne 69100 France
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[email protected] Abstract—Managing chronic health conditions at home, through the early detection of symptoms and subsequent rapid remedial action will be therapeutically and financially more effective. Unfortunately, this widely agreed upon statement implies a significant adaptation and/or evolution of present healthcare delivery, from a technological and social point of view. Designing reliable, embedded, non-intrusive sensors adapted to long-term monitoring; processing and collecting health indicators from multiple data sources; and the development of a connective healthcare delivery spanning the clinical domain and the daily environment of a given individual, are undoubted challenges facing the shift from an historical model based on the treatment of acute diseases. In this paper, we present the key possibilities capable of enabling successful implementation of health monitoring systems at home and on the move, as well as the remaining challenges to be addressed to implement these promising solutions.
I.
I NTRODUCTION
Personal Health Systems (PHS) aim to provide the necessary tools for remote health monitoring, especially for chronic conditions such as diabetes and coronary heart disease, as well as for augmenting the autonomy of disabled or elderly people and thus avoid untimely hospitalization. Based on body-worn or ambient sensors, these systems measure physiological signals and acquire relevant information on the health-related contexts of an individual in order to provide preliminary diagnostic indicators to medical staff without the need of a physical medical consultation. For the convenient, discreet and robust implementation of these functions, the development of PHS requires the use of a wide range of technologies, such as mobile technologies, embedded and wearable systems and ambient intelligence. These systems have to perform three primary functions: the measurement of physiological and behavioural signals from the individual, the processing of corresponding data to build medical indicators, and the communication of these indicators to various recipients, including the user himself, but also various medical personnel/centres. In order to achieve these objectives, a PHS is based on a network architecture whose nodes can combine several capabilities [1]: measurement/storage, measurement/signal transfer without processing, and processing/transfer of indicators. Processing the data to build medical indicators must overcome the challenge of data heterogeneity: signals are measured from various localisations (spatial diversity), at different times asynchronously (temporal diversity) and using different kind of sensors (nature diversity). Finally, the challenge of inter-
operability arises as soon as the data needs to be transferred from/to a shared electronic patient record [2]. The following sections focus on the issues related to the pre-cited capabilities of a particular sensor, depending on its integration in the various networks composing a PHS. II.
R EMAINING SENSOR ISSUES AND CHALLENGES IN A W IRELESS B ODY A REA N ETWORK
The monitoring of vital signs generally consists in the measurement of signals directly on the human body, as most assessed parameters are based on variations of physiological phenomena. Technology advances and recent developments have focussed on electronics and telecommunication solutions to set up wireless architectures, to both gather sensor data and make them available to monitoring systems and/or recording systems, possibly located over long distances. The wearability of such a network will be important in the context of a Health “Smart Home”, but may also enable continuance of the measurements in a larger ambulatory context (i.e. within multiple environments and in “outdoors” in general). However, for medical and health monitoring purposes, the body worn sensors must fulfil additional constraints of equal or even higher importance: ensuring continuous measurements with high reliability, enabling long-term monitoring without causing trauma to the body measurement site, and providing acceptable ease-of-use for any patient or user of the system [3]. Regarding electronic development and miniaturisation, the extended autonomy required for the long-term and continuous measurement of signals necessitates a drastic decrease in the device’s power consumption. This would enable the use of smaller batteries such as cell coins. In a sensor node, one of the most consuming modules is that associated with wireless data transmission, more than the analog-to-digital conversion or the data processing. Therefore an efficient reduction in power consumption will largely depend on the quantity of data sent, the range of transmission and the allocated bandwidth. The amount of data transmitted can be decreased by reducing the sampling rate of signals, but this will generally decrease the quality of indicators extracted by the remote data postprocessor. To overcome this challenge, additional embedded signal processing must be considered so that only relevant data will be sent over the radio-frequency transmission. For example, an electrocardiogram (ECG) signal is frequently sampled at 1024 Hz to reach the 1 ms precision in R-peak detection and Heart Rate (HR) computation. This is necessary to meet the required accuracy for further frequency analysis,
