KEYWORDS: Sensors, Control systems, Gait analysis, Fuzzy systems, Fuzzy logic, Algorithm development, Data modeling, Databases, Data acquisition, Data conversion
An in-socket sensory system enables the monitoring of transfemoral amputee movement for a microprocessor-controlled prosthetic leg. User movement recognition from an in-socket sensor allows a powered prosthetic leg to actively mimic healthy ambulation, thereby reducing an amputee’s metabolic energy consumption. This study established an adaptive neurofuzzy inference system (ANFIS)-based control input framework from an in-socket sensor signal for gait phase classification to derive user intention as read by in-socket sensor arrays. Particular gait phase recognition was mapped with the cadence and torque control output of a knee joint actuator. The control input framework was validated with 30 experimental gait samples of the in-socket sensory signal of a transfemoral amputee walking at fluctuating speeds of 0 to 2 km · h − 1. The physical simulation of the controller presented a realistic simulation of the actuated knee joint in terms of a knee mechanism with 95% to 99% accuracy of knee cadence and 80% to 90% accuracy of torque compared with those of normal gait. The ANFIS system successfully detected the seven gait phases based on the amputee’s in-socket sensor signals and assigned accurate knee joint torque and cadence values as output.
A registration method to fuse two-dimensional (2-D) echocardiography images with cardiac computed tomography (CT) volume is presented. The method consists of two major procedures: temporal and spatial registrations. In temporal registration, the echocardiography frames at similar cardiac phases as the CT volume were interpolated based on electrocardiogram signal information, and the noise of the echocardiography image was reduced using the speckle reducing anisotropic diffusion technique. For spatial registration, an intensity-based normalized mutual information method was applied with a pattern search optimization algorithm to produce an interpolated cardiac CT image. The proposed registration framework does not require optical tracking information. Dice coefficient and Hausdorff distance for the left atrium assessments were 0.87±0.04 and 1.23±0.32 mm, respectively; for left ventricle, they were 0.82±0.07 and 1.14±0.18 mm, respectively. There was no significant difference in the mitral valve annulus diameter measurement between the manually and automatically registered CT images. The transformation parameters showed small deviations (≤1.14 mm deviation in translation and <2 deg for rotation) between manual and automatic registrations. The proposed method aids the physician in diagnosing mitral valve disease as well as provides surgical guidance during the treatment procedure.
The problem of eliminating character-resembling blobs on a detected region in the plate detection stage of an automated license plate recognition system is addressed. The proposed method amplifies the slight differences between the noncharacter blobs (anomalies) and the character blobs (true signal) to enhance the tractability. This method postulates on two propositions: (1) the anomalies are usually located around the true signal and the suspected anomalies and (2) blobs should be given less emphasis in computing a reference point. The first proposition is based on prior knowledge and observation; the second proposition is based on the fact that a reference point that takes anomalies into account is contaminated and thus misleading. The gist of the method mainly focuses on the methodology to emphasize the blobs differently in accordance to their location in computing the reference point that approximates the representative value of true signal properties more accurately, thus giving the effect of amplifying the slight differences. The performance of the method is evaluated on both its capability and consistency in solving certain types of anomalies.
The leadframe fabrication process normally involves additional thin-metal layer plating on the bulk copper substrate surface for wire bonding purposes. Silver, tin, and copper flakes are commonly adopted as plating materials. It is critical to assess the density of the plated metal layer, and in particular to look for porosity or voids underneath the layer, which may reduce the reliability during high-temperature stress. A fast, reliable inspection technique is needed to assess the porosity or void weakness. To this end, the characteristics of x-rays generated from bulk samples were examined using an energy-dispersive x-ray (EDX) detector to examine the porosity percentage. Monte Carlo modeling was integrated with Castaing’s formula to verify the integrity of the experimental data. Samples with different porosity percentages were considered to test the correlation between the intensity of the collected x-ray signal and the material density. To further verify the integrity of the model, conventional cross-sectional samples were also taken to observe the porosity percentage using Image J software measurement. A breakthrough in bulk substrate assessment was achieved by applying EDX for the first time to nonelemental analysis. The experimental data showed that the EDX features were not only useful for elemental analysis, but also applicable to thin-film metal layer thickness measurement and bulk material density determination. A detailed experiment was conducted using EDX to assess the plating metal layer and bulk material porosity.
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