Falls are among the main causes of injuries in elderly individuals. Balance and mobility impairment are major indicators of fall risk in this group. The objective of this research was to develop a fall risk feedback system that operates in real time using an inertial sensor-based instrumented cane. Based on inertial sensor data, the proposed system estimates the kinematics (contact phase and orientation) of the cane. First, the contact phase of the cane was estimated by a convolutional neural network. Next, various algorithms for the cane orientation estimation were compared and validated using an optical motion capture system. The proposed cane contact phase prediction model achieved higher accuracy than the previous models. In the cane orientation estimation, the Madgwick filter yielded the best results overall. Finally, the proposed system was able to estimate both the contact phase and orientation in real time in a single-board computer.
Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.
Dielectrophoresis (DEP) is a label-free, accurate, fast, low-cost diagnostic technique that uses the principles of polarization and the motion of bioparticles in applied electric fields. This technique has been proven to be beneficial in various fields, including environmental research, polymer research, biosensors, microfluidics, medicine and diagnostics. Biomedical science research is one of the major research areas that could potentially benefit from DEP technology for diverse applications. Nevertheless, many medical science research investigations have yet to benefit from the possibilities offered by DEP. This paper critically reviews the fundamentals, recent progress, current challenges, future directions and potential applications of research investigations in the medical sciences utilizing DEP technique. This review will also act as a guide and reference for medical researchers and scientists to explore and utilize the DEP technique in their research fields.
Automatic data annotation eliminates most of the challenges we faced due to the manual methods of annotating sensor data. It significantly improves users’ experience during sensing activities since their active involvement in the labeling process is reduced. An unsupervised learning technique such as clustering can be used to automatically annotate sensor data. However, the lingering issue with clustering is the validation of generated clusters. In this paper, we adopted the k-means clustering algorithm for annotating unlabeled sensor data for the purpose of detecting sensitive location information of mobile crowd sensing users. Furthermore, we proposed a cluster validation index for the k-means algorithm, which is based on Multiple Pair-Frequency. Thereafter, we trained three classifiers (Support Vector Machine, K-Nearest Neighbor, and Naïve Bayes) using cluster labels generated from the k-means clustering algorithm. The accuracy, precision, and recall of these classifiers were evaluated during the classification of “non-sensitive” and “sensitive” data from motion and location sensors. Very high accuracy scores were recorded from Support Vector Machine and K-Nearest Neighbor classifiers while a fairly high accuracy score was recorded from the Naïve Bayes classifier. With the hybridized machine learning (unsupervised and supervised) technique presented in this paper, unlabeled sensor data was automatically annotated and then classified.
This study presents a new technique to improve the indoor localization of a mobile node by utilizing a Zigbee-based received-signal-strength indicator (RSSI) and odometry. As both methods suffer from their own limitations, this work contributes to a novel methodological framework in which coordinates of the mobile node can more accurately be predicted by improving the path-loss propagation model and optimizing the weighting parameter for each localization technique via a convex search. A self-adaptive filtering approach is also proposed which autonomously optimizes the weighting parameter during the target node's translational and rotational motions, thus resulting in an efficient localization scheme with less computational effort. Several real-time experiments consisting of four different trajectories with different number of straight paths and curves were carried out to validate the proposed methods. Both temporal and spatial analyses demonstrate that when odometry data and RSSI values are available, the proposed methods provide significant improvements on localization performance over existing approaches.
Bridges are designed to withstand different types of loads, including dead, live, environmental, and occasional loads during their service period. Moving vehicles are the main source of the applied live load on bridges. The applied load to highway bridges depends on several traffic parameters such as weight of vehicles, axle load, configuration of axles, position of vehicles on the bridge, number of vehicles, direction, and vehicle's speed. The estimation of traffic loadings on bridges are generally notional and, consequently, can be excessively conservative. Hence, accurate prediction of the in-service performance of a bridge structure is very desirable and great savings can be achieved through the accurate assessment of the applied traffic load in existing bridges. In this paper, a review is conducted on conventional vehicle-based health monitoring methods used for bridges. Vision-based, weigh in motion (WIM), bridge weigh in motion (BWIM), drive-by and vehicle bridge interaction (VBI)-based models are the methods that are generally used in the structural health monitoring (SHM) of bridges. The performance of vehicle-assisted methods is studied and suggestions for future work in this area are addressed, including alleviating the downsides of each approach to disentangle the complexities, and adopting intelligent and autonomous vehicle-assisted methods for health monitoring of bridges.