such as Heart Rate Variability (HRV) in monitoring mental or physical conditions. Adding a spectrum algorithm to an embedded R-peak detection will enable a direct calculation of the HR and HRV indicators can then be sent, thus lowering the data transmission rate by a minimum ratio of 1/100. This method already exists for the given example of HR (RS800, Polar Electro Oy.), and recently several devices have been realeased from different groups and SMCs (Garmin Ltd., Withings, etc.), even if sometimes questionable in terms of reliability [4]–[6], and should be appropriately applied to other physiological parameters such as electrodermal activity and respiration rate, and to behavioural parameters such as activity detection and recognition. The key point in HR is that today, the complementary development of the measurement systems and the relevance of the estimated indicators, have enabled the marketing of solutions for the monitoring of well-being based on HR. Companies like Firstbeat Technologies Oy offers services for the monitoring of physical activity and well-being by integrating commercially existing devices. The ”bottleneck” to this implementation is still the design of wearable sensors and electrodes suitable for comfortable, convenient, artefact-free measurement of bioelectrical signals. The embedded calculation of indicators assumes automated isolation and correction of potential artefacts, without any possible control afterward. Promising device developments and projects involving electrode integration in textile have been, or are still running [7]–[9], but only a very few wearable sensors are currently commercially available for true long-term and accurate measurement of heart rate, respiration rate, or electrodermal activity. The reduction of power consumption must finally take into account the radio-frequency module itself. Many papers present surveys of different protocols suitable for proper communication support for WBANs [10]–[14]: the standards emerging from these overviews are Bluetooth (BT) 2.1+EDR, Zigbee Health Care profile, Ultra Wide Band (UWB) technology protocols, Bluetooth Low Energy (BLE) and the upcoming IEEE 802.15.6. Besides the most common standards, further developements have been proposed to adapt them specially for WBANs; in particular, the underlying IEEE 802.15.4 standard for ZigBee profiles has been one of the most used to reach this obective [15]. The need for interoperability (depending on available interfaces for transmission), and the balance between average consumption and available data rate are probably the key criteria in selecting one particular standard to connect the sensor nodes. In particular, the matter of interoperability is further discussed in Section IV. III.
A FIXED - BASE NETWORK IN THE H EALTH S MART H OME
HSH systems are primarily sensing systems deployed at home to support activity detection and context awareness applications for health monitoring purposes [16]. Thus an HSH system could involve the integration of a WBAN for the measurement of physiological signals on the individual, however it mainly comprises ambient and activity sensors, together with smart tools providing additional health indicators. The main difference between activity/ambient sensors and the smart tools lies in the mobile nature of the sensor node
in the network. Activity and ambient sensors are usually fixed in the environment, integrated into floors, walls and ceilings. Activity detection is mostly based on presence detection with pressure or passive infrared (PIR) sensors, and ambient sensors measure temperature, light, etc. and therefore do not need to be moved within the home. On the other hand, smart health tools are common objects or dedicated devices for health monitoring purposes at home, freely movable by the individual: for example, smart bathroom scales can be used, not only for weighting purpose, but also to assess quality of balance and to transmit information to a server [17]. As in this application the sensor nodes remain in the home (either in a fix position or not), the challenge of energy requirements is greatly modified as every fixed component is possibly wired for both power supply and data transmission. Moreover, being located within a limited area, they can be connected to a common and unique receiver, defined as the personal processing unit. This enables, for mobile nodes sending data through wireless communication, the reduction of transmission power. Indeed, the sensitivity (antenna gain) of the receiver can be greatly increased due to its connection to main power lines, and thus one can create an optimised and mixed wired/wireless network architecture [18]. Additionally, due to discontinuous use (especially when the patient is not at home), these sensors do not require such a large data rate as WBAN sensors. Optimising sleepawake cycles of the sensors will reduce sufficiently power consumption to ensure years of autonomy even if battery powered. IV.
