Remote Blood Glucose Monitoring in mHealth Scenarios: A Review <s> The Evolution to a Body Area Network Architecture (2010-Present) <s> BACKGROUND ::: Evidence-based policies have become increasingly accepted in clinical practice. However, policies on many of the non-clinical activities that take place in health care facilities may be less frequently evidence based. ::: ::: ::: METHODS ::: We carried out a review of literature on safety of mobile phones in hospitals and survey of practice in selected European countries. ::: ::: ::: RESULTS ::: When first evidence on the dangers of electronic interference associated with mobile phones appeared in the 1990s, hospitals in many countries introduced complete bans on mobile phones. Yet a review of recent evidence suggests that there is no significant risk from using mobile phones in hospitals as long as they are more than a metre away from sensitive equipment, whereas the risk to the most modern equipment is even less. With the technological evolution of mobile phones, the residual risk of interference appears to be minimal and controllable. Although some countries are reluctant to relax regulation, others now limit bans to areas in which sensitive equipment is used and some discourage the use of mobile phones on the grounds of noise exposure. ::: ::: ::: CONCLUSION ::: With new technology on the doorstep, the potential benefits and risks associated with mobile phones should be examined explicitly in the light of the evidence. <s> BIB001 </s> Remote Blood Glucose Monitoring in mHealth Scenarios: A Review <s> The Evolution to a Body Area Network Architecture (2010-Present) <s> This work describes the implementation of a complete wireless body-area network (WBAN) system to deploy in medical environments. Issues related to hardware implementations, software and wireless protocol designs are addressed. In addition to reviewing and discussing the current attempts in wireless body area network technology, a WBAN system that has been designed for healthcare applications will be presented in detail herein. The wireless system in the WBAN uses medical bands to obtain physiological data from sensor nodes. The medical bands are selected to reduce the interference and thus increase the coexistence of sensor node devices with other network devices available at medical centers. The collected data is transferred to remote stations with a multi-hopping technique using the medical gateway wireless boards. The gateway nodes connect the sensor nodes to the local area network or the Internet. As such facilities are already available in medical centers; medical professions can access patients’ physiological signals anywhere in the medical center. The data can also be accessed outside the medical center as they will be made available online. <s> BIB002 </s> Remote Blood Glucose Monitoring in mHealth Scenarios: A Review <s> The Evolution to a Body Area Network Architecture (2010-Present) <s> Pacemaker and implantable defibrillator implantation rates have increased significantly over the last decade. This, along with increasing complexity of the devices, has placed a large burden on the physicians and technicians that provide the follow up services for these patients. Recently technological advances have allowed remote interrogation of pacemakers and defibrillators with subsequent transmission of this information to a remote location for assessment. The technology behind remote device follow up, the potential advantages and the status of this technology is addressed in this article. <s> BIB003 </s> Remote Blood Glucose Monitoring in mHealth Scenarios: A Review <s> The Evolution to a Body Area Network Architecture (2010-Present) <s> Background: Developments in an artificial pancreas (AP) for patients with type 1 diabetes have allowed a move toward performing outpatient clinical trials. “Home-like” environment implies specific protocol and system adaptations among which the introduction of remote monitoring is meaningful. We present a novel tool allowing multiple patients to monitor AP use in home-like settings. Methods: We investigated existing systems, performed interviews of experienced clinical teams, listed required features, and drew several mockups of the user interface. The resulting application was tested on the bench before it was used in three outpatient studies representing 3480 h of remote monitoring. Results: Our tool, called DiAs Web Monitoring (DWM), is a web-based application that ensures reception, storage, and display of data sent by AP systems. Continuous glucose monitoring (CGM) and insulin delivery data are presented in a colored chart to facilitate reading and interpretation. Several subjects can be monitored simultaneously on the same screen, and alerts are triggered to help detect events such as hypoglycemia or CGM failures. In the third trial, DWM received approximately 460 data per subject per hour: 77% for log messages, 5% for CGM data. More than 97% of transmissions were achieved in less than 5 min. Conclusions: Transition from a hospital setting to home-like conditions requires specific AP supervision to which remote monitoring systems can contribute valuably. DiAs Web Monitoring worked properly when tested in our outpatient studies. It could facilitate subject monitoring and even accelerate medical and technical assessment of the AP. It should now be adapted for long-term studies with an enhanced notification feature. <s> BIB004 </s> Remote Blood Glucose Monitoring in mHealth Scenarios: A Review <s> The Evolution to a Body Area Network Architecture (2010-Present) <s> Type 1 Diabetes Mellitus (T1DM) is an autoimmune disease in which the insulin-producing beta cells of the pancreas are destroyed and insulin must be injected daily to enable the body to metabolize glucose. Standard therapy for T1DM involves self-monitoring of blood glucose (SMBG) several times daily with a blood glucose meter and injecting insulin via a syringe, pen or insulin pump. An “Artificial Pancreas” (AP) is a closed-loop control system that uses a continuous glucose monitor (CGM), an insulin pump and an internal algorithm to automatically manage insulin infusion to keep the subject’s blood glucose within a desired range. Although no fully closed-loop AP systems are currently commercially available there are