Establishing metrics and control laws for the learning process: ball and beam balancing

Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam implementation of a dexterity puzzle in which subjects stabilize a ball at the mid-point of a beam by manipulating the angular position of the b...

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Published inBiological cybernetics Vol. 114; no. 1; pp. 83 - 93
Main Authors Buza, Gergely, Milton, John, Bencsik, Laszlo, Insperger, Tamas
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2020
Springer Nature B.V
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Abstract Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam implementation of a dexterity puzzle in which subjects stabilize a ball at the mid-point of a beam by manipulating the angular position of the beam. Stabilizability analysis of different biomechanical models for the ball and beam task with time-delayed proportional-derivative feedback identified the angular position of the beam as the manipulated variable. Consequently, we monitored the changes in the dynamics with learning by measuring changes in the control parameters. Two types of stable motion are possible: node type (nonoscillatory) and spiral type (oscillatory). Both types of motion are observed experimentally and correspond to well-defined regions in the parameter space of the control gains. With practice the control gains for each subject move close to or on the portion of the boundary which separates the node-type and spiral-type solutions and which is associated with the rightmost characteristic exponent of smallest real part. These observations suggest that with learning the control gains for ball and beam balancing change in such a way that minimizes overshoot and the settling time. This study provides an example of how mathematical analysis together with careful experimental observations can shed light onto the early stages of skill acquisition. Since the difficulty of this task depends on the length of the beam, ball and beam balancing tasks may be useful for the rehabilitation of children with dyspraxia and those recovering from a stroke.
AbstractList Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam implementation of a dexterity puzzle in which subjects stabilize a ball at the mid-point of a beam by manipulating the angular position of the beam. Stabilizability analysis of different biomechanical models for the ball and beam task with time-delayed proportional-derivative feedback identified the angular position of the beam as the manipulated variable. Consequently, we monitored the changes in the dynamics with learning by measuring changes in the control parameters. Two types of stable motion are possible: node type (nonoscillatory) and spiral type (oscillatory). Both types of motion are observed experimentally and correspond to well-defined regions in the parameter space of the control gains. With practice the control gains for each subject move close to or on the portion of the boundary which separates the node-type and spiral-type solutions and which is associated with the rightmost characteristic exponent of smallest real part. These observations suggest that with learning the control gains for ball and beam balancing change in such a way that minimizes overshoot and the settling time. This study provides an example of how mathematical analysis together with careful experimental observations can shed light onto the early stages of skill acquisition. Since the difficulty of this task depends on the length of the beam, ball and beam balancing tasks may be useful for the rehabilitation of children with dyspraxia and those recovering from a stroke.
Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam implementation of a dexterity puzzle in which subjects stabilize a ball at the mid-point of a beam by manipulating the angular position of the beam. Stabilizability analysis of different biomechanical models for the ball and beam task with time-delayed proportional-derivative feedback identified the angular position of the beam as the manipulated variable. Consequently, we monitored the changes in the dynamics with learning by measuring changes in the control parameters. Two types of stable motion are possible: node type (nonoscillatory) and spiral type (oscillatory). Both types of motion are observed experimentally and correspond to well-defined regions in the parameter space of the control gains. With practice the control gains for each subject move close to or on the portion of the boundary which separates the node-type and spiral-type solutions and which is associated with the rightmost characteristic exponent of smallest real part. These observations suggest that with learning the control gains for ball and beam balancing change in such a way that minimizes overshoot and the settling time. This study provides an example of how mathematical analysis together with careful experimental observations can shed light onto the early stages of skill acquisition. Since the difficulty of this task depends on the length of the beam, ball and beam balancing tasks may be useful for the rehabilitation of children with dyspraxia and those recovering from a stroke.Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam implementation of a dexterity puzzle in which subjects stabilize a ball at the mid-point of a beam by manipulating the angular position of the beam. Stabilizability analysis of different biomechanical models for the ball and beam task with time-delayed proportional-derivative feedback identified the angular position of the beam as the manipulated variable. Consequently, we monitored the changes in the dynamics with learning by measuring changes in the control parameters. Two types of stable motion are possible: node type (nonoscillatory) and spiral type (oscillatory). Both types of motion are observed experimentally and correspond to well-defined regions in the parameter space of the control gains. With practice the control gains for each subject move close to or on the portion of the boundary which separates the node-type and spiral-type solutions and which is associated with the rightmost characteristic exponent of smallest real part. These observations suggest that with learning the control gains for ball and beam balancing change in such a way that minimizes overshoot and the settling time. This study provides an example of how mathematical analysis together with careful experimental observations can shed light onto the early stages of skill acquisition. Since the difficulty of this task depends on the length of the beam, ball and beam balancing tasks may be useful for the rehabilitation of children with dyspraxia and those recovering from a stroke.
