Real-Time Step Length Estimation in Indoor and Outdoor Scenarios.

In this paper, human step length is estimated based on the wireless channel properties and the received signal strength indicator (RSSI) method. The path loss between two ankles, called the on-ankle path loss, is converted from the RSSI, which is measured by our developed wearable hardware in indoor and outdoor ambulation scenarios. The human walking step length is estimated by a reliable range of RSSI values. The upper threshold and the lower threshold of this range are determined experimentally. This paper advances our previous step length measurement technique by proposing a novel exponential weighted moving average (EWMA) algorithm to update the upper and lower thresholds, and thus the step length estimation, recursively. The EWMA algorithm allows our measurement technique to process each shorter subset of the dataset, called a time window, and estimate the step length, rather than having to process the whole dataset at a time. The step length is periodically updated on the fly when the time window is "sliding" forwards. Thus, the EWMA algorithm facilitates the step length estimation in real-time. The impact of the EWMA parameter is analysed, and the optimal parameter is discovered for different experimental scenarios. Our experiments show that the EWMA algorithm could achieve comparable accuracy as our previously proposed technique with errors as small as 3.02% and 0.30% for the indoor and outdoor scenarios, respectively, while the processing time required to output an estimation of the step length could be significantly shortened by 53.96% and 60% for the indoor walking and outdoor walking, respectively.

Step Length Estimation Using the RSSI Method in Walking and Jogging Scenarios.

In this paper, human step length was estimated based on wireless channel properties and the received signal strength indicator (RSSI) method. Path loss between two ankles of the person under test was converted from the RSSI, which was measured using our developed wearable transceivers with embedded micro-controllers in four scenarios, namely indoor walking, outdoor walking, indoor jogging, and outdoor jogging. For brevity, we call it on-ankle path loss. The histogram of the on-ankle path loss showed clearly that there were two humps, where the second hump was closely related to the maximum path loss, which, in turn, corresponded to the step length. This histogram can be well approximated by a two-term Gaussian fitting curve model. Based on the histogram of the experimental data and the two-term Gaussian fitting curve, we propose a novel filtering technique to filter out the path loss outliers, which helps set up the upper and lower thresholds of the path loss values used for the step length estimation. In particular, the upper threshold was found to be on the right side of the second Gaussian hump, and its value was a function of the mean value and the standard deviation of the second Gaussian hump. Meanwhile, the lower threshold lied on the left side of the second hump and was determined at the point where the survival rate of the measured data fell to 0.68, i.e., the cumulative distribution function (CDF) approached 0.32. The experimental data showed that the proposed filtering technique resulted in high accuracy in step length estimation with errors of only 10.15 mm for the indoor walking, 4.40 mm for the indoor jogging, 4.81 mm for the outdoor walking, and 10.84 mm for the outdoor jogging scenarios, respectively.

Step Length Measurements Using the Received Signal Strength Indicator.

In this paper, portable transceivers with micro-controllers and radio frequency modules are developed to measure the received signal strength, path loss, and thus the distance between the human ankles for both indoor and outdoor environments. By comparing the experimental results and the theoretical model, a path loss model between transceivers attached to the subject's ankles is derived. With the developed experimental path loss model, the step length can be measured relatively accurately, despite the imperfections of hardware devices, with the distance errors of a centimeter level. This paper, therefore, helps address the need for a distance measurement method that has fewer health concerns, is accurate, and is less affected by occlusions and confined spaces. Our findings possibly lay a foundation for some important applications, such as the measurement of gait speed and localization of the human body parts, in wireless body area networks.

Advances in Wearable Sensors: Signalling the Provenance of Garments Using Radio Frequency Watermarks.

There is a significant nascent market for ethically produced products with enormous commercial potential around the world. A reliable method to signal the provenance of products is therefore critical for industry, given that competition based on price is not a viable strategy. The ability to trace and signal ethical treatment of animals is also of significant value to textiles manufactures. The efficacy of such a method can be measured with respect to the cost of implementation, scalability, and the difficulty of counterfeiting. The key to traceability is to win the trust of the consumer about the veracity of this information. Wearable sensors make it possible to monitor and improve the management of traceability and/or provenance. In this paper, we introduce a method for signalling the provenance of garments using radio frequency watermarks. The proposed model consists of two levels of authentication that are easy to use by legitimate vendors, but extremely difficult to imitate or hack, because the watermark is built-in and based on the radiation signature of electroactive materials.

Electrically Conducting Hydrogel Graphene Nanocomposite Biofibers for Biomedical Applications.

