Is Intermittent Control the Source of the Non-Linear Oscillatory Component (0.2-2Hz) in Human Balance Control?

OBJECTIVE: To explain the 0.2-2Hz oscillation in human balance. MOTIVATION: Oscillation (0.2-2 Hz) in the control signal (ankle moment) is sustained independently of external disturbances and exaggerated in Parkinson's disease. Does resonance or limit cycles in the neurophysiological feedback loop cause this oscillation? We investigate two linear (non-predictive, predictive) and one non-linear (intermittent-predictive) control model (NPC, PC, IPC). METHODS: Fourteen healthy participants, strapped to an actuated single segment robot with dynamics of upright standing, used natural haptic-visual feedback and myoelectric control signals from lower leg muscles to maintain balance. An input disturbance applied stepwise changes in external force. A linear time invariant model (ARX) extracted the delayed component of the control signal related linearly to the disturbance, leaving the remaining, larger, oscillatory non-linear component. We optimized model parameters and noise (observation, motor) to replicate concurrently (i) estimated-delay, (ii) time-series of the linear component, and (iii) magnitude-frequency spectrum and transient magnitude response of the non-linear component. Results (mean±S.D., p<0.05): NPC produced estimated delays (0.116±0.03s) significantly lower than experiment (0.145±0.04s). Overall fit (i)-(iii) was (79±7%, 83±7%, 84±6% for NPC, PC, IPC). IPC required little or no noise. Mean frequency of experimental oscillation (0.99±0.16 Hz) correlated trial by trial with closed loop resonant frequency (fres), not limit cycles, nor sampling rate. NPC (0.36±0.08Hz) and PC (0.86±0.4Hz) showed fres significantly lower than IPC (0.98±0.2Hz). CONCLUSION: Human balance control requires short-term prediction. SIGNIFICANCE: IPC mechanisms (prediction error, threshold related sampling, sequential re-initialization of open-loop predictive control) explain resonant gain without uncontrolled oscillation for healthy balance.

Estimation of absolute states of human skeletal muscle via standard B-mode ultrasound imaging and deep convolutional neural networks.

The objective is to test automated in vivo estimation of active and passive skeletal muscle states using ultrasonic imaging. Current technology (electromyography, dynamometry, shear wave imaging) provides no general, non-invasive method for online estimation of skeletal muscle states. Ultrasound (US) allows non-invasive imaging of muscle, yet current computational approaches have never achieved simultaneous extraction or generalization of independently varying active and passive states. We use deep learning to investigate the generalizable content of two-dimensional (2D) US muscle images. US data synchronized with electromyography of the calf muscles, with measures of joint moment/angle, were recorded from 32 healthy participants (seven female; ages: 27.5, 19-65). We extracted a region of interest of medial gastrocnemius and soleus using our prior developed accurate segmentation algorithm. From the segmented images, a deep convolutional neural network was trained to predict three absolute, drift-free components of the neurobiomechanical state (activity, joint angle, joint moment) during experimentally designed, simultaneous independent variation of passive (joint angle) and active (electromyography) inputs. For all 32 held-out participants (16-fold cross-validation) the ankle joint angle, electromyography and joint moment were estimated to accuracy 55 ± 8%, 57 ± 11% and 46 ± 9%, respectively. With 2D US imaging, deep neural networks can encode, in generalizable form, the activity-length-tension state relationship of these muscles. Observation-only, low-power 2D US imaging can provide a new category of technology for non-invasive estimation of neural output, length and tension in skeletal muscle. This proof of principle has value for personalized muscle assessment in pain, injury, neurological conditions, neuropathies, myopathies and ageing.

Fully automated image-based estimation of postural point-features in children with cerebral palsy using deep learning.

The aim of this study was to provide automated identification of postural point-features required to estimate the location and orientation of the head, multi-segmented trunk and arms from videos of the clinical test 'Segmental Assessment of Trunk Control' (SATCo). Three expert operators manually annotated 13 point-features in every fourth image of 177 short (5-10 s) videos (25 Hz) of 12 children with cerebral palsy (aged: 4.52 ± 2.4 years), participating in SATCo testing. Linear interpolation for the remaining images resulted in 30 825 annotated images. Convolutional neural networks were trained with cross-validation, giving held-out test results for all children. The point-features were estimated with error 4.4 ± 3.8 pixels at approximately 100 images per second. Truncal segment angles (head, neck and six thoraco-lumbar-pelvic segments) were estimated with error 6.4 ± 2.8°, allowing accurate classification (F 1 > 80%) of deviation from a reference posture at thresholds up to 3°, 3° and 2°, respectively. Contact between arm point-features (elbow and wrist) and supporting surface was classified at F 1 = 80.5%. This study demonstrates, for the first time, technical feasibility to automate the identification of (i) a sitting segmental posture including individual trunk segments, (ii) changes away from that posture, and (iii) support from the upper limb, required for the clinical SATCo.

