Multistep Prediction of Physiological Tremor for Surgical Robotics Applications

Accurate canceling of physiological tremor is extremely important in robotics-assisted surgical instruments/procedures. The performance of robotics-based hand-held surgical devices degrades in real time due to the presence of phase delay in sensors (hardware) and filtering (software) processes. Effe...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2013-11, Vol.60 (11), p.3074-3082
Main Authors: Veluvolu, Kalyana C., Tatinati, Sivanagaraja, Hong, Sun-Mog, Ang, Wei Tech
Format: Article
Language:English
Subjects:
Accelerometry - instrumentation
Accelerometry - methods
Adaptation models
Algorithms
Autoregressive (AR)
band limited multiple linear Fourier combiner (BMFLC)
Fourier Analysis
Hand - physiopathology
Humans
inertial sensors
Kalman filter
Models, Statistical
multistep prediction
physiological motion
Physiology
Real-time systems
Robotics - instrumentation
Surgery, Computer-Assisted - instrumentation
Surgery, Computer-Assisted - methods
Surgical robots
Task Performance and Analysis
tremor
Tremor - physiopathology
Tremors
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Summary:Accurate canceling of physiological tremor is extremely important in robotics-assisted surgical instruments/procedures. The performance of robotics-based hand-held surgical devices degrades in real time due to the presence of phase delay in sensors (hardware) and filtering (software) processes. Effective tremor compensation requires zero-phase lag in filtering process so that the filtered tremor signal can be used to regenerate an opposing motion in real time. Delay as small as 20 ms degrades the performance of human-machine interference. To overcome this phase delay, we employ multistep prediction in this paper. Combined with the existing tremor estimation methods, the procedure improves the overall accuracy by 60% for tremor estimation compared to single-step prediction methods in the presence of phase delay. Experimental results with developed methods for 1-DOF tremor estimation highlight the improvement.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2013.2264546