Author Bencsik, Laszlo
Buza, Gergely
Insperger, Tamas
Milton, John
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Issue 1
Keywords Learning
Reaction time
Human balancing
Visual feedback
Motor control
Language English
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Communicated by Benjamin Lindner.
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PublicationTitleAlternate Biol Cybern
PublicationYear 2020
Publisher Springer Berlin Heidelberg
Springer Nature B.V
Publisher_xml – name: Springer Berlin Heidelberg
– name: Springer Nature B.V
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WelfordATReaction time, speed of performance, and ageAnn New York Acad Sci19885151171:STN:280:DyaL1c3gvVWntA%3D%3D
GawthropPJLoramIGolleeHLakieMIntermittent control models of human standing: similarities and differencesBiol Cybern2014108159168245006163962584
TallandGACairnieJAging effects on simple, disjunctive, and alerted finger reaction timeJ Gerontol1961163703741:STN:280:DyaF387htV2mug%3D%3D13919346
GawthropPJLoramILakieMGolleeHIntermittent control: a computational theory of human controlBiol Cybern2011104315121327829
MetcalfCDIrvineTASimsJLWangYLSuAWYNorrisDOComplex hand dexterity: a review of biomechanical methods for measuring musical performanceFront Psychol20145414248605314026728
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BuzaGInspergerTMathematical models for balancing tasks on a see-saw with reaction time delayIFC PapersOnLine20185114288293
RowleyKMGordonJKuligKCharacterizing the balance-dexterity task as a concurrent bipedal task to investigate trunk control during dynamic balanceJ Biomech20187721121730037579
StepanGDelay effects in the human sensory system during balancingPhil Trans R Soc A20093671195121219218159
InouyeJMValero-CuevasFJMuscle synergies heavily influence the neural control of arm endpoint stiffness and energy consumptionPLoS Comput Biol2016122124
VenkadesanMGuckenheimerJValero-CuevasFJManipulating the edge of stabilityJ Biomech20074016531661174002312666355
MiltonJCabreraJLOhiraTTajimaSTonosakiYEurichCWCampbellSAThe time-delayed inverted pendulum: implications for human balance controlChaos: Interdiscip J Nonlinear Sci2009192026110
YoshikawaNSuzukiYKiyonoKNomuraTIntermittent feedback-control strategy for stabilizing inverted pendulum on manually controlled cart as analogy to human stick balancingFront Comp Neurosci20161034
CabreraJLMiltonJGOn–off intermittency in a human balancing taskPhys Rev Lett20028915870212366030
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MiallRCTask-dependent changes in visual feedback control: a frequency analysis of human manual trackingJ Mot Behav1996281251351:STN:280:DC%2BD1Mjjs1SmsQ%3D%3D12529214
WellsteadPEIntroduction to physical system modelling1979LondonAcademic Press
MiltonJSolodkinAHlustikPSmallSLThe mind of expert motor performance is cool and focusedNeuroImage20073580481317317223
CabreraJLMiltonJGHuman stick balancing: tuning Lévy flights to improve balance controlChaos20041469169815446980
FooPKelsoJASde GuzmanGCFunctional stabilization of unstable fixed points: human pole balancing using time-to-balance informationJ Exp Psychol Hum Percept Perform2000264128112971:STN:280:DC%2BD3M%2Fks1Cjsg%3D%3D10946715
BazziSEbertJHoganNSternadDStability and predictability in human control of complex objectsChaos: An Interdiscip J Nonlinear Sci20182810103103
LyleMAValero-CuevasFJGregorRJPowersCMLower extremity dexterity is associated with agility in adolescent soccer athletesScand J Med Sci Sports201525181881:STN:280:DC%2BC2c3lt1Kkug%3D%3D24325628
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NijhawanRWuSCompensating time delays with neural predictions: are predictions sensory or motor?Philos Trans R Soc A: Math, Phys Eng Sci2009367189110631078
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References_xml – reference: ParrellBLammertACCiccarelliGQuatieriTFCurrent models of speech motor control: a control-theoretic overview of architectures and propertiesJ Acoust Soc Am201914531456148131067944
– reference: GawthropPJLoramIGolleeHLakieMIntermittent control models of human standing: similarities and differencesBiol Cybern2014108159168245006163962584
– reference: MetcalfCDIrvineTASimsJLWangYLSuAWYNorrisDOComplex hand dexterity: a review of biomechanical methods for measuring musical performanceFront Psychol20145414248605314026728
– reference: MiltonJMeyerRZhvanetskyMRidgeSInspergerTControl at stability’s edge minimizes energetic costs: expert stick balancingJ R Soc Interface20161320160212272783614938085
