Estimation of Physiological Tremor from Accelerometers for Real-Time Applications

Sensors

Kalyana C. Veluvolu¹ 

[1] School of Electronics Engineering, Kyungpook National University, Daegu, Korea

关键词: tremor;    inertial sensors;    BMFLC;    Kalman filter;    real-time estimation;   

DOI  :  10.3390/s110303020

来源: mdpi

【 摘 要 】

Accurate filtering of physiological tremor is extremely important in robotics assisted surgical instruments and procedures. This paper focuses on developing single stage robust algorithms for accurate tremor filtering with accelerometers for real-time applications. Existing methods rely on estimating the tremor under the assumption that it has a single dominant frequency. Our time-frequency analysis on physiological tremor data revealed that tremor contains multiple dominant frequencies over the entire duration rather than a single dominant frequency. In this paper, the existing methods for tremor filtering are reviewed and two improved algorithms are presented. A comparative study is conducted on all the estimation methods with tremor data from microsurgeons and novice subjects under different conditions. Our results showed that the new improved algorithms performed better than the existing algorithms for tremor estimation. A procedure to separate the intended motion/drift from the tremor component is formulated.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.