Piezoelectric energy harvesting systems have been drawing the attention of the research community over recent years due to their potential for recharging/replacing batteries embedded in low-power-consuming smart electronic devices and wireless sensor networks. However, conventional linear piezoelectric energy harvesters (PEH) are often not a viable solution in such advanced practices, as they suffer from a narrow operating bandwidth, having a single resonance peak present in the frequency spectrum and very low voltage generation, which limits their ability to function as a standalone energy harvester. Generally, the most common PEH is the conventional cantilever beam harvester (CBH) attached with a piezoelectric patch and a proof mass. This study investigated a novel multimode harvester design named the arc-shaped branch beam harvester (ASBBH), which combined the concepts of the curved beam and branch beam to improve the energy-harvesting capability of PEH in ultra-low-frequency applications, in particular, human motion. The key objectives of the study were to broaden the operating bandwidth and enhance the harvester's effectiveness in terms of voltage and power generation. The ASBBH was first studied using the finite element method (FEM) to understand the operating bandwidth of the harvester. Then, the ASBBH was experimentally assessed using a mechanical shaker and real-life human motion as excitation sources. It was found that ASBBH achieved six natural frequencies within the ultra-low frequency range (<10 Hz), in comparison with only one natural frequency achieved by CBH within the same frequency range. The proposed design significantly broadened the operating bandwidth, favouring ultra-low-frequency-based human motion applications. In addition, the proposed harvester achieved an average output power of 427 μW at its first resonance frequency under 0.5 g acceleration. The overall results of the study demonstrated that the ASBBH design can achieve a broader operating bandwidth and significantly higher effectiveness, in comparison with CBH.
A modified smoothed particle hydrodynamic (MSPH) computational technique was utilized to simulate molten particle motion and infiltration speed on multi-scale analysis levels. The radial velocity and velocity gradient of molten alumina, iron infiltration in the TiC product and solidification rate, were predicted during centrifugal self-propagating high-temperature synthesis (SHS) simulation, which assisted the coating process by MSPH. The effects of particle size and temperature on infiltration and solidification of iron and alumina were mainly investigated. The obtained results were validated with experimental microstructure evidence. The simulation model successfully describes the magnitude of iron and alumina diffusion in a centrifugal thermite SHS and Ti + C hybrid reaction under centrifugal acceleration.
The paper deals with a stagnation-point boundary layer flow towards a permeable stretching/shrinking sheet in a nanofluid where the flow and the sheet are not aligned. We used the Buongiorno model that is based on the Brownian diffusion and thermophoresis to describe the nanofluid in this problem. The main purpose of the present paper is to examine whether the non-alignment function has the effect on the problem considered when the fluid suction and injection are imposed. It is interesting to note that the non-alignment function can ruin the symmetry of the flows and prominent in the shrinking sheet. The fluid suction will reduce the impact of the non-alignment function of the stagnation flow and the stretching/shrinking sheet but at the same time increasing the velocity profiles and the shear stress at the surface. Furthermore, the effects of the pertinent parameters such as the Brownian motion, thermophoresis, Lewis number and the suction/injection on the flow and heat transfer characteristics are also taken into consideration. The numerical results are shown in the tables and the figures. It is worth mentioning that dual solutions are found to exist for the shrinking sheet.
A caustic vector vortex optical field is experimentally generated and demonstrated by a caustic-based approach. The desired caustic with arbitrary acceleration trajectories, as well as the structured states of polarization (SoP) and vortex orders located in different positions in the field cross-section, is generated by imposing the corresponding spatial phase function in a vector vortex optical field. Our study reveals that different spin and orbital angular momentum flux distributions (including opposite directions) in different positions in the cross-section of a caustic vector vortex optical field can be dynamically managed during propagation by intentionally choosing the initial polarization and vortex topological charges, as a result of the modulation of the caustic phase. We find that the SoP in the field cross-section rotates during propagation due to the existence of the vortex. The unique structured feature of the caustic vector vortex optical field opens the possibility of multi-manipulation of optical angular momentum fluxes and SoP, leading to more complex manipulation of the optical field scenarios. Thus this approach further expands the functionality of an optical system.
This study aimed to quantify the association of four anthropometric parameters of the human arm, namely, the arm circumference (CA), arm length (LA), skinfold thickness (ST) and inter-sensor distance (ISD), with amplitude (RMS) and crosstalk (CT) of mechanomyography (MMG) signals. Twenty-five young, healthy, male participants were recruited to perform forearm flexion, pronation and supination torque tasks. Three accelerometers were employed to record the MMG signals from the biceps brachii (BB), brachialis (BRA) and brachioradialis (BRD) at 80% maximal voluntary contraction (MVC). Signal RMS was used to quantify the amplitude of the MMG signals from a muscle, and cross-correlation coefficients were used to quantify the magnitude of the CT among muscle pairs (BB & BRA, BRA & BRD, and BB & BRD). For all investigated muscles and pairs, RMS and CT showed negligible to low negative correlations with CA, LA and ISD (r = -0.0001--0.4611), and negligible to moderate positive correlations with ST (r = 0.004-0.511). However, almost all of these correlations were statistically insignificant (p > 0.05). These findings suggest that RMS and CT values for the elbow flexor muscles recorded and quantified using accelerometers appear invariant to anthropometric parameters.
