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The geometry of an inductively coupled plasma (ICP) etcher is usually considered to be an important factor for determining both plasma and process uniformity over a large wafer. During the past few decades, these parameters were determined by the "trial and error" method, resulting in wastes of time and funds. In this paper, a new approach of regression orthogonal design with plasma simulation experiments is proposed to investigate the sensitivity of the structural parameters on the uniformity of plasma characteristics. The tool for simulating plasma is CFD-ACE+, which is commercial multi-physical modeling software that has been proven to be accurate for plasma simulation. The simulated experimental results are analyzed to get a regression equation on three structural parameters. Through this equation, engineers can compute the uniformity of the electron number density rapidly without modeling by CFD-ACE+. An optimization performed at the end produces good results.

An organism grows from very small to the whole body, while an engineering product is assembled from elements. An organism is formed autonomously and adaptable to his/her/its environment, while an engineering product can only execute very limited actions. The formation of a product determines its functionality. Nature is the best teacher for learning how structures are formed for specific functionality. This paper compares the design process with the developmental process of embryo and proposes a qualitative development framework that simulates the gene transcription and translation in biology. The key step in design is transforming behaviors to structures. This is a process from information to the form and it bears some similarity with the process from DNA to the protein in embryogenesis. Three basic steps are required from DNA to the protein: gene transcription, transport and protein synthesis, which is named as gene expression. Key mechanisms contributing to this transformation process are investigated and a qualitative development framework are constructed for a growth design process. Simple examples are presented for illustration of proposed methods.Copyright © 2015 by ASME

Robot-assisted therapy has been proved more effective for treating neurological conditions than conventional therapy. It is known that early training can enhance motor learning and improve functional abilities more than chronicphase training. But there is almost no such lower-limb rehabilitation robot for patients within three months after stroke in clinical. This article introduces such a new robot for acute and subacute stroke patients, which can increase joint flexibility, prevent muscle disuse atrophy, help neural plasticity, enhance motor learning and improve functional abilities by providing patients simulating-gait-training. We did randomized controlled trials including total 8 subjects (4 healthy, 4 patients). At the end of rehabilitation training, the patients’ conditions were assessed by nursing and training staff using the Fugl-Meyer Assessment score. After four weeks of robot-assisted therapy, experimental results showed that the patients’ score and their activities of daily living improved a lot. It is proved that the lower-limb rehabilitation robot for acute and subacute patients is effective.

It is generally accepted that early treatment is an effective way in improving body’s function of the stroke patients. This paper reviews the background of the rehabilitation theory and some typical products of lower limb rehabilitation robots. Lower limb rehabilitation robots have been drawn into rehabilitation training. Researchers have done large amounts of rehabilitation training experiments based on these rehabilitation robots. This paper reviews some representative articles. Abundant clinical trials show that robot-assisted rehabilitation therapy is more effective than conventional therapy in Functional Ambulatory Capacity (FAC), walking speed, step length, etc. However, there are few lower limb rehabilitation robots directing at patients in early stage (the first 3 months after illness) in the domestic and international markets. Therefore, lower limb rehabilitation robot for acute and subacute stroke patients is a promising research area in the future.

Stroke patients may have limb paralysis or disturbance of consciousness. In the rehabilitation system, the main task of human-computer interaction focused on visual interaction. In this study, it has been confirmed that the visual feedback system in the rehabilitation has played an important role. This robotic system combines a dual video to meet training needs. In the experiment, trainees trains in accordance with the planned trajectory. Through the combined visual system, motion analysis feeds back to trainees in real time. iIn comparing to traditional training without feedback, the combination of Visual feedback can enhance the trainee's consciousness of balance, train the neural sensitivity of the brain and nerve system, and can restore the movement ability.

Quantitative evaluation for estimating motor function is a prerequisite for clinical application of rehabilitation robot. The current clinical evaluations, such as Fugl-Meyer assessment, still have some deficiency. The study provided an innovative evaluation method, which contrasted the physiological character of impaired limb with the contralateral upper limb of post stroke hemiplegic patients, and investigate the comparability of surface Electromyography (sEMG) between patients and healthy persons during robot-assisted motor recovery training possess similar track and equivalent velocity. There is much comparability of sEMG characteristic in healthy limb of patients compare with healthy person, yet less comparability exist in the impaired limb. The results in the study imply that the method depend on contralateral limb sEMG characteristic have potential capacity in clinical quantitative evaluation of rehabilitation and may competent to associate with other physiological character.

A convenient designing tool is developed aiming at providing a Thinking Assistant for innovative and creative designing. The tool is easy to develop by a designer himself following his own thought pattern. Neural networks are used to develop potential new structure patterns by changing connection properties of substructures. Design examples are provided to validate the method.

Our goal is to apply robotics and automation technology to assist, quantify, enhance, and verify neuro-rehabilitation. In this paper a novel robot neuro-rehabilitation for upper limb, with many merits, is developed. Mechanism and control of the robot are introduced in detail. By a clinical trial involving 30 stroke patients with three months at Rehabilitation Center of China, some results are obtained 1) robot-aided therapy does not have adverse effects, 2) patients can accept the procedure, 3) the therapy may reduce muscular tension, and 4) manipulation of the impaired upper limb may influence brain recovery. Some new ideas are also presented to make rehabilitation therapy more effectively. These ideas will be helpful to further quicken the development of the robot neuro-rehabilitation.

Joint clearance is one of important factors which affect motion precision of machines. In this paper the mathematical model of a new-type joint, tripod-ball sliding joint, is established, and the new concepts of basal system and active system are put forward. Based on the mode-change criterion established here, the consistent equations of motion in full-scale are derived by using Kane method. The dynamic behavior of the crank-slider mechanism with clearance in the tripod-ball sliding joint is investigated. The results including motion error and impact acceleration are obtained and the advantage of this new joint is shown.

In order to estimate the effect of neural rehabilitation robot for improving the upper extremity motor function, 23 hemiplegia patients who are BrunnstromTII at least receive clinical rehabilitation training by the upper extremity compound movements rehabilitation training robot. The assistance models of the neural rehabilitation robot and the programming of the clinical rehabilitation training are studied in this dissertation. The clinical assessment results make clear that after a period of rehabilitation treatment, the function of most patients, which could be assessed by Fugl-Meyer method, improved to a certain extent, and the rehabilitation effect is better than the traditional rehabilitation training. The outcome indicates that, the upper extremity compound movements rehabilitation training robot has a significant application prospect in clinical rehabilitation.

In order to improve the effect of robotic rehabilitation therapy, we need to find out which elements of robot training influence it. Our aim is to analysis the relation between the patients-active force and the effect. This paper reviews a clinical therapy involving 6 hemiplegia patients with the upper extremity compound movements rehabilitation training robot developed by Tsinghua University, Beijing. By processing the collected data, we get the evidence that the elevated scores after training and the patients' active force are high correlated. The larger the patient's active force, the better the training effect.