Accurate and robust lane detection, especially the curve lane detection, is the premise of lane departure warning system and forward collision warning system. In this article, an algorithm based on improved river flow and random sample consensus is proposed to detect curve lane under challenging conditions including the dashed lane markings and vehicle occlusion. The curve lanes are modeled as hyperbola pair. To determine the coefficient of curvature, an improved river flow method is presented to search feature points in the far vision field guided by the results of detected straight lines in near vision field or the curved lines from the last frame, which can connect dashed lane markings or obscured lane markings. As a result, it is robust on dashed lane markings and vehicle occlusion conditions. Then, random sample consensus is utilized to calculate the curvature, which can eliminate noisy feature points obtained from improved river flow. The experimental results show that the proposed method can accurately detect lane under challenging conditions.
Atrial fibrillation, often called AF is considered to be the most common type of cardiac arrhythmia, which is a major healthcare challenge. Early detection of AF and the appropriate treatment is crucial if the symptoms seem to be consistent and persistent. This research work focused on the development of a heart monitoring system which could be considered as a feasible solution in early detection of potential AF in real time. The objective was to bridge the gap in the market for a low-cost, at home use, noninvasive heart health monitoring system specifically designed to periodically monitor heart health in subjects with AF disorder concerns. The main characteristic of AF disorder is the considerably higher heartbeat and the varying period between observed R waves in electrocardiogram (ECG) signals. This proposed research was conducted to develop a low cost and easy to use device that measures and analyzes the heartbeat variations, varying time period between successive R peaks of the ECG signal and compares the result with the normal heart rate and RR intervals. Upon exceeding the threshold values, this device creates an alert to notify about the possible AF detection. The prototype for this research consisted of a Bitalino ECG sensor and electrodes, an Arduino microcontroller, and a simple circuit. The data was acquired and analyzed using the Arduino software in real time. The prototype was used to analyze healthy ECG data and using the MIT-BIH database the real AF patient data was analyzed, and reasonable threshold values were found, which yielded a reasonable success rate of AF detection.
Measurement of the displacement of the center-of-pressure (COP) is an important tool used in biomechanics to assess postural stability and human balance. The goal of this research was to design and validate a low-cost portable device that can offer a quick indication of the state of postural stability and human balance related conditions. Approximate entropy (ApEn) values reflecting the amount of irregularity hiding in COP oscillations were used to calculate the index. The prototype adopted a portable design using the measurements of the load cells located at the four corners of a low-cost force platform. The test subject was asked to stand on the device in a quiet, normal, upright stance for 30 s with eyes open and subsequently for 30 s with eyes closed. Based on the COP displacement signals, the ApEn values were calculated. The results indicated that the prototype device was capable of capturing the increase in regularity of postural control in the visual-deprivation conditions. It was also able to decipher the subtle postural control differences along anterior–posterior and medial–lateral directions. The data analysis demonstrated that the prototype would enable the quantification of postural stability and thus provide a low-cost portable device to assess many conditions related to postural stability and human balance such as aging and pathologies.
Long-term structural health monitoring (SHM) systems need intelligent management of the monitoring data. By analogy with the way the human brain processes memories, we present a bio-inspired memory model (BIMM) that does not require prior knowledge of the structure parameters. The model contains three time-domain areas: a sensory memory area, a short-term memory area and a long-term memory area. First, the initial parameters of the structural state are specified to establish safety criteria. Then the large amount of monitoring data that falls within the safety limits is filtered while the data outside the safety limits are captured instantly in the sensory memory area. Second, disturbance signals are distinguished from danger signals in the short-term memory area. Finally, the stable data of the structural balance state are preserved in the long-term memory area. A strategy for priority scheduling via fuzzy c-means for the proposed model is then introduced. An experiment on bridge tower deformation demonstrates that the proposed model can be applied for real-time acquisition, limited-space storage and intelligent mining of the monitoring data in a long-term SHM system.
The effect of reservoir design and long-term use with inhaled metered dose inhaler (MDI) corticosteroids on aerosol dose availability was examined. Beclomethasone dipropionate (Vanceril) was delivered by MDI with three brands of available reservoir devices: the AeroChamber, the OptiHaler, and the Aerosol Cloud Enhancer (ACE). An in vitro lung model simulated inspiration. Long-term use was simulated by exhausting five MDI canisters of beclomethasone through each sample of reservoir tested. Each canister exhausted through a reservoir represented approximately 1 month of use with one drug. Total inhaled dose was collected at the reservoir mouthpiece and measured using a spectrophotometric assay. Dose delivery was measured before simulated use and after each MDI canister was exhausted through the reservoir. Three samples of each brand were tested with cleaning and three samples were tested without cleaning. With cleaning, the AeroChamber, OptiHaler, and ACE delivered significantly different average doses of 16.6, 10.3, and 8.7 micrograms per MDI actuation, respectively, (P = 0.0017) over time of use. Changes in dose delivery over time of use were not significant (P = 0.2011). Without cleaning, the same three brands averaged 21.1, 9.7, and 7.8 micrograms per MDI actuation, respectively, (P = 0.0019), and changes in dose delivery over time were not significant (P = 0.3265). Reservoir design can affect the delivery of an inhaled corticosteroid, although the delivery over 4 to 5 months remained stable.
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