Foreground Detection Analysis of Ultrasound Image Sequences Identifies Markers of Motor Neurone Disease across Diagnostically Relevant Skeletal Muscles.

Diagnosis of motor neurone disease (MND) includes detection of small, involuntary muscle excitations, termed fasciculations. There is need to improve diagnosis and monitoring of MND through provision of objective markers of change. Fasciculations are visible in ultrasound image sequences. However, few approaches that objectively measure their occurrence have been proposed; their performance has been evaluated in only a few muscles; and their agreement with the clinical gold standard for fasciculation detection, intramuscular electromyography, has not been tested. We present a new application of adaptive foreground detection using a Gaussian mixture model (GMM), evaluating its accuracy across five skeletal muscles in healthy and MND-affected participants. The GMM provided good to excellent accuracy with the electromyography ground truth (80.17%-92.01%) and was robust to different ultrasound probe orientations. The GMM provides objective measurement of fasciculations in each of the body segments necessary for MND diagnosis and hence could provide a new, clinically relevant disease marker.

The effect of fear of falling on vestibular feedback control of balance.

Vestibular sensation contributes to cervical-head stabilization and fall prevention. To what extent fear of falling influences the associated vestibular feedback processes is currently undetermined. We used galanic vestibular stimulation (GVS) to induce vestibular reflexes while participants stood at ground level and on a narrow walkway at 3.85 m height to induce fear of falling. Fear was confirmed by questionnaires and elevated skin conductance. Full-body kinematics was measured to differentiate the whole-body centre of mass response (CoM) into component parts (cervical, axial trunk, appendicular short latency, and medium latency). We studied the effect of fear of falling on each component to discern their underlying mechanisms. Statistical parametric mapping analysis provided sensitive discrimination of early GVS and height effects. Kinematic analysis revealed responses at 1 mA stimulation previously believed marginal through EMG and force plate analysis. The GVS response comprised a rapid, anode-directed cervical-head acceleration, a short-latency cathode-directed acceleration (cathodal buckling) of lower extremities and pelvis, an anode-directed upper thorax acceleration, and subsequently a medium-latency anode-directed acceleration of all body parts. At height, head and upper thorax early acceleration were unaltered, however, short-latency lower extremity acceleration was increased. The effect of height on balance was a decreased duration and increased rate of change in the CoM acceleration pattern. These results demonstrate that fear modifies vestibular control of balance, whereas cervical-head stabilization is governed by different mechanisms unaffected by fear of falling. The mechanical pattern of cathodal buckling and its modulation by fear of falling both support the hypothesis that short-latency responses contribute to regulate balance.

Visuo-manual tracking: does intermittent control with aperiodic sampling explain linear power and non-linear remnant without sensorimotor noise?

