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

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

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

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

Stretchable Dual-Capacitor Multi-Sensor for Touch-Curvature-Pressure-Strain Sensing

We introduce a new type of multi-functional capacitive sensor that can sense several different external stimuli. It is fabricated only with polydimethylsiloxane (PDMS) films and silver nanowire electrodes by using selective oxygen plasma treatment method without photolithography and etching processes. Differently from the conventional single-capacitor multi-functional sensors, our new multifunctional sensor is composed of two vertically-stacked capacitors (dual-capacitor). The unique dual-capacitor structure can detect the type and strength of external stimuli including curvature, pressure, strain, and touch with clear distinction, and it can also detect the surface-normal directionality of curvature, pressure, and touch. Meanwhile, the conventional single-capacitor sensor has ambiguity in distinguishing curvature and pressure and it can detect only the strength of external stimulus. The type, directionality, and strength of external stimulus can be determined based on the relative capacitance changes of the two stacked capacitors. Additionally, the logical flow reflected on a tree structure with its branches reaching the direction and strength of the corresponding external stimulus unambiguously is devised. This logical flow can be readily implemented in the sensor driving circuit if the dual-capacitor sensor is commercialized actually in the future

The Smartphone Brain Scanner: A Portable Real-Time Neuroimaging System

Combining low cost wireless EEG sensors with smartphones offers novel opportunities for mobile brain imaging in an everyday context. We present a framework for building multi-platform, portable EEG applications with real-time 3D source reconstruction. The system - Smartphone Brain Scanner - combines an off-the-shelf neuroheadset or EEG cap with a smartphone or tablet, and as such represents the first fully mobile system for real-time 3D EEG imaging. We discuss the benefits and challenges of a fully portable system, including technical limitations as well as real-time reconstruction of 3D images of brain activity. We present examples of the brain activity captured in a simple experiment involving imagined finger tapping, showing that the acquired signal in a relevant brain region is similar to that obtained with standard EEG lab equipment. Although the quality of the signal in a mobile solution using a off-the-shelf consumer neuroheadset is lower compared to that obtained using high density standard EEG equipment, we propose that mobile application development may offset the disadvantages and provide completely new opportunities for neuroimaging in natural settings

Remote heart rate monitoring - Assessment of the Facereader rPPg by Noldus

Remote photoplethysmography (rPPG) allows contactless monitoring of human cardiac activity through a video camera. In this study, we assessed the accuracy and precision for heart rate measurements of the only consumer product available on the market, namely the Facereader™ rPPG by Noldus, with respect to a gold standard electrocardiograph. Twenty-four healthy participants were asked to sit in front of a computer screen and alternate two periods of rest with two stress tests (i.e. Go/No-Go task), while their heart rate was simultaneously acquired for 20 minutes using the ECG criterion measure and the Facereader™ rPPG. Results show that the Facereader™ rPPG tends to overestimate lower heart rates and underestimate higher heart rates compared to the ECG. The Facereader™ rPPG revealed a mean bias of 9.8 bpm, the 95% limits of agreement (LoA) ranged from almost -30 up to +50 bpm. These results suggest that whilst the rPPG Facereader™ technology has potential for contactless heart rate monitoring, its predictions are inaccurate for higher heart rates, with unacceptable precision across the entire range, rendering its estimates unreliable for monitoring individuals