Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics, June 12-15, Noordwijk, The Netherlands

Comparison of grip action triggered by haptic or visual cue

Janez Podobnik and Marko Munih

Abstract- Current state of the art in virtual environmentdevelopment allows different levels of immersion, from graph-ical environments, where only visual information is presentedto the user, to haptic environments, where whole set of visualand kinesthetic information is presented to the user. Thispaper presents results of two experimental sets conducted in ahaptic virtual environment (HVE) and in a graphical virtualexperiment (GVE) respectively. The grip force responses to anabrupt haptic or visual cue are investigated and compared.Although the underlying neural control mechanism triggeredby haptic or visual cue are different, both responses are wellpronounced, have similar shape and can thus be compared.Response triggered by the haptic cue has shorter delay, isstronger and shorter in duration in comparison to the responsetriggered by the visual cue.

L. INTRODUCTION

With new advances in robotics, transducers for measuringphysical properties (force, EMG activity, ...) and computertechnology new experimental and measuring devices can beconstructed [1], [2]. These new devices allow experimentswhich are now much less complicated to conduct, are moreaccurate and can be conducted in much more controlled envi-ronment [3], [4]. New advances also allow new rehabilitationtechnologies which are all being vigorously tested, evaluatedand used with success in rehabilitation environment [5]. Useof virtual environments and haptic devices is recognized asa promising approach in augmenting the effectiveness of therehabilitation [6], [3], [4].

Computer generated virtual and haptic environments allowdifferent levels of immersion [1]. The question is whatkind of responses are elicited by different levels of immer-sion. This paper presents the comparison of results of theexperiments conducted in a graphical virtual environment(GVE) and a haptic virtual environment (HVE) which conveydifferent levels of immersion. First set of experiments wasconducted in GVE setup composed of a force transducers formeasuring a grip force and graphical interface. Second set ofexperiments was conducted in HVE setup composed of forcetransducers for measuring the grip force, haptic interfaceHapticMaster and the same graphical interface as in GVEsetup.

Haptic devices are electro-mechanical devices, which con-vey a kinesthetic sense of presence to a human operator inter-acting with a computer generated environment. Through thisinteraction virtual sense of touch is achieved [4]. A hapticdevice can resist to the movements of the human operator, it

This work was supported by the Slovenian Research Agency.J. Podobnik and M. Munih are with the Laboratory of Biomedical Engi-

neering and Robotics, Faculty of Electrical Engineering, University of Ljubl-jana, SI-1000 Ljubljana, Slovenia janezp@robo. fe.uni-lj . si,marko@robo.fe.uni-lj.si

can act with force disturbances on the user, and compel theuser to use higher forces to complete the task. On the otherhand, haptic device can guide and assist the user to completethe given task. Haptic technology allows programming andgenerating external load forces, and defining exact dynamicsand behavior of a virtual environment [2]. Haptic devicesare highly suitable for rehabilitation and have shown widepotential use [5].

The injury of a central nervous system, hand injury andneural or neuromuscular disease affect the hand function.One of the important factors affecting the hand functionis the ability to control the grip strength of sub-maximalforces which are employed during grasping and manipulationof different objects [7]. Understanding the developmentand control of human precision grip in healthy subjects isfundamental for understanding and developing the techniquesand technology for rehabilitation [3].

In a study of the development of a human precision gripEliasson et al. [8] have conducted experiments on triggeredgrip actions during sudden loading. Experiments were notconducted with use of visual environments and no visualdisplay was used in the study. The experiments have shownthat when an abrupt vertical force perturbation acts on theobject held by a precision grip, somatosensory input from thedigits triggers an increase in grip force to restore an adequatesafety margin, thus preventing frictional slips. In the studyconducted by Eliasson et al. the unpredicted increase in loadforce was induced by dropping a small disc on to a receptacleattached to the object held by the subject. In the presentstudy experiments were conducted in the HVE and GVEexperimental conditions. In HVE experimental conditionsthe haptic interface produced the programmed unpredictedincrease in load force. A grip force-measuring device wasinstalled on robot end-effector for measuring the subject'sgrip force response. In the HVE experimental conditionssomatosensory input from the digits triggered the increasein grip force. In the GVE experimental set, a falling sphereshown on the graphical display acted as a visual cue andtriggered the increase in grip force which stopped the sphere.The motivation for the study presented in this paper was totest the proposed experimental setup and to acquire the gripresponses of healthy subjects.