KEY POINTS: A human controlling an external system is described most easily and conventionally as linearly and continuously translating sensory input to motor output, with the inevitable output remnant, non-linearly related to the input, attributed to sensorimotor noise. Recent experiments show sustained manual tracking involves repeated refractoriness (insensitivity to sensory information for a certain duration), with the temporary 200-500 ms periods of irresponsiveness to sensory input making the control process intrinsically non-linear. This evidence calls for re-examination of the extent to which random sensorimotor noise is required to explain the non-linear remnant. This investigation of manual tracking shows how the full motor output (linear component and remnant) can be explained mechanistically by aperiodic sampling triggered by prediction error thresholds. Whereas broadband physiological noise is general to all processes, aperiodic sampling is associated with sensorimotor decision making within specific frontal, striatal and parietal networks; we conclude that manual tracking utilises such slow serial decision making pathways up to several times per second. ABSTRACT: The human operator is described adequately by linear translation of sensory input to motor output. Motor output also always includes a non-linear remnant resulting from random sensorimotor noise from multiple sources, and non-linear input transformations, for example thresholds or refractory periods. Recent evidence showed that manual tracking incurs substantial, serial, refractoriness (insensitivity to sensory information of 350 and 550 ms for 1st and 2nd order systems respectively). Our two questions are: (i) What are the comparative merits of explaining the non-linear remnant using noise or non-linear transformations? (ii) Can non-linear transformations represent serial motor decision making within the sensorimotor feedback loop intrinsic to tracking? Twelve participants (instructed to act in three prescribed ways) manually controlled two systems (1st and 2nd order) subject to a periodic multi-sine disturbance. Joystick power was analysed using three models, continuous-linear-control (CC), continuous-linear-control with calculated noise spectrum (CCN), and intermittent control with aperiodic sampling triggered by prediction error thresholds (IC). Unlike the linear mechanism, the intermittent control mechanism explained the majority of total power (linear and remnant) (77-87% vs. 8-48%, IC vs. CC). Between conditions, IC used thresholds and distributions of open loop intervals consistent with, respectively, instructions and previous measured, model independent values; whereas CCN required changes in noise spectrum deviating from broadband, signal dependent noise. We conclude that manual tracking uses open loop predictive control with aperiodic sampling. Because aperiodic sampling is inherent to serial decision making within previously identified, specific frontal, striatal and parietal networks we suggest that these structures are intimately involved in visuo-manual tracking.

Effects of attentional focus on walking stability in elderly.

INTRODUCTION: Balance performance in the elderly is related to psychological factors such as attentional focus. We investigated the effects of internal vs. external focus of attention and fall history on walking stability in healthy older adults. METHOD: Walking stability of twenty-eight healthy older adults was assessed by applying random unilateral decelerations on a split-belt treadmill and analysing the resulting balance recovery movements. The internal focus instruction was: concentrate on the movement of your legs, whereas the external focus instruction was: concentrate on the movement of the treadmill. In both conditions participants were asked to look ahead at a screen. Outcome measures were coefficient of variation of step length and step width, and characteristics of the centre of mass velocity time-series as analysed using statistical parametric mapping. Fall history was assessed using a questionnaire. RESULTS: After each perturbation participants required two to three strides to regain a normal gait pattern, as determined by the centre of mass velocity response. No effects were found of internal and external focus of attention instructions and fall history on any of the outcome measures. DISCUSSION: We conclude that, compared to an internal focus of attention instruction, external focus to the walking surface does not lead to improved balance recovery responses to gait perturbations in the elderly.

Influence of focus of attention, reinvestment and fall history on elderly gait stability.

Falls represent a substantial risk in the elderly. Previous studies have found that a focus on the outcome or effect of the movement (external focus of attention) leads to improved balance performance, whereas a focus on the movement execution itself (internal focus of attention) impairs balance performance in elderly. A shift toward more conscious, explicit forms of motor control occurs when existing declarative knowledge is recruited in motor control, a phenomenon called reinvestment. We investigated the effects of attentional focus and reinvestment on gait stability in elderly fallers and nonfallers. Full body kinematics was collected from twenty-eight healthy older adults walking on a treadmill, while focus of attention was manipulated through instruction. Participants also filled out the Movement Specific Reinvestment Scale (MSRS) and the Falls Efficacy Scale International (FES-I), and provided details about their fall history. Coefficients of Variation (CV) of spatiotemporal gait parameters and Local Divergence Exponents (LDE) were calculated as measures of gait variability and gait stability, respectively. Larger stance time CV and LDE (decreased gait stability) were found for fallers compared to nonfallers. No significant effect of attentional focus was found for the gait parameters, and no significant relation between MSRS score (reinvestment) and fall history was found. We conclude that external attention to the walking surface does not lead to improved gait stability in elderly. Potential benefits of an external focus of attention might not apply to gait, because walking movements are not geared toward achieving a distinct environmental effect.

Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure.

