title: Noise Reduction for a MEMS-Gyroscope-Based Head Mouse.
abstract: In this paper, four different signal processing algorithms which can be applied to reduce the noise from a MEMS-gyroscope-based computer head mouse are presented. MEMS-gyroscopes are small, light, cheap and widely used in many electrical products. MultiPos, a MEMS-gyroscope-based computer head mouse system was designed for persons with movement disorders. Noise such as physiological tremor and electrical noise is a common problem for the MultiPos system. In this study four different signal processing algorithms were applied and evaluated by simulation in MATLAB and implementation in a dsPIC, with aim to minimize the noise in MultiPos. The algorithms were low-pass filter, Least Mean Square (LMS) algorithm, Kalman filter and Weighted Fourier Linear Combiner (WFLC) algorithm. Comparisons and system tests show that these signal processing algorithms can be used to improve the MultiPos system. The WFLC algorithm was found the best method for noise reduction in the application of a MEMS-gyroscope-based head mouse.
authors.affiliation: School of Innovation, Design and Engineering, Mälardalen University, Sweden.
authors.forename: Jiaying
authors.initials: J
authors.lastname: Du
authors.affiliation: Motion Control i Västerås AB, Sweden.
authors.forename: Christer
authors.initials: C
authors.lastname: Gerdtman
authors.affiliation: School of Innovation, Design and Engineering, Mälardalen University, Sweden.
authors.forename: Maria
authors.initials: M
authors.lastname: Lindén
mesh_terms: D000465:Algorithms; D016287:Computer Peripherals; D055617:Micro-Electrical-Mechanical Systems / Q000295:instrumentation*; D009069:Movement Disorders / Q000534:rehabilitation*; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio