Tremor suppression through impedance control.

Biomechanics and Movement Science Program, University of Delaware, Newark 19716, USA.
IEEE Transactions on Rehabilitation Engineering 04/2000; 8(1):53-9. DOI: 10.1109/86.830949
Source: PubMed

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.

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    ABSTRACT: Tremor is a rhythmical and involuntary oscillatory movement of a body part. Along with the social embarrassment, tremor can be debilitating to the accomplishment of daily tasks. Mechanical loading via wearable exoskeletons, orthoses, has been under investigation as a non-invasive tremor suppression alternative to medication or surgery. In this method the challenge is identifying and attenuating the tremorous motion without adding resistance to the patient's intentional motion. In this research, three different control algorithms were designed to calculate the proper suppressive force to be applied by the orthosis to the patient's arm. The first control algorithm is based on a sinusoidal model of the tremor and the controller output, the required suppressive force to attenuate tremor, is sinusoidal. The second method is using an adaptive frequency estimator to find the tremor fundamental frequency in real time. The tremor amplitude is variable and the resistive force estimated by the controller has variable amplitude and the estimated frequency of the tremor. The third method was developed by using the so called backstepping method as a nonlinear control design tool. The main part of the controller is a high-pass filter and the backstepping controller finds the required suppressive force to make the output of the high-pass filter to converge to zero. Stability and robustness of the closed-loop system against the joint parametric uncertainties were analyzed for the proposed control algorithms. An experimental setup was designed and developed to emulate the dynamics of a human arm joint with tremorous motion. A pneumatic cylinder was used to apply orthotic suppressive force. The force produced by the pneumatic cylinder was controlled using a backstepping sliding mode controller. The algorithm was implemented with a NI cRIO real-time controller for two types of tremorous motion: parkinsonian and essential. In addition to accurate tracking of the tremor frequency, the experimental results show significant tremor suppression in the range of 29.9-38.7 dB (96.8-98.8 %) at the fundamental frequency, and 6.5-14.9 dB (52.7-82.0 %) at the second harmonic.
    11/2013, Degree: PhD, Supervisor: Dr. Edmond Richer
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    ABSTRACT: Tremor is a rhythmical and involuntary oscillatory movement of a body part and it is one of the most common movement disorders. Orthotic devices have been under investigation as a noninvasive tremor suppression alternative to medication or surgery. The challenge in musculoskeletal tremor suppression is estimating and attenuating the tremor motion without impeding the patient's intentional motion. In this research a robust tremor suppression algorithm was derived for patients with pathological tremor in the upper limbs. First the motion in the tremor frequency range is estimated using a high-pass filter. Then, by applying the backstepping method the appropriate amount of torque is calculated to drive the output of the estimator toward zero. This is equivalent to an estimation of the tremor torque. It is shown that the arm/orthotic device control system is stable and the algorithm is robust despite inherent uncertainties in the open-loop human arm joint model. A human arm joint simulator, capable of emulating tremorous motion of a human arm joint was used to evaluate the proposed suppression algorithm experimentally for two types of tremor, Parkinson and essential. Experimental results show 30–42 dB (97.5–99.2%) suppression of tremor with minimal effect on the intentional motion.
    IEEE Transactions on Neural Systems and Rehabilitation Engineering 12/2013; · 3.26 Impact Factor
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    ABSTRACT: In this paper, we propose a method for identifying systems incorporating a mechanical oscillation part for a non-invasive ultrasound theragnostic system(NIUTS). The NIUTS tracks and follows movement in an area requiring treatment (renal stones, in this study) by irradiating the area with high intensity focused ultrasound (HIFU). Blur noise caused by oscillation of the mechanical system adversely affects the servo performance. To solve this problem and enhance the servo performance, it is first necessary to identify those parts of the NIUTS system that incorporate a mechanical oscillation part. Secondly, we implemented a mechanical oscillation suppression filter based on the abovementioned method for identifying the mechanical oscillation part.
    International Journal of Automation Technology (IJAT). 01/2014; 8(1):110-119.


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