intense academic and commercial efforts to produce safe and effective AP systems. In this paper we present the Diabetes Assistant (DiAs), an ultraportable AP research platform designed to enable home studies of Closed Loop Control (CLC) of blood glucose in subjects with Type 1 Diabetes Mellitus. DiAs consists of an Android (Google Inc., Mountain View, CA, USA) smartphone equipped with communication, control and user interface software wirelessly connected to a continuous glucose monitor and insulin pump. The software consists of a network of mobile applications with well-defined Application Programming Interfaces (APIs) running atop an enhanced version of Android with non-essential elements removed. CLC and safety applications receive real-time data from the CGM and pump, estimate the patient’s metabolic state and risk of hypo- and hyperglycemia, adjust the insulin infusion rate, raise alarms as needed and transmit de-identified data to a secure remote server. Some applications may be replaced by researchers wishing to conduct outpatient ambulatory studies of novel Closed Loop Control, Safety or User Interface modules. Over the past three years the DiAs platform has been used in a series of AP clinical trials sponsored by the National Institutes of Health, the Juvenile Diabetes Research Foundation, the Helmsley Charitable Trust and the European Union AP@Home project. Results of clinical trials using DiAs indicate that a smartphone with targeted operating system modifications and appropriate system software can be successfully used in outpatient clinical trials of FDA Class III medical devices such as Artificial Pancreas. <s> BIB005 </s> Remote Blood Glucose Monitoring in mHealth Scenarios: A Review <s> The Evolution to a Body Area Network Architecture (2010-Present) <s> Summary Background Diabetes, which has been jeopardizing human health over the past few years, can be vanquished by improving glycemic control. This paper reports the findings of the pilot study, which employed InDiaTel, a remote monitoring system for diabetic patients. This concept was supported by the Department of Science and Technology (Government of India), and the results were validated by the MedZon Diabetes Centre (Vellore, India). Methods The primary objective of InDiaTel is to monitor glucose and other vital signs continuously. It has been designed using a PIC microcontroller through multichannel data acquisition. Serial communication is established between the patient unit and the nursing and doctor units, which are in remote areas. Results For clinical evaluation, the system's output was compared with the MedZon Diabetes Centre report in which a non-invasive glucose sensor showed a deviation of 15% with glucose tolerance test (G.T.T.). Other vital signs showed good accuracy of about 95% with the commercial device. The prototype was analyzed for usability, and was accepted by more than 80% of study subjects. Conclusion The positive finding of this system improved glycemic control and confirmed the feasibility of efficient health care management. The novelty can be attributed to non-invasive measurement, multichannel data acquisition and serial communication. <s> BIB006
Rather interestingly, the improvements in ICT caused once more a paradigm shift concerning data collection and upload. The need to acquire signals using multiple sensors attached to the body, and possibly operate on it through different actuator devices led to a new architectural schema known as Body Area Network (BAN) BIB002 . BANs are wireless networks having a very limited range and interconnecting several small devices usually worn by the patient that are located within a distance of just a couple of meters. In this case, directly connecting each single device to the cloud is impossible for many reasons. First, these devices have very limited size and sometimes are even implanted under the patient skin, posing severe limitations both on their functional capabilities and power source availability. Moreover, similar to mobile phones, the radio emission required to connect to a baseband station using Third Generation Mobile Communication System (3G)/Universal Mobile Telecommunications System (UMTS) is on the order of 500 to 3000 mW and is definitely unacceptable for devices operating so close to the human body BIB001 . Finally, depending on the purpose of the BAN, an actuator may be involved, such as an insulin pump or a cardioverter device, and the logic for controlling them must be part of the very same BAN to avoid delays or unresponsive events in case of poor connectivity. Thus, a dedicated component coordinating all the devices is required such as the Body Gateway shown in Figure 3 . This component interacts using Bluetooth with the Network Hub, usually a smartphone, which is the key for enabling network connectivity and enacting the remote monitoring that is the subject of this paper. A BAN architecture may be instantiated with minimal work to support several scenarios exploiting different devices in various medical contexts BIB003 BIB006 . Incidentally, we observe that the computational power of modern Android TM smartphones is suitable for running even complex algorithms. Moreover, smartphones may also be effectively used as functional input devices thanks to their valuable displays besides still acting as Network Hubs for the telemedicine services. Thus, they are being increasingly used as prototyping devices with enhanced graphic capabilities that are available at a cost much lower than the one required for designing a custom new board from scratch. When a smartphone is used according to this paradigm, besides acting as a Network Hub, it also plays the role of a Body Gateway, with both components coalescing into a single device. However, when this solution is implemented, all the body connected devices must be capable of communicating using Bluetooth technology, since this is the only short range wireless technology supported by smartphones. An interesting example is given by the Diabetes Assistant (DiAs) BIB005 BIB004 , which is basically a commercial Android TM smartphone used for implementing an Artificial Pancreas. The DiAs will be better described in Sections 4.1 and 4.2, since it has been used by the authors in two studies involving remote monitoring on diabetes patients.