II. METHODSA. Apparatus

Grip force measuring handle was constructed of two loadcells opposing each other for measuring grip force FG.Information from both cells was used to measure grip forceFG by averaging the outputs from both load cells. Load

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Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics, June 12-15, Noordwijk, The Netherlands

cells were attached to a frame, which was attached on theend-point of the haptic interface. Parallel contact surfacesmeasured 33x30 mm and were 34 mm apart. Contact surfaceswere covered by a 4 mm cork plate (as used for cork notice-boards). Measuring range of the grip force measuring handlewas 50 N.

Haptic interface used in this study was a three-degrees offreedom admittance controlled haptic interface HapticMasterdeveloped by FCS Control Systems [9]. Completely newcontrol algorithm for controlling the haptic interface armwas designed and implemented on RTLinux with 2.5 kHzsampling loop frequency. The adopted design paradigmallows implementation of a transparent custom-made robotcontroller.A standard PC with a 21 inch LCD display was used for

displaying 3D virtual environment. Coin3D [10] toolkit wasused for developing the visualization.

Fig. 1. Graphical virtual environment.

B. SubjectsSeven healthy male adults (25-28 years old) participated

in both experiments. The participants had no history of neu-romuscular or musculoskeletal disorders related to the upperextremities and gave their informed consent to participate.

C. Procedure and experimental protocolThe subject was seated in front of the haptic interface

and LCD display. Subject was instructed to lightly grip thegrip force measuring handle by applying pinch grasp (seeFig. 2). The minimum grip force for resisting the slip at thedownward load force of 5 N was in range of 2.5 - 3.5 N.Hence, the light grip was denoted as a grip with a grip forcesmaller than 3.5 N. The subject was instructed to stop thesphere from falling.

Preliminary experiments have shown that there was noeffect of learning for experimental set of 10 successivemeasurements. To further eliminate the effect of learning theHVE and GVE experiments were carried out in mixed andrandom order.

Graphical virtual environment consisted of a sphere onwhich the loading force acts, and two cones representing

Fig. 2. HapticMaster with grip force measuring handle.

virtual fingers. When the experiment started the cones did nottouch the sphere, but were instead in a small distance fromthe sphere (see Fig. 1). If grip force was smaller than 3.5 N,the distance of the cones from the sphere was in proportionto the grip force. If grip force was larger than 3.5 N the conesbecame attached to the surface of the sphere. Movement ofthe sphere was allowed only in z-axis direction (up-downmovement). Cones moved in parallel with the sphere in z-axis and also horizontally, proportional to the grip force torepresent the contact of the sphere with cones.

1) HVE experiment: End-point position of the hapticinterface was displayed as a sphere (as described in chapterII-A). Two forces act on the sphere with mass m: theprogrammed load force FL and measured end-point forceFM. The measured end-point force FM was applied bythe human operator and was measured with three-degree offreedom force sensor attached to the end-point of the hapticinterface.

m a(t) = FL(t) + FM(t) (1)New position and velocity of the end-point of the haptic

interface were then obtained from the calculated accelerationa. When experiment started only the FM force acted on thesphere and the subject was able to move freely the end-point of the haptic interface in z-axis direction. Force FLwas a step function with amplitude of 5 N. The FL forcewas initiated randomly 2 to 7 seconds after the start of theeach experiment.

2) GVE experiment: In the GVE experiment the positionof the end-point of the haptic interface was fixed throughoutthe duration of the experiment. Hence, at the initiation of theload force the sphere began to move downwards but the end-point of the haptic interface remained in the same position.In the HVE experiment subject had to apply the sufficientgrip force to ensure adequate friction conditions for stablegrasp. Only then the sphere could be stopped by applyingsufficient load force FM. The relationship between the gripforce and load force is proportional [11] and depends onfriction conditions [7]. Since the load force FM was notmeasured in the GVE experiments the relationship betweengrip force and force acting on the sphere was simulated. TheFM in GVE experiment was substituted by friction force FF,which was proportional to the measured grip force FG.