Conductive biomaterials have recently gained much attention, specifically owing to their application for electrical stimulation of electrically excitable cells. Herein, flexible, electrically conducting, robust fibers composed of both an alginate biopolymer and graphene components have been produced using a wet-spinning process. These nanocomposite fibers showed better mechanical, electrical, and electrochemical properties than did single fibers that were made solely from alginate. Furthermore, with the aim of evaluating the response of biological entities to these novel nanocomposite biofibers, in vitro studies were carried out using C2C12 myoblast cell lines. The obtained results from in vitro studies indicated that the developed electrically conducting biofibers are biocompatible to living cells. The developed hybrid conductive biofibers are likely to find applications as 3D scaffolding materials for tissue engineering applications.

Performance Evaluation of Non-GPS Based Localization Techniques under Shadowing Effects.

Non-GPS localization has gained much interest from researchers and industries recently because GPS might fail to meet the accuracy requirements in shadowing environments. The two most common range-based non-GPS localization methods, namely Received Signal Strength Indicator (RSSI) and Angle-of-Arrival (AOA), have been intensively mentioned in the literature over the last decade. However, an in-depth analysis of the weighted combination methods of AOA and RSSI in shadowing environments is still missing in the state-of-the-art. This paper proposes several weighted combinations of the two RSSI and AOA components in the form of pAOA + qRSSI, devises the mathematical model for analyzing shadowing effects, and evaluates these weighted combination localization methods from both accuracy and precision perspectives. Our simulations show that increasing the number of anchors does not necessarily improve the precision and accuracy, that the AOA component is less susceptible to shadowing than the RSSI one, and that increasing the weight of the AOA component and reducing that of the RSSI component help improve the accuracy and precision at high Signal-to-Noise Ratios (SNRs). This observation suggests that some power control algorithm could be used to increase automatically the transmitted power when the channel experiences large shadowing to maintain a high SNR, thus guaranteeing both accuracy and precision of the weighted combination localization techniques.

Joint Transmission Power Control and Relay Cooperation for WBAN Systems.

Improving transmission reliability is a crucial challenge for Wireless Body Area Networks (WBANs) because of the instability of channel conditions and the stringent Packet Loss Ratio (PLR) requirement for many WBANs applications. On the other hand, limited by the size of WBAN nodes, the energy consumption of WBAN nodes should be minimized. In this paper, we jointly consider transmission power control, dynamic slot scheduling and two-hop cooperative mechanism and propose an Autocorrelation-based Adaptive Transmission (AAT) scheme that achieves a better trade-off between transmission reliability and energy consumption for WBAN systems. The new scheme is designed to be compatible with IEEE 802.15.6. We evaluated the performance of the newly proposed scheme by importing the real channel datasets into our simulation model. Simulation results demonstrate that the AAT method can effectively improve the transmission reliability while reducing the energy consumption. We also provide the performance evaluation from three perspectives, namely packet error ratio, energy consumption and energy efficiency, and provide recommendations on the application of the two-hop cooperative mechanism associated with the proposed AAT in the contexts of WBANs.

Optimization of Camera Arrangement Using Correspondence Field to Improve Depth Estimation.

Stereo matching algorithms attempt to estimate depth from the images obtained by two cameras. In most cases, the arrangement of cameras (their locations and orientations with respect to the scene) is determined based on human experience. In this paper, it is shown that the camera arrangement can be optimized using the concept of correspondence field (CF) for better acquisition of depth. Specifically, this paper demonstrates the relationship between the CF of a pair of cameras and depth estimation accuracy and presents a method to optimize their arrangement based on the gradient of the CF. The experimental results show that a pair of cameras optimized by the proposed method can improve the accuracy of depth estimation by as much as 30% compared with the conventional camera arrangements.

Preparation and characterization of hybrid conducting polymer-carbon nanotube yarn.

Hybrid polypyrrole (PPy)-multi walled carbon nanotube (MWNT) yarns were obtained by chemical and electrochemical polymerization of pyrrole on the surface and within the porous interior of twisted MWNT yarns. The material was characterized by scanning electron microscopy, electrochemical, mechanical and electrical measurements. It was found that the hybrid PPy-MWNT yarns possessed significantly higher mechanical strength (over 740 MPa) and Young's modulus (over 54 GPa) than the pristine MWNT yarn. The hybrid yarns also exhibited substantially higher electrical conductivity (over 235 S cm(-1)) and their specific capacitance was found to be in excess of 60 F g(-1). Measurements of temperature dependence of electrical conductivity revealed semiconducting behaviour, with a large increase of band gap near 100 K. The collected low temperature data are in good agreement with a three-dimensional variable range hopping model (3D-VRH). The improved durability of the yarns is important for electrical applications. The composite yarns can be produced in commercial quantities and used for applications where the electrical conductivity and good mechanical properties are of primary importance.