– reference: InouyeJMValero-CuevasFJMuscle synergies heavily influence the neural control of arm endpoint stiffness and energy consumptionPLoS Comput Biol2016122124
– reference: MiltonJSolodkinAHlustikPSmallSLThe mind of expert motor performance is cool and focusedNeuroImage20073580481317317223
– reference: BrennerESmeetsJFast responses of the human hand to changes in target positionJ Mot Behav1997292973101:STN:280:DC%2BC28vmtFyqtA%3D%3D12453772
– reference: NijhawanRVisual prediction: psychophysics and neurophysiology of compensation for time delaysBehav Brain Sci200831217919818479557
– reference: MehtaBSchaalSForward models in visuomotor controlJ Neurophysiol20028894295312163543
– reference: StepanGRetarded dynamical systems1989HarlowLongman
– reference: YoshikawaNSuzukiYKiyonoKNomuraTIntermittent feedback-control strategy for stabilizing inverted pendulum on manually controlled cart as analogy to human stick balancingFront Comp Neurosci20161034
– reference: GeorgopoulosAPKalaskaJFMasseyJTSpatial trajectories and reaction times of aimed movements: effects of practice, uncertainty and change in target locationJ Neurophysiol1981467257431:STN:280:DyaL38%2Fjt1CgtQ%3D%3D7288461
– reference: WoodsDLWymaJMYundEWHerronTJReedBFactors influencing the latency of the simple reaction timeFront Hum Neurosci20159131258591984374455
– reference: GawthropPJLoramILakieMGolleeHIntermittent control: a computational theory of human controlBiol Cybern2011104315121327829
– reference: InspergerTMiltonJSensory uncertainty and stick balancing at the fingertipBiol Cybern20141088510124463637
– reference: StepanGDelay effects in the human sensory system during balancingPhil Trans R Soc A20093671195121219218159
– reference: RowleyKMGordonJKuligKCharacterizing the balance-dexterity task as a concurrent bipedal task to investigate trunk control during dynamic balanceJ Biomech20187721121730037579
– reference: LyleMAValero-CuevasFJGregorRJPowersCMThe lower extremity dexterity test as a measure of lower extremity dynamical capabilityJ Biomech2013465998100223357699
– reference: WellsteadPEIntroduction to physical system modelling1979LondonAcademic Press
– reference: LyleMAValero-CuevasFJGregorRJPowersCMLower extremity dexterity is associated with agility in adolescent soccer athletesScand J Med Sci Sports201525181881:STN:280:DC%2BC2c3lt1Kkug%3D%3D24325628
– reference: Lehotzky D (2017) Numerical methods for the stability and stabilizability analysis of delayed dynamical systems. Ph.D. thesis, Budapest University of Technology and Economics
– reference: MiltonJCabreraJLOhiraTTajimaSTonosakiYEurichCWCampbellSAThe time-delayed inverted pendulum: implications for human balance controlChaos: Interdiscip J Nonlinear Sci2009192026110
– reference: ThoroughmanKAShadmehrRLearning of action through adaptive combination of motor primitivesNature20004077427471:CAS:528:DC%2BD3cXnsFWlu7g%3D110487202556237
– reference: FlanaganJVetterPJohanssonRSWolpertDMPrediction precedes control in motor learningCurr Biol20031321461501:CAS:528:DC%2BD3sXmsFeqsA%3D%3D12546789
– reference: RonsseRWeiKSternadDOptimal control of a hybrid rhythmic-discrete task: the bouncing ball revisitedJ Neurophysiol2010103524822493201300422867585
– reference: ShadmehrRSmithMAKrakauerJWError correction, sensory prediction, and adaptation in motor controlAnnu Rev Neurosci2010331891081:CAS:528:DC%2BC3cXhsFartrzK20367317
– reference: WelfordATReaction time, speed of performance, and ageAnn New York Acad Sci19885151171:STN:280:DyaL1c3gvVWntA%3D%3D
– reference: MiltonJGFuerteABélairCLippaiJKamimuraAOhiraTDelayed pursuit-escape as a model for virtual stick balancingNonlinear Theory Appl20134129137
– reference: FooPKelsoJASde GuzmanGCFunctional stabilization of unstable fixed points: human pole balancing using time-to-balance informationJ Exp Psychol Hum Percept Perform2000264128112971:STN:280:DC%2BD3M%2Fks1Cjsg%3D%3D10946715
– reference: BurdetEOsuRFranklinDWMillerTEKawatoMThe central nervous system stabilizes unstable dynamics by learning optimal impedanceNature20014144464491:CAS:528:DC%2BD3MXovFamsLY%3D11719805
– reference: FranklinDWWolpertDMComputational mechanisms of sensorimotor controlNeuron20117234254421:CAS:528:DC%2BC3MXhsVKiu7fI22078503
– reference: MolnarTGHajduDInspergerTKarimiHGaoQThe Smith predictor, the modified Smith predictor, and the finite spectrum assignment a comparative studyStability, control and application of time-delay systems2019OxfordButterworth-Heinemann209226