Changes in the retinal size of stationary objects provide a cue to the observer's motion in the environment: Increases indicate the observer's forward motion, and decreases backward motion. In this study, a series of images each comprising a pair of pine-tree figures were translated into auditory modality using sensory substitution software. Resulting auditory stimuli were presented in an ascending sequence (i.e. increasing in intensity and bandwidth compatible with forward motion), descending sequence (i.e. decreasing in intensity and bandwidth compatible with backward motion), or in a scrambled order. During the presentation of stimuli, blindfolded participants estimated the lengths of wooden sticks by haptics. Results showed that those exposed to the stimuli compatible with forward motion underestimated the lengths of the sticks. This consistent underestimation may share some aspects with visual size-contrast effects such as the Ebbinghaus illusion. In contrast, participants in the other two conditions did not show such magnitude of error in size estimation; which is consistent with the "adaptive perceptual bias" towards acoustic increases in intensity and bandwidth. In sum, we report a novel cross-modal size-contrast illusion, which reveals that auditory motion cues compatible with listeners' forward motion modulate haptic representations of object size.
It is a theoretical exportation for mass transpiration and thermal transportation of Casson nanofluid over an extending cylindrical surface. The Stagnation point flow through porous matrix is influenced by magnetic field of uniform strength. Appropriate similarity functions are availed to yield the transmuted system of leading differential equations. Existence for the solution of momentum equation is proved for various values of Casson parameter [Formula: see text], magnetic parameter M, porosity parameter [Formula: see text] and Reynolds number Re in two situations of mass transpiration (suction/injuction). The core interest for this study aroused to address some analytical aspects. Therefore, existence of solution is proved and uniqueness of this results is discussed with evaluation of bounds for existence of solution. Results for skin friction factor are established to attain accuracy for large injection values. Thermal and concentration profiles are delineated numerically by applying Runge-Kutta method and shooting technique. The flow speed retards against M, [Formula: see text] and [Formula: see text] for both situations of mass injection and suction. The thermal boundary layer improves with Brownian and thermopherotic diffusions.
This study investigates thermal natural convective heat transfer in a nanofluid filled-non-Darcian porous and wavy-walled domain under the local thermal non-equilibrium condition. The considered cavity has corrugated and cold vertical walls and insulated horizontal walls except the heated part positioned at the bottom wall. The transport equations in their non-dimensional model are numerically solved based on the Galerkin finite-element discretization technique. The dimensionless governing parameters of the present work are the nanoparticle in volume concentration, the Darcy number, number of undulations, modified heat conductivity ratio, dimensionless heated part length, and location. Comparisons with other published theoretical and experimental results show good agreement with the present outcomes. The findings indicate that the heater length, its position, and the waves number on the side vertical walls as well as the nanoparticles concentration can be the control parameters for free convective motion and heat transport within the wavy cavity.
The multi-scale and nonlinear nature of the ocean dynamics dramatically affects the spreading of matter, like pollutants, marine litter, etc., of physical and chemical seawater properties, and the biological connectivity inside and among different basins. Based on the Finite-Scale Lyapunov Exponent analysis of the largest available near-surface Lagrangian data set from the Global Drifter Program, our results show that, despite the large variety of flow features, relative dispersion can ultimately be described by a few parameters common to all ocean sub-basins, at least in terms of order of magnitude. This provides valuable information to undertake Lagrangian dispersion studies by means of models and/or of observational data. Moreover, our results show that the relative dispersion rates measured at submesoscale are significantly higher than for large-scale dynamics. Auxiliary analysis of high resolution GPS-tracked drifter hourly data as well as of the drogued/undrogued status of the buoys is provided in support of our conclusions. A possible application of our study, concerning reverse drifter motion and error growth analysis, is proposed relatively to the case of the missing Malaysia Airlines MH370 aircraft.
