Tremor suppression through impedance control.
ABSTRACT This paper presents a method for designing tremor suppression systems that achieve a specified reduction in pathological tremor power through controlling the impedance of the human-machine interface. Position, rate, and acceleration feedback are examined and two techniques for the selection of feedback coefficients are discussed. Both techniques seek a desired closed-loop human-machine frequency response and require the development of open-loop human-machine models through system identification. The design techniques were used to develop a tremor suppression system that was subsequently evaluated using human subjects. It is concluded that nonadaptive tremor suppression systems that utilize impedance control to achieve a specified reduction in tremor power can be successfully designed when accurate open-loop human-machine models are available.
Conference Paper: Neural Oscillator based Conrtol for Wrist Tremor Attenuation[Show abstract] [Hide abstract]
ABSTRACT: This paper explores the possibility of adopting neural oscillator for pathological tremor attenuation. Targeting on a specific case, we aim to suppress the tremor of the wrist joint via functional electrical stimulation (FES). A biological inspired neural oscillator is constructed that aims to generate the anti-tremor rhythmic stimulation patterns that will stimulate a pair of antagonist muscles of wrist. Surface EMG is used to entrain the neural oscillator and shape the output amplitude adaptively. The neural oscillator serves as an adaptive feedforward controller. Simulation is performed on a concrete musculoskeletal model of wrist and the results are satisfactory.Computational Cybernetics, 2007. ICCC 2007. IEEE International Conference on; 11/2007
Conference Paper: On the Assessment of an Orthosis for Pathological Tremor SuppressionAAATE; 09/2013
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ABSTRACT: Biomechanical loading, in particular, viscous loading of the upper limb has been proposed in the literature as a means for suppressing pathologic tremor. It is expected that an improvement on manipulative function can be obtained by reducing the tremorous motion associated to some neurological disorders. This article presents two non-grounded control strategies to suppress tremor by means of a orthotic (wearable) exoskeleton. These two strategies are based on biomechanical loading and notch filtering of tremor via internal forces. Both controls strategies are evaluated and validated on the robotic exoskeleton called WOTAS (wearable orthosis for tremor assessment and suppression). At the end, results obtained in the pre-clinical trials and conclusions of this study are presentedRobotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on; 06/2006
Tremor Suppression Through Impedance Control
Stephen Pledgie1, Kenneth Barner2, Sunil Agrawal3
University of Delaware
Newark, Delaware 19716
duPont Hospital for Children
Wilmington, Delaware 19899
1 Ph.D. Candidate, Biomechanics and Movement Science Program
2 Department of Computer and Electrical Engineering
3 Department of Mechanical Engineering
4 Extended Manipulation Laboratory
This paper presents a method for designing tremor suppression systems that achieve a
specified reduction in pathological tremor power through controlling the impedance of the hu-
man-machine interface. Position, rate, and acceleration feedback are examined and two tech-
niques for the selection of feedback coefficients are discussed. Both techniques seek a desired
closed-loop human-machine frequency response and require the development of open-loop hu-
man-machine models through system identification.
The design techniques were used to develop a tremor suppression system that was subse-
quently evaluated using human subjects. It is concluded that non-adaptive tremor suppression
systems that utilize impedance control to achieve a specified reduction in tremor power can be
successfully designed when accurate open-loop human-machine models are available.
Tremor is an involuntary, rhythmic, oscillatory movement of the body . Tremor
movements are typically categorized as being either physiological or pathological in origin.
Physiological tremor pervades all human movements, both voluntary and involuntary, and is
generally considered to exist as a consequence of the structure, function, and physical properties
of the neuromuscular and skeletal systems . Its frequency varies with time and lies between 8
and 12 Hz. Pathological tremor arises in cases of injury and disease and is typically of greater
amplitude and lower frequency than physiological tremor. In its mildest form, pathological
tremor impedes the activities of daily living and hinders social function. In more severe cases,
tremor occurs with sufficient amplitude to obscure all underlying voluntary activity [3, 4].
