Sensors2014, 14(4), 6819-6827; doi:10.3390/s140406819 - published online 15 April 2014 Show/Hide Abstract
Abstract: Freezing of gait (FOG) is a common symptom in Parkinsonism, which affects the gait pattern and is associated to a fall risk. Automatized FOG episode detection would allow systematic assessment of patient state and objective evaluation of the clinical effects of treatments. Techniques have been proposed in the literature to identify FOG episodes based on the frequency properties of inertial sensor signals. Our objective here is to adapt and extend these FOG detectors in order to include other associated gait pattern changes, like festination. The proposed approach is based on a single wireless inertial sensor placed on the patient’s lower limbs. The preliminary experimental results show that existing frequency-based freezing detectors are not sufficient to detect all FOG and festination episodes and that the observation of some gait parameters such as stride length and cadence are valuable inputs to anticipate the occurrence of upcoming FOG events.
Sensors2014, 14(4), 6806-6818; doi:10.3390/s140406806 - published online 14 April 2014 Show/Hide Abstract
Abstract: Multiwall carbon nanotubes (MWCNTs) were easily and efficiently decorated with Pd nanoparticles through a vapor-phase impregnation-decomposition method starting from palladium acetylacetonates. The sensor device consisted on a film of sensitive material (MWCNTs-Pd) deposited by drop coating on platinum interdigitated electrodes on a SiO2 substrate. The sensor exhibited a resistance change to ozone (O3) with a response time of 60 s at different temperatures and the capability of detecting concentrations up to 20 ppb. The sensor shows the best response when exposed to O3 at 120 °C. The device shows a very reproducible sensor performance, with high repeatability, full recovery and efficient response.
Sensors2014, 14(4), 6797-6805; doi:10.3390/s140406797 - published online 14 April 2014 Show/Hide Abstract
Abstract: A three-magnet array unilateral NMR sensor with a homogeneous sensitive spot was employed for assessing aging of the turbine oils used in two different power stations. The Carr-Purcell-Meiboom-Gill (CPMG) sequence and Inversion Recovery-prepared CPMG were employed for measuring the 1H-NMR transverse and longitudinal relaxation times of turbine oils with different service status. Two signal components with different lifetimes were obtained by processing the transverse relaxation curves with a numeric program based on the Inverse Laplace Transformation. The long lifetime components of the transverse relaxation time T2eff and longitudinal relaxation time T1 were chosen to monitor the hydraulic fluid aging. The results demonstrate that an increase of the service time of the turbine oils clearly results in a decrease of T2eff,long and T1,long. This indicates that the T2eff,long and T1,long relaxation times, obtained from the unilateral magnetic resonance measurements, can be applied as indices for degradation of the hydraulic fluid in power station turbines.
Sensors2014, 14(4), 6788-6796; doi:10.3390/s140406788 - published online 14 April 2014 Show/Hide Abstract
Abstract: Quorum sensing (QS) is a mechanism adopted by bacteria to regulate expression of genes according to population density. N-acylhomoserine lactones (AHLs) are a type of QS signalling molecules commonly found in Gram-negative bacteria which have been reported to play a role in microbial spoilage of foods and pathogenesis. In this study, we isolated an AHL-producing Hafnia alvei strain (FB1) from spherical fish pastes. Analysis via high resolution triple quadrupole liquid chromatography/mass spectrometry (LC/MS) on extracts from the spent supernatant of H. alvei FB1 revealed the existence of two short chain AHLs: N-(3-oxohexanoyl) homoserine lactone (3-oxo-C6-HSL) and N-(3-oxo- octanoyl) homoserine lactone (3-oxo-C8-HSL). To our knowledge, this is the first report of the production of AHLs, especially 3-oxo-C8-HSL, by H. alvei.
Sensors2014, 14(4), 6758-6787; doi:10.3390/s140406758 - published online 11 April 2014 Show/Hide Abstract
Abstract: This study was motivated by the need to improve densification of Global Horizontal Irradiance (GHI) observations, increasing the number of surface weather stations that observe it, using sensors with a sub-hour periodicity and examining the methods of spatial GHI estimation (by interpolation) with that periodicity in other locations. The aim of the present research project is to analyze the goodness of 15-minute GHI spatial estimations for five methods in the territory of Spain (three geo-statistical interpolation methods, one deterministic method and the HelioSat2 method, which is based on satellite images). The research concludes that, when the work area has adequate station density, the best method for estimating GHI every 15 min is Regression Kriging interpolation using GHI estimated from satellite images as one of the input variables. On the contrary, when station density is low, the best method is estimating GHI directly from satellite images. A comparison between the GHI observed by volunteer stations and the estimation model applied concludes that 67% of the volunteer stations analyzed present values within the margin of error (average of ±2 standard deviations).
Sensors2014, 14(4), 6734-6757; doi:10.3390/s140406734 - published online 11 April 2014 Show/Hide Abstract
Abstract: The future of robotics predicts that robots will integrate themselves more every day with human beings and their environments. To achieve this integration, robots need to acquire information about the environment and its objects. There is a big need for algorithms to provide robots with these sort of skills, from the location where objects are needed to accomplish a task up to where these objects are considered as information about the environment. This paper presents a way to provide mobile robots with the ability-skill to detect objets for semantic navigation. This paper aims to use current trends in robotics and at the same time, that can be exported to other platforms. Two methods to detect objects are proposed, contour detection and a descriptor based technique, and both of them are combined to overcome their respective limitations. Finally, the code is tested on a real robot, to prove its accuracy and efficiency.