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m a(t) = FL(t) + FF(t) < 0

FF(t) = kf FG (t)(2)(3)(4)

Force FF represents a friction force which opposes theload force FL. If the friction force FF was greater than theload force FL, the equation 2 was forced to m a(t) = O,to prevent the sphere from moving upwards at the excessivegrip forces. The friction coefficient kf was calculated so thatgrip force of FG = 3.5N would result in FL + FF = 0 atFL = 5 N, thus kf = 5 N -1.43. In order to fully stop3.5 N=the sphere after the sum of forces became zero the velocitywas gradually decreased to zero by applying the followingrule:

v t 2 kfF s(t)t -=o

o ~~m

In the HVE experiments, user grasping the parallel contactsurfaces applied sufficiently large grip force to ensure ade-quate friction conditions for stable grasp. When the graspwas stable, user was able to apply load force FM and stopthe haptic interface which simulated the dynamic hapticvirtual environment. In both types of virtual environmentthe grip force FG affected the sphere dynamics. In the HVEexperiment the applied grip force FG affected the dynamicsof grip force by ensuring the adequate frictional conditions,while in the GVE experiment this relationship was simulatedand the user did not receive haptic feedback.

D. Data analysis

Signals were recorded at 250 Hz sample frequency, 9-10trials were performed for each of two experimental setups persubject. Experiment was divided in three phases (see Fig. 3):

. Preloading phase: a phase before the initiation of theload force FL.

. Dynamic loading phase: a phase of an abrupt responseof the subject to stabilize the object, from the onset ofthe grip response to the settling of the grip force.

. Static loading phase: a phase of the suboptimal gripforce for resisting the slip of the object due to a constant(static) load force.

The following parameters were extracted from the signalsof the grip force (see Fig. 3):

. Baseline grip force FGb was a mean grip force at least1 second before the initiation of load force. This wasthe grip force in the preloading phase.

. Grip force peak FGmax.

. Static grip force FGS was the grip force in the staticloading phase.

* Grip response latency T1 was the time from the initiationof the load force FL and the onset of the grip forceincrease. The onset of the grip force increase began atthe moment when the grip force reached 5 % of the

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Fig. 3. The grip force response (red line) to the step load force (black line).The grip force response was divided into three phases: A - preloading phase,B - dynamic loading phase and C - static loading phase. In the preloadingphase the baseline grip force FGb was measured and in the static loadingphase the static grip force FGS was measured. Dynamic loading phase wasmost informative and four parameters were measured: grip response latencyTl, grip response rise time Tr, grip force peak FGmax and grip responsefall time Tf.

difference between the baseline grip force FGb and thegrip force peak FGmax.

* Grip response rise time Tr was the time from the onsetof the grip force and the grip force peak FGmax.

* Grip response fall time Tf was the time from the gripforce peak and settling of the grip force. The grip forcesettled when it reached 5 % of the difference betweenthe static grip force FGb and the grip force peak FGmax.

Mann-Whitney U test was used for testing the significantdifferences in the parameter values for the HVE and GVEconditions. P value p < 0.05 was selected as a level ofsignificance.

III. RESULTS

For both the HVE and the GVE experiments the gripresponse curves have similar and distinctive skewed bellshaped profile (see Fig. 4). Before initiation of the load forceFL the subject gripped the handle with a constant force. Afterthe initiation of the load force FL a small delay is present inthe grip force response, after which the grip force responserapidly increases to the peak grip force, and then decreasesto a constant force, which is higher than the grip force beforethe initiation of the load force FL. The rate of the decreaseof the grip force is smaller than the rate of the increase of thegrip force. The grip response was divided in three phases:preloading phase, dynamic loading phase and static loadingphase.

A. Preloading phaseIn the preloading phase the baseline grip force FGb was

constant. Median value for all subjects was 2.6 N for HVEexperiment and 2.8 N for GVE experiment and did not differsignificantly (p = 0.57 > 0.05; see Fig. 5(b)). Only insubject 1 the difference was significant (HVE: FGb = 2.1N, GVE: FGb = 2.6 N; p = 0.02 < 0.05).