A number of digital filtering algorithms have been developed for the purpose of remov-
ing unwanted noise from signals of interest and have thus found application in tremor sup-
pression. Riviere and Thakor have investigated the application of adaptive notch filtering for the
purpose of suppressing pathological tremor noise during computer pen input [5, 6]. When a ref-
erence of the noise signal is available, adaptive finite impulse response (FIR) filters can produce
a closed-loop frequency response very similar to that of an adaptive notch filter . Gonzalez et
al. developed a digital filtering algorithm that utilized an optimal equalizer to equilibrate a
tremor contaminated input signal and a target signal that the subject attempted to follow on a
computer screen . Inherent human tracking characteristics, such as a relatively constant tem-
poral delay and over and undershoots at target trajectory extrema, were incorporated in a
“pulled-optimization” process designed to minimize a measure of performance similar to the
squared error of the tracking signal.
To improve an individual’s ability to perform manual tasks in a physical environment, it
is necessary to suppress tremor-related movements. This can be accomplished by applying re-
sistive forces to the user’s limb to attenuate movements that occur at or near tremor frequencies.
The mechanical impedance of the human-machine interface is altered due to the activity of a set
of actuators driven by a displacement feedback controller.
Several projects have investigated the application of viscous (velocity dependent) resis-
tive forces to the hand and wrist of tremor subjects for the purpose of suppressing tremor move-
ments [4, 7, 9, 10, 11]. Experimentation with varying levels of velocity dependent force feed-
back showed, qualitatively, that tremor movements could be increasingly suppressed with
increasing levels of viscous force feedback, but that concurrent resistance of voluntary move-
ment may occur.
Closed loop functional electrical stimulation (FES) has been shown to be effective in
suppressing tremor movements in patients with essential tremor, parkinsonian tremor, and cere-
bellar tremor [12, 13]. In this approach, tremorogenic muscles are stimulated out-of-phase to
cancel the tremor forces generated by affected muscles. Investigators were successful in deter-
mining closed loop configurations that attenuate 2 - 5 Hz tremor movements with minimal at-
tenuation applied to voluntary movements in the 0 – 1 Hz range.
Previous investigations into non-adaptive feedback tremor suppression systems have not
utilized quantitative performance criteria during the design of the feedback control system. They
addressed the question of whether or not velocity dependent resistive forces (damping) could ef-
fectively suppress tremor movements, but were not concerned with achieving a specified statisti-
cal reduction in the tremor.
The objective of this research was the development of a methodology that incorporates
quantitative performance criteria as well as position, rate, and acceleration feedback into the de-
sign of a non-adaptive tremor suppression system. The remainder of this paper is divided into
six sections. Section 2 presents the results of an analysis of pathological tremor movements.
The design process for the tremor suppression system is described in Section 3. Next, a method
of system identification for the human-machine system is discussed. Sections 5 and 6 present the
methods and results of an evaluation of the system. Finally, the paper is completed with a brief
discussion and concluding remarks.
2. Analysis of Tremor Movements
An investigation into the spatio-temporal characteristics of tremor movements was per-
formed to gain insight into the spatial distribution and time-frequency properties of pathological
tremor movements. Previous investigations into tremor frequency have typically applied the
Fast Fourier Transform (FFT) algorithm to a sampled data sequence to obtain information re-
garding the exact frequency content of the data. However, no information with respect to the
evolution of the frequency content over time is generated with the FFT. It is for this reason that
a time-frequency analysis of pathological tremor movements was undertaken. The spatial distri-
bution of tremor movements was also examined. A tremor suppression system could potentially
take advantage of unique temporal and spatial distributions in the tremor.
A broad set of experiments was developed to examine the pertinent tremor characteris-
tics. Five tremor subjects ages 18 to 91 participated in the study.
The tremor subjects were qualitatively categorized with respect to the severity of their
tremor. Two subjects possessed the ability to write in a somewhat legible manner and received a
low severity label. Relatively large tremor amplitude that prevented legible writing was ob-
served in two of the subjects. The remaining tremor subject exhibited high variability in tremor
amplitude and, as such, received a variable severity label. The origin of the tremor in subjects B,
D, and E was unknown because no medical diagnosis was available.
The subjects performed target-tracking tasks while seated in front of a 17” computer dis-
play. The position of an on-screen cursor was controlled by manipulating a stylus attached to the
end-effector of the PHANToM, a small robotic arm used in haptic interfaces. The PHANToM is
an excellent platform for data collection because it has less than 0.1 N of static backdrive fric-
tion, an end-effector inertia of at most 100 grams with the motors disabled, a workspace of 13
cm x 18 cm x 25 cm, and a nominal end-effector position resolution of 0.03 mm.
Table 1. Subject Information.
Figure 1. Experimental Setup.