Double adaptive bandlimited multiple Fourier linear combiner for real-time estimation/filtering of physiological tremor

Veluvolu, Kalyana C.; Latt, Win Tun; Ang, Wei Tech

doi:10.1016/j.bspc.2009.06.001

Cited by 56 publications

(44 citation statements)

References 13 publications

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“…This significantly improves accuracy around tiny anatomy such as retinal vessels and reduces trauma to surrounding tissue caused by tremor. In the future, we plan on analyzing lowerlevel current control on the piezoelectric motors, examining vibration estimations of the sensors, and incorporating tremor prediction algorithms [18][19][20]. …”

Section: Discussionmentioning

confidence: 99%

State estimation and feedforward tremor suppression for a handheld micromanipulator with a Kalman filter

Becker¹,

MacLachlan

Riviere³

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Active compensation of physiological tremor for handheld micromanipulators depends on fast control and actuation responses. Because of real-world latencies, real-time compensation is usually not completely effective at eliminating unwanted hand motion. By modeling tremor, more effective cancellation is possible by anticipating future hand motion. We propose a feedforward control strategy that utilizes tremor velocity from a state-estimating Kalman filter. We demonstrate that estimating hand motion in a feedforward controller overcomes real-world latencies in micromanipulator actuation. In hold-still tasks with a fully handheld micromanipulator, the proposed feedforward approach improves tremor rejection by over 50%.

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Section: Discussionmentioning

confidence: 99%

State estimation and feedforward tremor suppression for a handheld micromanipulator with a Kalman filter

Becker¹,

MacLachlan

Riviere³

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…The algorithm first analyzes the individual's hand motion and extracts the involuntary and voluntary components. For this purpose, a low-pass Band-limited Multiple Fourier Linear Combiner (BMFLC) filter (see [29][30][31][32]) is implemented to extract the involuntary component of the hand motion, which has a highfrequency nature in comparing with voluntary component of the motion [24,25]. The BMFLC filter is an adaptive technique which is utilized to extract involuntary movements while introducing minimal filtering latency into the interaction.…”

Section: Components and The Design Of Actionsmentioning

confidence: 99%

“…The BMFLC filter is an adaptive technique which is utilized to extract involuntary movements while introducing minimal filtering latency into the interaction. The design of the filter can be found in [29][30][31][32].…”

Section: Components and The Design Of Actionsmentioning

confidence: 99%

“…the BMFLC technique. BMFLC is designed to track multiple harmonics of a signal [29][30][31] and showed higher accuracy compared to conventional FLC-based filters [30]. In the literature, BMFLC filtering has also been used for extracting physiological hand tremor of surgeons [36][37][38] and recently has shown good performance in extracting pathological involuntary motions [33].…”

Section: Components and The Design Of Actionsmentioning

confidence: 99%

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Telerobotics-Assisted Platform for Enhancing Interaction with Physical Environments for People Living with Cerebral Palsy

Atashzar

Jafari

Shahbazi

et al. 2017

J. Med. Robot. Res.

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In this paper, the design and implementation of a new telerobotics-assisted platform is proposed for individuals who have cerebral palsy (CP). The main objective of the proposed assistive system is to modulate capabilities of individuals through the proposed telerobotic medium and to enhance their control over interaction with objects in a real physical environment. The proposed platform is motivated by evidence showing that lack of interaction with real environments can develop further secondary sensorimotor and cognitive issues for people who grow up with CP. The proposed telerobotic system assists individuals by (a) mapping their limited but convenient motion range to a larger workspace needed for task performance in the real environment, (b) transferring only the voluntary components of the hand motion to the task-side robot to perform tasks and (c) kinaesthetically dissipating the energy of their involuntary motions using a viscous force field implemented in high frequency domain. Consequently, using the proposed system, an individual who has CP will be capable of providing smooth and large-scale motions and presenting enhanced coordination while performing tasks, even if they naturally have involuntary movements, limited range of motion and/or coordination deficits. The proposed architecture is implemented and initially tested for one nondisabled participant. Afterwards, the system is evaluated for one individual who lives with CP. The resulting quality of motion and task performance are analyzed through a designed clinical protocol. The results confirm the functionality of the proposed assistive platform in enhancing the capabilities of individuals who live with CP in interacting with physical environments.

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“…It is also need to notice that the noise structure in the EEG signal remains unknown, thus by using a quantified value of the noise can naturally add uncertainty into the system. By incorporating a time varying linear model with a fixed frequency band, this paper aims to develop a alternative spectral estimation method based on band-limited multiple Fourier linear combiner (BMFLC) [8] [9]. The original BMFLC adopts a truncated Fourier series as the model and estimated the Fourier coefficients by least mean squares (LMS) adaptive algorithm.…”

Section: Introductionmentioning

confidence: 99%

Estimation of EEG during Voluntary Movement by Using Kalman Smoother Based BMFLC

Wang

Lim

Seo

2011

2011 5th International Conference on Bioinformatics and Biomedical Engineering

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The electroencephalogram(EEG) is a useful tool to let researchers understand the brain states. Frequency analysis of EEG signal during different mental tasks received significant attention. The band-limited Fourier linear combiner (BMFLC) is a truncated Fourier series model for EEG signal. In this paper a time varying state-space model of BMFLC have been proposed. By using Kalman smoother to update the adaptive weights in the BMFLC, an accurate signal tracking performance is obtained. By using the adaptive weights of BMFLC estimated from Kalman smoother, an accurate time frequency decomposition can also be achieved. Since the EEG is non-stationarity signal, the time-frequency analysis is essential to analyze brain states during different mental tasks. A study is conducted on 3 subjects to identify the subject specified frequency band during the voluntary movement.

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Double adaptive bandlimited multiple Fourier linear combiner for real-time estimation/filtering of physiological tremor

Cited by 56 publications

References 13 publications

State estimation and feedforward tremor suppression for a handheld micromanipulator with a Kalman filter

State estimation and feedforward tremor suppression for a handheld micromanipulator with a Kalman filter

Telerobotics-Assisted Platform for Enhancing Interaction with Physical Environments for People Living with Cerebral Palsy

Estimation of EEG during Voluntary Movement by Using Kalman Smoother Based BMFLC

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