Prediction of pathological tremor using adaptive multiple oscillators linear combiner. (May 2016)

• Record Type: Journal Article
• Authors: Xiao, Feiyun; Gao, Yongsheng; Wang, Shengxin; Zhao, Jie
• Is Part Of: Biomedical signal processing and control. Volume 27(2016)
• Page Start: 77
• Page End: 86
• Publication Date: 2016-05
• Subjects: Prediction -- AMOLC -- Pathological tremor -- Oscillator; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2016.01.006
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Pathological tremor signal prediction algorithm AMOLC based on Hopf oscillator is proposed. The optimum parameters of AMOLC are obtained by building experimental platform which can generates simulated tremor motion. The corresponding optimal parameters are verified by actual pathological tremor signals. The AMOLC is zero phase lag and it can be used in real-time application. Abstract: A new pathological tremor signal prediction algorithm for tremor suppression, the adaptive multiple oscillators linear combiner (AMOLC) based on Hopf oscillator, is proposed in this paper. This method can be used to predict pathological tremor signal with high accuracy and well robustness. An experimental platform is built to simulate the tremor motion to obtain the optimum parameters of AMOLC algorithm. Furthermore, AMOLC algorithm is applied to tremor prediction for actual pathological tremor patients. Results verify that chosen model parameters indeed improve the prediction performance which meets the demand of tremor suppression with high accuracy and well robustness. A comparison of computational complexity is conducted between some existing prediction methods and AMOLC.