Despite widespread availability of ultrasound and a need for personalised muscle diagnosis (neck/back pain-injury, work related disorder, myopathies, neuropathies), robust, online segmentation of muscles within complex groups remains unsolved by existing methods. For example, Cervical Dystonia (CD) is a prevalent neurological condition causing painful spasticity in one or multiple muscles in the cervical muscle system. Clinicians currently have no method for targeting/monitoring treatment of deep muscles. Automated methods of muscle segmentation would enable clinicians to study, target, and monitor the deep cervical muscles via ultrasound. We have developed a method for segmenting five bilateral cervical muscles and the spine via ultrasound alone, in real-time. Magnetic Resonance Imaging (MRI) and ultrasound data were collected from 22 participants (age: 29.0±6.6, male: 12). To acquire ultrasound muscle segment labels, a novel multimodal registration method was developed, involving MRI image annotation, and shape registration to MRI-matched ultrasound images, via approximation of the tissue deformation. We then applied polynomial regression to transform our annotations and textures into a mean space, before using shape statistics to generate a texture-to-shape dictionary. For segmentation, test images were compared to dictionary textures giving an initial segmentation, and then we used a customized Active Shape Model to refine the fit. Using ultrasound alone, on unseen participants, our technique currently segments a single image in [Formula: see text] to over 86% accuracy (Jaccard index). We propose this approach is applicable generally to segment, extrapolate and visualise deep muscle structure, and analyse statistical features online.

Proactive Selective Inhibition Targeted at the Neck Muscles: This Proximal Constraint Facilitates Learning and Regulates Global Control.

While individual muscle function is known, the sensory and motor value of muscles within the whole-body sensorimotor network is complicated. Specifically, the relationship between neck muscle action and distal muscle synergies is unknown. This work demonstrates a causal relationship between regulation of the neck muscles and global motor control. Studying violinists performing unskilled and skilled manual tasks, we provided ultrasound feedback of the neck muscles with instruction to minimize neck muscle change during task performance and observed the indirect effect on whole-body movement. Analysis of ultrasound, kinematic, electromyographic and electrodermal recordings showed that proactive inhibition targeted at neck muscles had an indirect global effect reducing the cost of movement, reducing complex involuntary, task-irrelevant movement patterns and improving balance. This effect was distinct from the effect of gaze alignment which increased physiological cost and reduced laboratory-referenced movement. Neck muscle inhibition imposes a proximal constraint on the global motor plan, forcing a change in highly automated sensorimotor control. The proximal location ensures global influence. The criterion, inhibition of unnecessary action, ensures reduced cost while facilitating task-relevant variation. This mechanism regulates global motor function and facilitates reinforcement learning to change engrained, maladapted sensorimotor control associated with chronic pain, injury and performance limitation.

An evaluation of 3D head pose estimation using the Microsoft Kinect v2.

The Kinect v2 sensor supports real-time non-invasive 3D head pose estimation. Because the sensor is small, widely available and relatively cheap it has great potential as a tool for groups interested in measuring head posture. In this paper we compare the Kinect's head pose estimates with a marker-based record of ground truth in order to establish its accuracy. During movement of the head and neck alone (with static torso), we find average errors in absolute yaw, pitch and roll angles of 2.0±1.2°, 7.3±3.2° and 2.6±0.7°, and in rotations relative to the rest pose of 1.4±0.5°, 2.1±0.4° and 2.0±0.8°. Larger head rotations where it becomes difficult to see facial features can cause estimation to fail (10.2±6.1% of all poses in our static torso range of motion tests) but we found no significant changes in performance with the participant standing further away from Kinect - additionally enabling full-body pose estimation - or without performing face shape calibration, something which is not always possible for younger or disabled participants. Where facial features remain visible, the sensor has applications in the non-invasive assessment of postural control, e.g. during a programme of physical therapy. In particular, a multi-Kinect setup covering the full range of head (and body) movement would appear to be a promising way forward.

Ultrasound-Based Detection of Fasciculations in Healthy and Diseased Muscles.

Involuntary muscle activations are diagnostic indicators of neurodegenerative pathologies. Currently detected by invasive intramuscular electromyography, these muscle twitches are found to be visible in ultrasound images. We present an automated computational approach for the detection of muscle twitches, and apply this to two muscles in healthy and motor neuron disease-affected populations. The technique relies on motion tracking within ultrasound sequences, extracting local movement information from muscle. A statistical analysis is applied to classify the movement, either as noise or as more coherent movement indicative of a muscle twitch. The technique is compared to operator identified twitches, which are also assessed to ensure operator agreement. We find that, when two independent operators manually identified twitches, higher interoperator agreement (Cohen's κ) occurs when more twitches are present (κ = 0.94), compared to a lower number (κ = 0.49). Finally, we demonstrate, via analysis of receiver operating characteristics, that our computational technique detects muscle twitches across the entire dataset with a high degree of accuracy (0.83 < accuracy < 0.96).