S CENARIOS AND SYSTEM INTEROPERABILITY
We have shown that the hardware, as well as the protocols, to be used by a particular sensor node in one of the different network previously described, depends entirely on the sensor’s required autonomy, the data rate and on the range of the wireless communication. There is therefore, no reason for using a single protocol for all networks. Although this would have given compatibility between them, and thus facilitated data gathering, the lack of optimisation would lead to a failure in the appropriate design of a pervasive, non-obtrusive and long-term health monitoring system. When considering a fixed-base network at home for the monitoring of activities, coupled to several smart tools available for the user who is wearing sensors in the form of a WBAN, two main scenarios of communication can be identified: the first one when the user is at home and the second one when he is not. Definitions of these scenarios, related only to the communication mode between the networks, do not take into account the medical / health monitoring application itself, as the latter doesn’t change the main configuration of the networks. At home, a local area network could be used as a common architecture to make the data available to a single processing unit, as many homes are already equipped with such a network (by Ethernet or Wi-Fi). For example, market penetration of the triple play service has reached 38% in France in 2012, and is planned to reach 60% in 2015 [19]. This provides both an internal network structure (LAN) as well as external connectivity
via the Internet (WAN). A central processing unit could be connected into this network, having the role of both collecting data from the different sensors surrounding it, and making the results available to the local user through a computer application and to any telemedicine service via the Internet. If the different sensor networks are to communicate directly on an existing Ethernet or Wi-Fi, no additional interface would be needed for the processing unit to receive data. On the other way, if the networks are based on other kinds of protocol, such as ZigBee which is optimised for battery powered sensors, the communication interface could be directly integrated into the processing unit as this is the only part of the structure which needs to collect the data to be processed. Obviously, this applies particularly to the WBAN. Due to the very limited range required by the communication between the sensor nodes, this network has not only the need of a gateway with the LAN to communicate with the processing unit when the user is at home, but also when he is on the move. A smartphone clearly appears to be a perfect device to play this role. In terms of interoperability, it already implements several protocols which enable its connection to the processing unit both at home and outside: Wi-Fi and Bluetooth for local connection and EDGE, HSDPA, or the upcoming LTE (4G) for a remote connection. Similar to the use of an existing network architecture in the home, the use of a Smartphone avoids the need of the user to carry an additional device to serve as a gateway, the Smartphone fulfilling this requirement. In France, the market penetration of mobile phones has exceeded 100%, to reach 108% at the end of 2012. Smartphones already represent a market penetration of 51.4% in France in 2012 (MobiLens, ComScore Inc.), and is predicted to exceed 70% in 2015 [19]. On the WBAN’s side, every smartphone implements today the Bluetooth 2.1 protocol, and new devices are getting Bluetooth Smart Ready hardware. The Bluetooth Low Energy is a straight contender to support WBAN as it matches very low current consumption, reasonable data rate and high interoperability with a unique standardised protocol. By way of illustration, Fig. 1 shows hardware connection and supporting protocols for the situations described above. A standardised format to exchange the various data still remains to be defined, however different projects are currently studying which approach could match the requirements, for example implementations of Health Level 7 (HL7) [20], [21] or ISO/IEEE 11073 [22], [23]. V.
A PPLICATIONS , FROM LOCAL BIOFEEDBACK TO REMOTE HEALTHCARE
The variety of sensors, exploited within the various networks described above, form an overarching system for the Health monitoring on the user. The most promising application of such a system would be the remote healthcare monitoring/provision of patients by remote medical services, but this requires much further development of communication standards and software implementation, and especially requires the adaptation of the healthcare provider system on a very wide scale. Living Labs for Health are emerging structures which might develop and test these services at a small scale before wider implementation; however this process is slowed by
Fig. 1. Generic network architecture for a health monitoring system. Smartphone connects body worn sensors to the personal processing unit through LAN if client at home or WAN if away.
