An experimental study of ZigBee for body sensor networks

We present an experimental performance evaluation of ZigBee networks in the context of data-intensive body sensor networks (BSNs). IEEE 802.15.4/ZigBee devices were mainly developed for use in wireless sensors network (WSN) applications; however, due to characteristics such as low power and small form factor, they are also being widely used in BSN applications, making it necessary to evaluate their suitability in this context. The delivery ratio and end-to-end delay were evaluated, under contention, for both star and tree topologies. The reliability of the ZigBee network in a star topology without hidden nodes was very good (delivery ratio close to 100%), provided the acknowledgement mechanism was enabled. On the other hand, the performance in a tree topology was degraded due to router overload and the activation of the route maintenance protocol triggered by periods of high traffic load. The effect of the devices’ clock drift and hidden nodes on the reliability of the star network was modeled and validated through experimental tests. In these tests, the worst-case delivery ratio when the acknowledgment is used decreased to 90% with two sensor nodes, while for the non-acknowledged mode the result was of 13%. These results show that a mechanism for distributing the nodes’ traffic over the time is required to avoid BSN performance degradation caused by router overload, clock drift and hidden node issues.Fundação para a Ciência e Tecnologi

Μελέτη διόδου FM/FI/NM με την μέθοδο των πεπερασμένων διαφορών

107 σ.Μεταπτυχιακή Εργασία--Εθνικό Μετσόβιο Πολυτεχνείο. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) "Φυσική και Τεχνολογικές Εφαρμογές"Η παρούσα μεταπτυχιακή διπλωματική αναφέρεται σ την μελέτη μιας μαγνητικής διόδου του τύπου FM/FI/Nm με τη μέθοδο των πεπερασμέων διαφορών. Το κύριο χαρακλτηριστικό μιας τέτοιας διόδου είναι το φαινόμενο spin filtering. Η μέθοςδος των πεπερασμένων διαφορών είναι μια προσεγγιστική μέθοδος που επιτρέπει τη μοντελοποίηση υπό μορφή κώδικα της διόδου.It is the study of a magnetic tunnel junction with the use of finite differences method. THe maincharacteristic of such junctions is that they aresubjected to the spin filter phenomenon.Ιωάννης Ν. Παντελόπουλο

An intra-vehicular wireless sensor network based on Android mobile devices and bluetooth low energy

This chapter presents the development and test of an intra-vehicular wireless sensor network (IVWSN), based on Bluetooth Low Energy (BLE), designed to present to the driver, in real-time, information collected from multiple sensors distributed inside of the car, using a human-machine interface (HMI) implemented on an Android smartphone. The architecture of the implemented BLE network is composed by the smartphone, which has the role of central station, and two BLE modules (peripheral stations) based on the CC2540 system-on-chip (SoC), which collect relevant sensor information from the battery system and the traction system of a plug-in electric car. Results based on an experimental performance evaluation of the wireless network show that the network is able to satisfy the application requirements, as long as the network parameters are properly configured taking into account the peculiarities of the BLE data transfer modes and the observed limitations of the BLE platform used in the implementation of the IVWSN.This work is supported by FCT with the reference project UID/EEA/04436/2013, COMPETE 2020 with the code POCI-01-0145-FEDER-006941

Exploiting linked data to create rich human digital memories

Memories are an important aspect of a person's life and experiences. The area of human digital memories focuses on encapsulating this phenomenon, in a digital format, over a lifetime. Through the proliferation of ubiquitous devices, both people and the surrounding environment are generating a phenomenal amount of data. With all of this disjointed information available, successfully searching it and bringing it together, to form a human digital memory, is a challenge. This is especially true when a lifetime of data is being examined. Linked Data provides an ideal, and novel, solution for overcoming this challenge, where a variety of data sources can be drawn upon to capture detailed information surrounding a given event. Memories, created in this way, contain vivid structures and varied data sources, which emerge through the semantic clustering of content and other memories. This paper presents DigMem, a platform for creating human digital memories, based on device-specific services and the user's current environment. In this way, information is semantically structured to create temporal "memory boxes" for human experiences. A working prototype has been successfully developed, which demonstrates the approach. In order to evaluate the applicability of the system a number of experiments have been undertaken. These have been successful in creating human digital memories and illustrating how a user can be monitored in both indoor and outdoor environments. Furthermore, the user's heartbeat information is analysed to determine his or her heart rate. This has been achieved with the development of a QRS Complex detection algorithm and heart rate calculation method. These methods process collected electrocardiography (ECG) information to discern the heart rate of the user

