Abstract

Background and objectivesHuman motor control (HMC) has been hypothesized to involve state estimation, prediction and feedback control to overcome noise, delays and disturbances. However, the nature of communication between these processes, and, in particular, whether it is continuous or intermittent, is still an open issue. Depending on the nature of communication, the resulting control is referred to as continuous control (CC) or intermittent control (IC). While standard HMC theories are based on CC, IC has been argued to be more viable since it reduces computational and communication burden and agrees better with some experimental results. However, to be a feasible model for HMC, IC has to cope well with inaccurately modeled plants, which are common in daily life, as when lifting lighter than expected loads. While IC may involve event-driven triggering, it is generally assumed that refractory mechanisms in HMC set a lower limit on the interval between triggers. Hence, we focus on periodic IC, which addresses this lower limit and also facilitates analysis.Theoretical methods and resultsTheoretical stability criteria are derived for CC and IC of inaccurately modeled linear time-invariant systems with and without delays. Considering a simple muscle-actuated hand model with inaccurately modeled load, both CC and IC remain stable over most of the investigated range, and may become unstable only when the actual load is much smaller than expected, usually smaller than the minimum set by the actual mass of the forearm and hand. Neither CC nor IC is consistently superior to the other in terms of the range of loads over which the system remains stable.Numerical methods and resultsNumerical simulations of time-delayed reaching movements are presented and analyzed to evaluate the effects of model inaccuracies when the control and observer gains are time-dependent, as is assumed to occur in HMC. Both IC and CC agree qualitatively with previously published experimental results with inaccurately modeled plants. Thus, our study suggests that IC copes well with inaccurately modeled plants and is indeed a viable model for HMC.

Highlights

  • Stochastic optimal feedback control (OFC) has been strongly advocated as a framework for investigating human motor control (HMC) [1,2,3,4,5]

  • The inherent noise in HMC is handled by an optimal observer that estimates the state, while inherent delays are overcome by a predictor that predicts the current state from time-delayed state estimation [3, 6]

  • The forearm and hand are modeled as a damped point-mass to account for viscous damping at the elbow and the damping effect of any external device operated by the hand

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Summary

Introduction

Stochastic optimal feedback control (OFC) has been strongly advocated as a framework for investigating human motor control (HMC) [1,2,3,4,5]. Standard HMC theories assume that the communication between these processes is continuous, though others argue that it is intermittent [5, 7,8,9,10]. Human motor control (HMC) has been hypothesized to involve state estimation, prediction and feedback control to overcome noise, delays and disturbances. Depending on the nature of communication, the resulting control is referred to as continuous control (CC) or intermittent control (IC). While standard HMC theories are based on CC, IC has been argued to be more viable since it reduces computational and communication burden and agrees better with some experimental results. We focus on periodic IC, which addresses this lower limit and facilitates analysis

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