Abstract
Abstract. Sensor-based gesture interaction technology has been widely adopted in consumer electronics. Nevertheless, bias, drift, and noise existing in sensor signals are difficult to eliminate, and accurate movement trajectory information is still needed to achieve flexible interaction application. This paper presents micro-electro-mechanical system (MEMS) motion sensor information processing algorithms designed on a gesture interaction system which integrates multiple low-cost MEMS motion sensors with ZigBee wireless technology to support embodied communication while acting together with machines. Sensor signal processing systems mainly solve noise removal, signal smoothing, gravity influence separation, coordinate system conversion, and position information retrieval. The attitude information which is an important movement parameter and required by position estimation is calculated with a quaternion-based extended Kalman filter (EKF). The effectiveness of the movement information retrieval of this gesture interface is verified by experiments and test analysis, both in static and moving cases. In the end, related applications of the described sensor information processing are discussed.
Highlights
Intelligent platforms, such as tablets, personal computers, personal digital assistants, gaming systems, and smartphones, have become ever more popularly used consumer electronics
For the purpose of understanding the reason why different coordinate systems exist in micro-electro-mechanical system (MEMS) sensor signal processing and movement information analysis, inertial navigation system (INS) and inertial measurement unit (IMU) coordinate systems are illustrated in the contents below
In this paper, advanced movement information processing and retrieval algorithms which are achieved by signal processing and information fusion techniques, and applied in a gesture interface with MEMS and IMU technologies, are explained
Summary
Intelligent platforms, such as tablets, personal computers, personal digital assistants, gaming systems, and smartphones, have become ever more popularly used consumer electronics. Many application paradigms require the usage of surfaces, cameras, sensor bars, or tethering, thereby restricting these applications, including more facility provision, observation and interaction coverage range limitation, and more complicated algorithms. Compared with these sensor systems mentioned above, low-cost inertial sensors based on micro-electro-mechanical system (MEMS) technology, which are made using the techniques of microfabrication, enhance the motion and tracking abilities for gesture user interfaces because of more real-time motion information provision, high performance, ruggedness, and low power (Shaeffer, 2013).
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