Estimation of Physiological Tremor from Accelerometers for Real-Time Applications

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.

[1]  W. T. Latt,et al.  Bandlimited Multiple Fourier Linear Combiner for Real-time Tremor Compensation , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[2]  竹安 数博,et al.  Time series analysis and its applications , 2007 .

[3]  Nitish V. Thakor,et al.  Adaptive Fourier modeling for quantification of tremor 1 Funding provided by National Institute on Disability and Rehabilitation Research (grant number H133G30064). 1 , 1997, Journal of Neuroscience Methods.

[4]  W. T. Ang,et al.  Estimation and filtering of physiological tremor for real‐time compensation in surgical robotics applications , 2010, The international journal of medical robotics + computer assisted surgery : MRCAS.

[5]  A. V. Balakrishnan,et al.  Kalman Filtering Theory , 1984 .

[6]  Ali Saberi,et al.  Filtering theory , 2007 .

[7]  W.T. Latt,et al.  System to Assess Accuracy of Micromanipulation , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[8]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[9]  Cameron N. Riviere,et al.  An Active Hand-Held Instrument for Enhanced Microsurgical Accuracy , 2000, MICCAI.

[10]  Cameron N. Riviere,et al.  Modeling and canceling tremor in human-machine interfaces , 1996 .

[11]  Jing Zhang,et al.  DSP controller based signal processing of physiological hand tremor , 2005, Proceedings of the 2005, American Control Conference, 2005..

[12]  José Luis Pons Rovira,et al.  Real-Time Estimation of Pathological Tremor Parameters from Gyroscope Data , 2010, Sensors.

[13]  Petros G. Voulgaris,et al.  On optimal ℓ∞ to ℓ∞ filtering , 1995, Autom..

[14]  G. Deuschl,et al.  The pathophysiology of tremor , 2001, Muscle & nerve.

[15]  Cameron N. Riviere,et al.  Toward active tremor canceling in handheld microsurgical instruments , 2003, IEEE Trans. Robotics Autom..

[16]  Jing Zhang,et al.  Real-time modeling and prediction of physiological hand tremor , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[17]  John A. Crowe,et al.  Numerical double integration of acceleration measurements in noise , 2004 .

[18]  H. S. Wolff,et al.  iRun: Horizontal and Vertical Shape of a Region-Based Graph Compression , 2022, Sensors.

[19]  U-Xuan Tan,et al.  Design and Calibration of an Optical Micro Motion Sensing System for Micromanipulation Tasks , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[20]  M. Brin,et al.  Consensus Statement of the Movement Disorder Society on Tremor , 2008, Movement disorders : official journal of the Movement Disorder Society.

[21]  Mika P. Tarvainen,et al.  Estimation of nonstationary EEG with Kalman smoother approach: an application to event-related synchronization (ERS) , 2004, IEEE Transactions on Biomedical Engineering.

[22]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[23]  U-Xuan Tan,et al.  Estimating Displacement of Periodic Motion With Inertial Sensors , 2008, IEEE Sensors Journal.

[24]  Nitish V. Thakor,et al.  An adaptive estimation of periodic signals using a Fourier linear combiner , 1994, IEEE Trans. Signal Process..

[25]  N.V. Thakor,et al.  Adaptive cancelling of physiological tremor for improved precision in microsurgery , 1998, IEEE Transactions on Biomedical Engineering.

[26]  U-Xuan Tan,et al.  Physiological tremor sensing using only accelerometers for real-time compensation , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.

[27]  E. Rocon,et al.  Design and Validation of a Rehabilitation Robotic Exoskeleton for Tremor Assessment and Suppression , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[28]  T. Kailath,et al.  A state-space approach to adaptive RLS filtering , 1994, IEEE Signal Processing Magazine.

[29]  J. Matsumoto,et al.  Time-frequency analysis of tremors. , 1998, Brain : a journal of neurology.

[30]  A. W. M. van den Enden,et al.  Discrete Time Signal Processing , 1989 .

[31]  Zhi-Hong Mao,et al.  Extraction of Sources of Tremor in Hand Movements of Patients With Movement Disorders , 2009, IEEE Transactions on Information Technology in Biomedicine.

[32]  S. Thomas Alexander,et al.  Adaptive Signal Processing , 1986, Texts and Monographs in Computer Science.

[33]  Tariq Rahman,et al.  Optimal digital filtering for tremor suppression , 2000, IEEE Transactions on Biomedical Engineering.