Postural threat differentially affects the feedforward and feedback components of the vestibular-evoked balance response.

Circumstances may render the consequence of falling quite severe, thus maximising the motivation to control postural sway. This commonly occurs when exposed to height and may result from the interaction of many factors, including fear, arousal, sensory information and perception. Here, we examined human vestibular-evoked balance responses during exposure to a highly threatening postural context. Nine subjects stood with eyes closed on a narrow walkway elevated 3.85 m above ground level. This evoked an altered psycho-physiological state, demonstrated by a twofold increase in skin conductance. Balance responses were then evoked by galvanic vestibular stimulation. The sway response, which comprised a whole-body lean in the direction of the edge of the walkway, was significantly and substantially attenuated after ~800 ms. This demonstrates that a strong reason to modify the balance control strategy was created and subjects were highly motivated to minimise sway. Despite this, the initial response remained unchanged. This suggests little effect on the feedforward settings of the nervous system responsible for coupling pure vestibular input to functional motor output. The much stronger, later effect can be attributed to an integration of balance-relevant sensory feedback once the body was in motion. These results demonstrate that the feedforward and feedback components of a vestibular-evoked balance response are differently affected by postural threat. Although a fear of falling has previously been linked with instability and even falling itself, our findings suggest that this relationship is not attributable to changes in the feedforward vestibular control of balance.

Interfacing sensory input with motor output: does the control architecture converge to a serial process along a single channel?

Modular organization in control architecture may underlie the versatility of human motor control; but the nature of the interface relating sensory input through task-selection in the space of performance variables to control actions in the space of the elemental variables is currently unknown. Our central question is whether the control architecture converges to a serial process along a single channel? In discrete reaction time experiments, psychologists have firmly associated a serial single channel hypothesis with refractoriness and response selection [psychological refractory period (PRP)]. Recently, we developed a methodology and evidence identifying refractoriness in sustained control of an external single degree-of-freedom system. We hypothesize that multi-segmental whole-body control also shows refractoriness. Eight participants controlled their whole body to ensure a head marker tracked a target as fast and accurately as possible. Analysis showed enhanced delays in response to stimuli with close temporal proximity to the preceding stimulus. Consistent with our preceding work, this evidence is incompatible with control as a linear time invariant process. This evidence is consistent with a single-channel serial ballistic process within the intermittent control paradigm with an intermittent interval of around 0.5 s. A control architecture reproducing intentional human movement control must reproduce refractoriness. Intermittent control is designed to provide computational time for an online optimization process and is appropriate for flexible adaptive control. For human motor control we suggest that parallel sensory input converges to a serial, single channel process involving planning, selection, and temporal inhibition of alternative responses prior to low dimensional motor output. Such design could aid robots to reproduce the flexibility of human control.

Human standing: does the control strategy preprogram a rigid knee?

Human standing requires control of multisegmental configuration. Does the postural system normally allow flexible adjustment of configuration, or does it minimize degrees of freedom at the ankle, knee, and hip joints? Gentle, external, unpredictable, sagittal, mechanical perturbations (randomized force, 1-10 N; duration, 0.2-2 s; and leg) were applied to either knee of 24 healthy participants who stood symmetrically for 200 s. The translation of knee perturbation force to ankle, knee, and hip joint rotations in the perturbed and unperturbed legs was studied. We assessed whether consequent joint rotations indicated a stiff configuration-conserving or viscous energy-absorbing relationship to the knee perturbation. Two distinctive response patterns were observed. Twenty-two participants showed limited knee flexion and high ankle stiffness, whereas two participants showed substantial knee flexion, low ankle stiffness, measurable internal rotation of the unperturbed hip (0.4 ± 0.3 vs. 3.0 ± 1°, 5.7 ± 17 vs. 0.5 ± 0.3 N/°, 1.1 ± 0.4°, respectively; mean ± SD), and a viscous relationship between perturbation force and subsequent ankle flexion, knee flexion, and perturbed and unperturbed hip internal rotation. The size of knee-flexion response to knee perturbations was uncorrelated with the extent of unperturbed standing sway. Normal standing conceals a large interindividual range in leg control strategies, indicating adaptive potential to progress with development and skill acquisition and decline with age, disease, injury, and fear. Commonly, leg configuration was maintained stiffly. Less commonly, a bilateral, low-stiffness, energy-absorbing strategy utilizing the available degrees of freedom was shown. We propose that identification of individual coordination strategy has diagnostic and prognostic potential in relation to perceptual-posture-movement-fall interactions.

