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This paper presents a sensing system for the real-time monitoring of human respiration. The system is equipped with a fast response thermoresistive micro calorimetric flow (TMCF) sensor and a dedicated data processing algorithm. The TMCF sensor is designed with a proposed nonlinear sensor model and fabricated in a CMOS compatible process, which obtains a high sensitivity of 114 mV/SLM and a fast response time of less than 6 ms. By using this high-performance micro flow sensor and its proprietary data processing algorithm, critical human respiration information including respiratory rate (RR) and minute ventilation (MV) can be easily obtained. The proposed sensing system achieves a very small mean absolute error (MAE) of less than 2.7 mHz for RR, and the extracted MV is also in good agreement with the commonly reported value of 4 - 6 L/min. In addition, benefiting from the very short time constant of the developed TMCF sensor, the proposed sensing system can successfully distinguish different respiratory diseases, such as apnea, hypopnea, polypnea, etc. Therefore, this proposed human respiration monitoring system will be a promising sensing technology for respiration diagnosis in medical applications. [ABSTRACT FROM AUTHOR]

Solder bump/ball technology has been extensively applied in microelectronic packaging industry. However, the size of solder balls/bumps as well as the pitch are getting smaller and smaller, conventional inspection techniques are insufficient for diagnosis of the defect. It is indispensable to explore new methods for solder joint inspection. In this paper, a nondestructive diagnosis system based on active thermography was proposed. The test vehicles, named as SFA1 and SFA2, were excited by the laser pulse, and the consequent thermal response of the packages was captured by a thermal imager. In order to improve the signal-to-noise ratio, the polynomial fit and differential absolute contrast techniques were utilized to reconstruct the thermal images. Then, the statistical features corresponding to each solder ball were extracted from the reconstructed thermal images, and used for clustering analysis withK-means algorithm. The results show that all the solder balls were recognized accurately, which demonstrates that the intelligent system using active thermography andK-means algorithm is effective for defects inspection in microelectronic packaging industry. [ABSTRACT FROM AUTHOR]

The surface roughness in silicon direct bonding is investigated based on the contact theory of a flat plate. Two silicon wafers with the same surface roughness in a Gaussian distribution are modeled as two different surfaces in contact. One surface is a rigid flat surface, and the other is a surface having a combined Gaussian-distributed roughness. The relations among the elastic stress due to surface deformation, the adhesive force due to surface activation, and the distance due to surface separation are developed to describe silicon direct bonding. The impact of separation distance on bonding force is explained in detail. A practical surface roughness criterion considering the influence of surface activation quality on silicon bonding is proposed. The model indicates that the bonding ability of silicon depends on the surface roughness and the quality of surface activation. It explains the threshold of surface roughness for silicon direct bonding and describes the experimental data well. Thus, the model can provide a helpful basis for the optimization of the silicon direct bonding process. [ABSTRACT FROM PUBLISHER]