the complexity of integrating these novel services/capabilities within existing practice, and the lack of sufficient involvement of clinical staff. A. Mobile applications The use of smartphones as gateways for WBAN enables a direct display to the user of the measured signals. The development of mobile applications can then use these data for a more advanced form of biofeedback, providing the user with information on his/her physical or mental condition, depending on the parameters (i.e. the sensors) available. There are already many applications which could be integrated into this platform: HRV and EDA analysis can be used for the monitoring of mental stress [24], combined with accelerometers to derive information on physical state. There are, for example, Polar devices and mobile applications integrating physical training with virtual coaches. For chronic diseases, WBAN can monitor specific parameters through the use of appropriate sensors (glucose meter for blood glucose monitoring, impedance meter for wound monitoring, etc.), whose number is growing with the development of new wearable technologies. These applications might also benefit from the services already accessible by smartphones, such as geolocation, accelerometers signals and online services providing environment information. B. Smart Home applications When at home, sensors of the fixed-base network provide additional information that supplements the WBAN and therefore expands the field of applications. For example, the monitoring of activities of daily living (ADL) by PIR sensors can be used for automated lighting, but a thorough analysis of ADLs is also useful for the monitoring of circadian rhythms and to detect the gradual lose of independence in elderly people [16]. Even if there is still a lack of standard connectivity to medical centres, there are already commercialised smart tools
for user-managed personal health: Blood pressure monitors, glucose meters, smart scales connected to a smartphone with a dedicated application to analyse and record information (iHealth Lab, Inc.) are examples of preliminary applications which demonstrate the already existing feasibility of Health Smart Home. VI.
D ISCUSSION
What is noticeable in the research area of WBAN is that significant progress have been made, related to the focus of research groups on telecommunication and electronics, in the optimisation of network protocols and miniaturisation of devices. On the other hand, there has been less significant progress during the last few years regarding robustness of physiological measurement in an ambulatory context, thus preventing from the development of relevant indicators for health monitoring, but also on near-field interoperability of the WBAN. In parallel, major groups like Apple, Polar or Garmin, slightly competed by SMEs, have released connected devices based on currently available standards, enabling direct connection of their devices to any smart tool (smartphone, touchpad, laptop). This implies that the most widespread standards (BT2.1, BLE, WiFi), might rule the future of communication tools to be qualified interoperable, thus justifying the architecture of the network presented in this paper. To take advantage of the different protocols and communication techniques presented in the litterature, which are truly optimised for WBAN connectivity, one must consider to avoid the use of smartphone as a gateway (cf. Fig. 2): •
Firstly to avoid an additionnal device, to keep intrusivity of the system at a minimum;
•
Secondly to enable the use of a custom, optimised and dedicated protocol for WBAN communication.
to connect to the personnal unit. At home, the basic solution would be to integrate a receiver in the unit which is directly compatible with the BAN protocol, thus maintaining the same capabilities for Smart Home applications. However, this architecture has two major drawbacks when being on the move: the first one is the loss of connectivity to wider networks unless an additionnal device is used for this specific connection (either to the phone or directly to cellular networks), but the use of additionnal devices should remain unwanted as it reduces wearability and comfort of the BAN. The second drawback is the loss of direct feedback for the user, which has become a strong argument for the acceptability of mobile health systems. VII.
C ONCLUSION
PHS commercialisation has been too slow up to the present to significantly improve healthcare and quality of life, and to reduce healthcare costs. This failure is often attributed to interoperability challenges and to the complexity of integrating novel systems with existing clinical practice. There has been insufficient appropriate clinical-pull to facilitate the implementation of a novel and effective management of chronic disease. However, by means of attractive, reliable and well-designed products, we can already see that more and more people are educating and equipping themselves to use health or fitness monitoring systems based on the currently existing networks and infrastructures (Bluetooth, WiFi, smartphone, etc.). By providing more home-health monitoring products and extended systems (through the use of a more global network, such as the internet and home LAN), the greater “social readiness” will stimulate scientists and clinicians to fully connect the “home health network” to medical structures. R EFERENCES [1]
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Fig. 2. Generic network architecture for a health monitoring system without using smartphone connectivity and feedback. Body worn sensors connect directly to the personal processing unit at home, but only use data-logging if on the move.
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