– reference: MiallRCWeirDJSteinJFManual tracking of visual targets by trained monkeysExp Brain Res1986201852011:STN:280:DyaL283mvFCitw%3D%3D
– reference: BuzaGInspergerTMathematical models for balancing tasks on a see-saw with reaction time delayIFC PapersOnLine20185114288293
– reference: NijhawanRWuSCompensating time delays with neural predictions: are predictions sensory or motor?Philos Trans R Soc A: Math, Phys Eng Sci2009367189110631078
– reference: AstromKJWittenmarkBComputer controlled systems: theory and design1984Englewood CliffsPrentice Hall
– reference: KawatoMInternal models for motor control and trajectory planningCurr Opin Neurobiol199997187271:CAS:528:DC%2BD3cXhtFCrug%3D%3D10607637
– reference: PalmorZJTime-delay compensation-Smith predictor and its modificationsThe control handbook2000Boca RatonCRC and IEEE Press224237
– reference: BazziSEbertJHoganNSternadDStability and predictability in human control of complex objectsChaos: An Interdiscip J Nonlinear Sci20182810103103
– reference: CabreraJLMiltonJGHuman stick balancing: tuning Lévy flights to improve balance controlChaos20041469169815446980
– reference: SchaalSAtkesonCGSternadDOne-handed juggling: a dynamical approach to a rhythmic movement taskJ Mot Behav199628216518312529218
– reference: CabreraJLMiltonJGOn–off intermittency in a human balancing taskPhys Rev Lett20028915870212366030
– reference: VenkadesanMGuckenheimerJValero-CuevasFJManipulating the edge of stabilityJ Biomech20074016531661174002312666355
– reference: TallandGACairnieJAging effects on simple, disjunctive, and alerted finger reaction timeJ Gerontol1961163703741:STN:280:DyaF387htV2mug%3D%3D13919346
– reference: MiallRCTask-dependent changes in visual feedback control: a frequency analysis of human manual trackingJ Mot Behav1996281251351:STN:280:DC%2BD1Mjjs1SmsQ%3D%3D12529214
– reference: MyersRHClassical and modern regression with applications1990BostonPws-Kent
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– reference: ChuVWParkSWSangerTDSternadDChildren with dystonia can learn a novel motor skill: strategies that are tolerant to high variabilityIEEE Trans Neural Sys Rehab Eng201624847858
– reference: MichielsWNiculescuSIOn the delay sensitivity of smith predictorsInt J Syst Sci2003348–9543551
– reference: HatfieldBDHillmanCHJanelleMThe psychophysiology of sport: a mechanistic understanding of the psychology of superior performanceHandbook of Sport Psychology20012New YorkWiley362386
– reference: BilalicMThe neuroscience of expertise2017New YorkCambridge University Press
– reference: ChagdesJRRietdykSJeffreyMHHowardNZRamanADynamic stability of a human standing on a balance boardJ Biomech201346152593260224041491
– reference: KrsticMDelay compensation for nonlinear, adaptive, and PDE systems2009BostonBirkhauser
– reference: CruiseDChagdesJLiddyJRietdykSHaddadJMZelaznikHRamanAAn active balance board system with real-time control of stiffness and time-delay to assess mechanisms of postural stabilityJ Biomech201760485628668186
– reference: InspergerTStepanGSemi-discretization method for time-delay systems2011New YorkSpringer
– reference: Valero-CuevasFJHoffmannHKurseMUKutchJJTheodorouEAComputational models for neuromuscular functionIEEE Rev Biomed Eng20092110135216877793116649
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Snippet Understanding how dexterity improves with practice is a fundamental challenge of motor control and neurorehabilitation. Here we investigate a ball and beam...
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StartPage 83
SubjectTerms Adult
Angular position
Balancing
Bioinformatics
Biomechanical engineering
Biomechanics
Biomedical and Life Sciences
Biomedicine
Complex Systems
Computer Appl. in Life Sciences
Control theory
Feedback, Physiological - physiology
Female
Humans
Learning
Learning - physiology
Male
Mathematical models
Motor skill learning
Motor task performance
Movement - physiology
Neurobiology
Neurology
Neurosciences
Original
Original Article
Parameters
Proportional derivative
Psychomotor Performance - physiology
Rehabilitation
Young Adult
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Title Establishing metrics and control laws for the learning process: ball and beam balancing
URI https://link.springer.com/article/10.1007/s00422-020-00815-z
https://www.ncbi.nlm.nih.gov/pubmed/31955261
https://www.proquest.com/docview/2375282168
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https://pubmed.ncbi.nlm.nih.gov/PMC7062859
Volume 114
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