Design and testing of a textile EMG sensor for prosthetic control

Nowadays, Electromyography (EMG) signals generated by the amputee’s residual limbs are widely used for the control of myoelectric prostheses, usually with the aid of pattern-recognition algorithms. Since myoelectric prostheses are wearable medical devices, the sensors that integrate them should be appropriate for the users’ daily life, meeting the requirements of lightness, flexibility, greater motion identification, and skin adaptability. Therefore, this study aims to design and test an EMG sensor for prosthetic control, focusing on aspects such as adjustability, lightness, precise and constant signal acquisition; and replacing the conventional components of an EMG sensor with textile materials. The proposed sensor was made with Shieldex Technik-tex P130 + B conductive knitted fabric, with 99% pure silver plating. EMG data acquisition was performed twice on three volunteers: one with the textile sensor, and other with a commercial sensor used in prosthetic applications. Overall, the textile and the commercial sensor presented total average Signal-to-Noise Ratio (SNR) values of 10.24 ± 5.45 dB and 11.74 ± 8.64 dB, respectively. The authors consider that the obtained results are promising and leave room for further improvements in future work, such as designing strategies to deal with known sources of noise contamination and to increase the adhesion to the skin. In sum, the results presented in this paper indicate that, with the appropriate improvements, the proposed textile sensor may have the potential of being used for myoelectric prosthetic control, which can be a more ergonomic and accessible alternative to the sensors that are currently used for controlling these devices.This work is financed by Project “Deus ex Machina”, NORTE-01-0145-FEDER-000026, funded by CCDRN, through Sistema de Apoio à Investigação Científica e Tecnológica (Projetos Estruturados I&D&I) of Programa Operacional Regional do Norte, from Portugal 2020 and by Project UID/CTM/00264/2019 of 2C2T –Centro de Ciência e TecnologiaTêxtil, funded by National Founds through FCT/MCTES

Uranus: A Middleware Architecture for Dependable AAL and Vital Signs Monitoring Applications

The design and realization of health monitoring applications has attracted the interest of large communities both from industry and academia. Several research challenges have been faced and issues tackled in order to realize effective applications for the management and monitoring of people with chronic diseases, people with disabilities, elderly people. However, there is a lack of efficient tools that enable rapid and possibly cheap realization of reliable health monitoring applications. The paper presents Uranus, a service oriented middleware architecture, which provides basic functions for the integration of different kinds of biomedical sensors. Uranus has also distinguishing characteristics like services for the run-time verification of the correctness of running applications and mechanisms for the recovery from failures. The paper concludes with two case studies as proof of concept

Performance evaluation of bluetooth low energy for high data rate body area networks

Bluetooth Low Energy (BLE) is a promising wireless network technology, in the context of body area network (BAN) applications, to provide the required quality of service (QoS) support concerning the communication between sensor nodes placed on a user’s body and a personal device, such as a smartphone. Most previous BLE performance studies in the literature have focused primarily in networks with a single slave (point-to-point link) or traffic scenarios with relatively low data rate. However, many BAN sensors generate high data rate traffic, and several sensor nodes (slaves) may be actively sending data in the same BAN. Therefore, this work focuses on the evaluation of the suitability of BLE mainly under these conditions. Results show that, for the same traffic, the BLE protocol presents lower energy consumption and supports more sensor nodes than an alternative IEEE 802.15.4-based protocol. This study also identifies and characterizes some implementation constraints on the tested platforms that impose limits on the achievable performance.This work has been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the projects UID/EEA/04436/2013 and UID/CTM/50025/2013, and by FEDER funds through the COMPETE 2020 Programme