Refractoriness in sustained visuo-manual control: is the refractory duration intrinsic or does it depend on external system properties?

Researchers have previously adopted the double stimulus paradigm to study refractoriness in human neuromotor control. Currently, refractoriness, such as the Psychological Refractory Period (PRP) has only been quantified in discrete movement conditions. Whether refractoriness and the associated serial ballistic hypothesis generalises to sustained control tasks has remained open for more than sixty years. Recently, a method of analysis has been presented that quantifies refractoriness in sustained control tasks and discriminates intermittent (serial ballistic) from continuous control. Following our recent demonstration that continuous control of an unstable second order system (i.e. balancing a 'virtual' inverted pendulum through a joystick interface) is unnecessary, we ask whether refractoriness of substantial duration (~200 ms) is evident in sustained visual-manual control of external systems. We ask whether the refractory duration (i) is physiologically intrinsic, (ii) depends upon system properties like the order (0, 1(st), and 2(nd)) or stability, (iii) depends upon target jump direction (reversal, same direction). Thirteen participants used discrete movements (zero order system) as well as more sustained control activity (1(st) and 2(nd) order systems) to track unpredictable step-sequence targets. Results show a substantial refractory duration that depends upon system order (250, 350 and 550 ms for 0, 1(st) and 2(nd) order respectively, n=13, p<0.05), but not stability. In sustained control refractoriness was only found when the target reverses direction. In the presence of time varying actuators, systems and constraints, we propose that central refractoriness is an appropriate control mechanism for accommodating online optimization delays within the neural circuitry including the more variable processing times of higher order (complex) input-output relations.

Myoelectric activity along human gastrocnemius medialis: different spatial distributions of postural and electrically elicited surface potentials.

It has recently been shown that motor units in human medial gastrocnemius (MG), activated during standing, occupy relatively small territories along the muscle's longitudinal axis. Such organisation provides potential for different motor tasks to produce differing regional patterns of activity. Here, we investigate whether postural control and nerve electrical stimulation produce equal longitudinal activation patterns in MG. Myoelectric activity, at different proximal-distal locations of MG, was recorded using a linear electrode array. To ensure differences in signal amplitude between channels did not result from local, morphological factors two experimental protocols were completed: (i) quiet standing; (ii) electrical stimulation of the tibial nerve. Averaged, rectified values (ARVs) were calculated for each channel in each condition. The distribution of signals along electrode channels was described using linear regression and differences between protocols at each channel determined as the ratio between mean ARV from standing: stimulation protocols. Ratio values changed systematically across electrode channels in seven (of eight) participants, with larger values in distal channels. The distribution of ARV along MG therefore differed between experimental conditions. Compared to fibres of units activated during MG nerve stimulation, units activated during standing may have a tendency to be more highly represented in the distal muscle portion.

Frequency-domain identification of the human controller.

System identification techniques applied to experimental human-in-the-loop data provide an objective test of three alternative control-theoretical models of the human control system: non-predictive control, predictive control, and intermittent predictive control. A two-stage approach to the identification of a single-input single-output control system is used: first, the closed-loop frequency response is derived using the periodic property of the experimental data, followed by the fitting of a parametric model. While this approach is well-established for non-predictive and predictive control, it is here used for the first time with intermittent predictive control. This technique is applied to data from experiments with human volunteers who use one of two control strategies, focusing either on position or on velocity, to manually control a virtual, unstable load which requires sustained feedback to maintain position or low velocity. The results show firstly that the non-predictive controller does not fit the data as well as the other two models, and secondly that the predictive and intermittent predictive controllers provide equally good models which cannot be distinguished using this approach. Importantly, the second observation implies that sustained visual manual control is compatible with intermittent control, and that previous results suggesting a continuous control model for the human control system do not rule out intermittent control as an alternative hypothesis. Thirdly, the parameters identified reflect the control strategy adopted by the human controller.