This study deals with the steady laminar slip flow of an incompressible Newtonian fluid in a non-uniform permeable channel under the influence of transverse magnetic field. The reabsorption through the wall is accounted for by considering flux as a function of downstream distance. The non-linear coupled partial differential equations of motion are first transformed into a single fourth order partial differential equation and then solved analytically using Adomain decomposition method. Effects of pertinent parameters on different flow properties are discussed by plotting graphs. Results reveal that magnetic field considerably influences the behavior of flow.
In the present research, aluminum oxide- water (Al2O3-H2O) nanofluid free convection due to magnetic forces through a permeable cubic domain with ellipse shaped obstacle has been reported. Lattice Boltzmann approach is involved to depict the impacts of magnetic, buoyancy forces and permeability on nanoparticles migration. To predict properties of Al2O3- water nanofluid, Brownian motion impact has been involved. Outcomes revels that considering higher magnetic forces results in greater conduction mechanism. Permeability can enhance the temperature gradient.
Although global demand for palm oil has been increasing, most activities in the oil palm plantations still rely heavily on manual labour, which includes fresh fruit bunch (FFB) harvesting and loose fruit (LF) collection. As a result, harvesters and/or collectors face ergonomic risks resulting in musculoskeletal disorder (MSD) due to awkward, extreme and repetitive posture during their daily work routines. Traditionally, indirect approaches were adopted to assess these risks using a survey or manual visual observations. In this study, a direct measurement approach was performed using Inertial Measurement Units, and surface Electromyography sensors. The instruments were attached to different body parts of the plantation workers to quantify their muscle activities and assess the ergonomics risks during FFB harvesting and LF collection. The results revealed that the workers generally displayed poor and discomfort posture in both activities. Biceps, multifidus and longissimus muscles were found to be heavily used during FFB harvesting. Longissimus, iliocostalis, and multifidus muscles were the most used muscles during LF collection. These findings can be beneficial in the design of various assistive tools which could improve workers' posture, reduce the risk of injury and MSD, and potentially improve their overall productivity and quality of life.
Nowadays, development of cable-stayed bridges is increasing around the world. The mitigation of seismic forces to these bridges are obligatory to prevent damages or failure of its structural members. Herein, this paper aimed to determine the near-fault ground motion effect on an existing cablestayed bridge equipped with lead-rubber bearing. In this context, Shipshaw cable-stayed bridge is selected as the case study. The selected bridge has a span of 183.2 m composite deck and 43 m height of steel tower. 2D finite element models of the non-isolated and base isolated bridges are modelled by using SAP2000. Three different near-fault ground motions which are Tabas 1978, Cape Mendocino 1992 and Kobe 1995 were subjected to the 2D FEM models in order to determine the seismic behaviour of the bridge. The near-fault ground motions were applied to the bridge in the longitudinal direction. Nonlinear dynamic analysis was performed to determine the dynamic responses of the bridge. Comparison of dynamic response of nonisolated and base isolated bridge under three different near-fault ground motions were conducted. The results obtained from numerical analyses of the bridge showed that the isolation system lengthened the period of bridge and minimised deck displacement, base shear and base moment of the bridge. It is concluded that the isolation system significantly reduced the destructive effects of near-fault ground motions on the bridge.
OBJECTIVE: To assess the efficacy of oral palm vitamin E in reducing symptoms of patients with osteoarthritis (OA) of the knee compared to oral glucosamine sulphate.
METHODS: This open study was carried out at the Universiti Kebangsaan Malaysia Medical Center, Kuala Lumpur, Malaysia between March 2006 and November 2007. Seventy-nine patients were recruited to receive either 1.5 g oral glucosamine sulphate or 400 mg oral palm vitamin E for 6 months. Symptoms were assessed using the Western Ontario and McMaster Universities (WOMAC) osteoarthritis index and visual analogue scale (VAS).
RESULTS: Sixty-four patients completed the trial (vitamin E n=33, glucosamine sulfate n=31). After 6 months of treatment, both groups showed a significant improvement in WOMAC scale and significant reduction in the VAS score during standing and walking. There was no significant difference in WOMAC scale and VAS score between the 2 groups. Except for mild allergic reaction and abdominal discomfort in one patient, there were no other serious adverse effects reported. Serum malondialdehyde was significantly higher in the glucosamine group compared to palm vitamin E treated group at the end of the study. Serum of vitamin E was significantly higher in the palm vitamin E group compared to glucosamine.
CONCLUSION: The finding of this study suggests that oral palm vitamin E in a dose of 400 mg taken daily has a potential role in reducing symptoms of patients with OA of the knee. It may be just as effective as glucosamine sulphate in reducing the symptoms and free from serious side effects. Further study is required to ascertain the mechanism of action beside its antioxidant effect.
Matched MeSH terms: Range of Motion, Articular/physiology