The Virtual QA process predicts IMRT passing rates with a high likelihood, allows the detection of failures due to setup errors, and it is sensitive enough to detect small differences between matched Linacs.

In this study, we design and present the novel wearable system with the interactive posture caption and recognition functions based on the non-vision over the ZigBee wireless sensor network (ZigBee-WSN). There are two type sensors, 3-axis accelerometer and clip type, to be employed in our wearable system. These sensors are arranged on user's four limbs such that the posture information can be gathered by them. Then, the posture information is transmitted to the data-controlling center over ZigBee-WSN. Finally, this center can analyze and distinguish various postures by our proposed algorithm through the friend user's interface to express. Our presented wearable system can distinguish out 28 kinds of hand postures and 13 kinds of leg postures altogether. Moreover, under our presented ZigBee-WSN system with small size, low-power consumption, and high-reliability characteristics, the data-controlling center can simultaneously tele-monitor the real-time body interactive postures of 8 persons, when the transmitting distance is less than 18 M and the package correct transmitted rate is more than 97.5%.

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The motivation of this research is to improve the ability of ambulation for people with a certain degree of disability. The control of the wheelchair is using two tilt sensors as an input-controlling module. One of the tilt sensors detects the anterior/posterior tilting of the head and moves the wheelchair forward/backward, the other distinguishes the left/right swing of the head. In order to increase the safety of this system, the M3S protocol established by the European Commission is also applied to this research. The system based on M3S protocol has the advantage of real-time signal transmission and emergent status monitoring for SCI patients with C2-C4 level.

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