Power-Generation Optimization Based on Piezoelectric Ceramic Deformation for Energy Harvesting Application with Renewable Energy

Along with the increase in renewable energy, research on energy harvesting combined with piezoelectric energy is being conducted. However, it is difficult to predict the power generation of combined harvesting because there is no data on the power generation by a single piezoelectric material. Before predicting the corresponding power generation and efficiency, it is necessary to quantify the power generation by a single piezoelectric material alone. In this study, the generated power is measured based on three parameters (size of the piezoelectric ceramic, depth of compression, and speed of compression) that contribute to the deformation of a single PZT (Lead zirconate titanate)-based piezoelectric element. The generated power was analyzed by comparing with the corresponding parameters. The analysis results are as follows: (i) considering the difference between the size of the piezoelectric ceramic and the generated power, 20 mm was the most efficient piezoelectric ceramic size, (ii) considering the case of piezoelectric ceramics sized 14 mm, the generated power continued to increase with the increase in the compression depth of the piezoelectric ceramic, and (iii) For piezoelectric ceramics of all diameters, the longer the depth of deformation, the shorter the frequency, and depending on the depth of deformation, there is a specific frequency at which the charging power is maximum. Based on the findings of this study, PZT-based elements can be applied to cases that receive indirect force, including vibration energy and wave energy. In addition, the power generation of a PZT-based element can be predicted, and efficient conditions can be set for maximum power generation

Parametric Studies of Melt Electrospinning Poly ?(caprolactone) Fibers for Tissue Engineering Applications

The process of electrospinning has received remarkable amount of attention as this technique can be used to fabricate suitable scaffolds for cells. In order to control morphology of scaffold, parametric studies are necessary in customized melt electrospinning. In this study, we demonstrate that fiber diameter could be controlled by customized nozzle and parameters which are temperature, voltage, and distance influence to fiber diameter. Moreover, we culture and seed murine CE3 stem cells derived from D3 embryonic stem cell line on fabricated scaffolds. Overall, scaffold controlled by parameter studies holds a promising strategy for superb cell attachment and proliferation

Gait Disorder Detection and Classification Method Using Inertia Measurement Unit for Augmented Feedback Training in Wearable Devices

Parkinson’s disease (PD) is a common neurodegenerative disease, one of the symptoms of which is a gait disorder, which decreases gait speed and cadence. Recently, augmented feedback training has been considered to achieve effective physical rehabilitation. Therefore, we have devised a numerical modeling process and algorithm for gait detection and classification (GDC) that actively utilizes augmented feedback training. The numerical model converted each joint angle into a magnitude of acceleration (MoA) and a Z-axis angular velocity (ZAV) parameter. Subsequently, we confirmed the validity of both the GDC numerical modeling and algorithm. As a result, a higher gait detection and classification rate (GDCR) could be observed at a higher gait speed and lower acceleration threshold (AT) and gyroscopic threshold (GT). However, the pattern of the GDCR was ambiguous if the patient was affected by a gait disorder compared to a normal user. To utilize the relationships between the GDCR, AT, GT, and gait speed, we controlled the GDCR by using AT and GT as inputs, which we found to be a reasonable methodology. Moreover, the GDC algorithm could distinguish between normal people and people who suffered from gait disorders. Consequently, the GDC method could be used for rehabilitation and gait evaluation

Ground Force Precision Calibration Method for Customized Piezoresistance Sensing Flexible Force Measurement Mat.

A force plate is mainly used in biomechanics; it aims to measure the ground reaction force in a persons walking or standing position. In this study, a large-area force mat of the piezoresistance sensing type was developed, and a deep-learning-based weight measurement calibration method was applied to solve the problem in which measurements are not normalized because of physical limitations in hardware and signal processing. The test set was composed of the values measured at each point by weight and the value of the center of the pressure variable, and the measured value was predicted using a deep neural network (DNN) regression model. The calibration verification results show that the average weight errors range from a minimum of 0.06% to a maximum of 3.334%. This is simpler than the previous method, which directly measures the ratio of the resistance value to the measured weight of each sensor and derives an equation

Quantitative Analysis of Postural Balance in Faller and Nonfaller Patients with Parkinson’s Disease

Background. Postural instability has been identified as a fall risk factor with a significant impact on the quality of life of patients with Parkinson’s disease (PD). The aim of this study was to compare the center of pressure (COP) between faller and nonfaller patients with PD during static standing. Methods. Thirty-two faller patients and 32 nonfaller patients with PD participated in this study. All patients performed the static balance test on a force plate. COP data were recorded during quiet standing. Mean distance, sway area, mean velocity, mean frequency, and peak power were derived from the COP data. Statistical analysis was performed using independent t-tests to compare faller and nonfaller patients. Results. Fallers presented a greater average distance, wider sway area, faster average speed, and greater peak power than nonfallers (p  0.05). Conclusions. Although falls occur during dynamic activities, our study demonstrated that even a safe and simple static postural balance test could significantly differentiate between faller and nonfaller patients. Thus, these results suggest that quantitatively assessed static postural sway variables would be useful for distinguishing prospective fallers among PD patients

Design and fabrication of auxetic PCL nanofiber membranes for biomedical applications

The main objective of this study was to fabricate poly (e-caprolactone) (PCL)-based auxetic nanofiber membranes and characterize them for their mechanical and physicochemical properties. As a first step, the PCL nanofibers were fabricated by electrospinning with two different thicknesses of 40 pm (called PCL thin membrane) and 180 pm (called PCL thick membrane). In the second step, they were tailored into auxetic patterns using femtosecond laser cut technique. The physicochemical and mechanical properties of the auxetic nanofiber membranes were studied and compared with the conventional electrospun PCL nanofibers (non-auxetic nano fiber membranes) as a control. The results showed that there were no significant changes observed among them in terms of their chemical functionality and thermal property. However, there was a notable difference observed in the mechanical properties. For instance, the thin auxetic nanofiber membrane showed the magnitude of elongation almost ten times higher than the control, which clearly demonstrates the high flexibility of auxetic nanofiber membranes. This is because that the auxetic nanofiber membranes have lesser rigidity than the control nanofibers under the same load which could be due to the rotational motion of the auxetic structures. The major finding of this study is that the auxetic PCL nanofiber membranes are highly flexible (10-fold higher elongation capacity than the conventional PCL nanofibers) and have tunable mechanical properties. Therefore, the auxetic PCL nanofiber membranes may serve as a potent material in various biomedical applications, in particular, tissue engineering where scaffolds with mechanical cues play a major role