Abstract
This paper presents a stable double-wireless-wearable-band platform that can detect hand gestures. The real-time monitoring and control system utilizes an MCU processor, a wireless transceiver, and a commercial three-axis, digital-output MEMS accelerometer. To detect the user’s hand movements, a 3D virtual environment is created via a double-wearable-band controller. Compared with a single wearable band, double wearable bands can identify more gestures with improved stability. Performances in terms of control and detection are discussed in detail. This research development allows the user to specify desired two-hand postures using the multi-sensor information fusion technique for controlling a variety of robotic devices. In the system, the defined two-hand postures also allow the user to add freestyle control to various applications, which bridge the communication gap between humans and the systems. Moreover, the integration of the action recognition algorithm of the combination of two bracelets and the server brings out a real-time approach to analyze and make decisions based on the users’ data. Therefore, the system can call for help in a timely manner under critical conditions.
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Acknowledgment
The research work was supported by the National Natural Science Foundation of China (61300043, 61373156 and 91438121), and the Science and Technology Commission of Shanghai Municipality (14DZ2260800).
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Xu, W., Liu, Y., Yang, Y., Ning, X., Chu, T., Song, H. (2017). An Optimized Fusion Method for Double-Wearable-Wireless-Band Platform on Cloud-Health Application. In: Chen, G., Shen, H., Chen, M. (eds) Parallel Architecture, Algorithm and Programming. PAAP 2017. Communications in Computer and Information Science, vol 729. Springer, Singapore. https://doi.org/10.1007/978-981-10-6442-5_20
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DOI: https://doi.org/10.1007/978-981-10-6442-5_20
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