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Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics, June 12-15, Noordwijk, The Netherlands

(HVE: FGS = 8.4 N, GVE: FGS = 5.6 N; p = 0.02 < 0.05)the static grip force FGS was lower in GVE experiment.

2.5 3 3.5 4

Fig. 4. Red line represents average of ten grip force responses at HVEexperiment, while black line represents average of ten grip force responsesat GVE experiment. Dashed line represent 25 and 75 percentile.

B. Dynamic loading phaseThe response latency in the HVE experiment was much

shorter as in the GVE experiment (p = 0.00 < 0.05; see

Fig. 5(a)). The median response latency time for all subjectswas 180 ms in the HVE experiment and 480 ms in the GVEexperiment.The median grip response rise time Tr was around 150

ms in both experiments indicating that the grip response risetime Tr was not experiment dependant (p = 0.47 > 0.05;see Fig. 5(c)). However, subjects 3, 4 and 7 had significantlydifferent (p < 0.05) grip response rise times in HVE andGVE experiments.

In HVE experiment the grip force peak FGmax was

significantly larger (FGmax= 38 N) than in GVE experiment(FGmax = 17 N; p = 0.00 < 0.05; see Fig. 5(d)). Only insubject 3 the difference was not significant (p > 0.05) dueto large dispersion of grip force peak FGmax.

Grip response fall time Tf in HVE experiment was shorter(Tf = 1.5 s) than in GVE experiment (Tf = 2.5 s; p =

0.0003 < 0.05; see Fig. 5(e)). In subject 5 the grip response

fall time Tr in HVE experiment was longer (Tr = 4.3 s)than in GVE experiment (Tr = 3.1 s; p = 0.002 < 0.05).In subjects 1, 4 and 7 there was no significant differencebetween the grip response fall time Tf in HVE and GVEexperiment (p > 0.05).

C. Static loading phaseIn general the median static grip force FGS in HVE and

GVE experiment did not differ significantly (p = 0.20; see

Fig. 5(f)). The static grip force in HVE experiments was

FGS = 6.8 N and FGS = 6.2 N in GVE experiment. Static

grip force FGS was significantly different and larger in GVEexperiment in subject 1 (HVE: FGS = 9.6 N, GVE: FGS =

11.1 N; p = 0.004 < 0.05), while in subject 3 (HVE: FGS =6.ON, GVE: FGS = 5.0 N; p = 0.01 < 0.05) and subject 7

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Fig. 5. Statistical values for measured parameters for HVE (blue box) andGVE (green box) experiments: (a) grip response latency T1 (p < 0.05), (b)baseline grip force FGb, (c) grip response rise time T, (d) grip force peakFGmax (p < 0.05), (e) grip response fall time Tf (p < 0.05), (f) staticgrip force FG,

IV. DISCUSSION

Prior to the beginning of the experiment the subjects were

instructed to hold the grip force measuring handle with gripforce smaller than 3.5 N. The grip force of 3.5 N was

considered as light grip as it was the higher bound of theminimum necessary grip force to oppose the load force ofFL = 5 N in static loading phase (minimum necessary

grip force to oppose the load force of FL = 5 N in staticloading phase fora given handle was found to be in range

2.5 - 3.5 N). Although in HVE experimental conditions thehaptic interface could move in up-down direction there was

no significant difference in grip force in preloading phasebetween the HVE and GVE experiments. Conclusion can

be made there is no difference between HVE and GVEexperimental conditions in preloading phase.

Hypothesis is that the graphical virtual environment isinsufficient to adequately test the triggered grip responses

and grip actions, and a system is needed that will also

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Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics, June 12-15, Noordwijk, The Netherlands

include neurological pathways, which are responsible forgrip actions. Grip force response in HVE experimentalconditions is initiated by the cutaneomuscular reflex [8], [12].Cutaneomuscular reflex is elicited with cutaneous stimulationof cutaneous mechanoreceptors in the glabrous skin, whichproduces short- and long-latency EMG responses in handmuscles [13]. Short-latency EMG responses are of spinalorigin, while long-latency EMG responses are probably ofcortical origin and involve higher CNS centers [12], [8], [13].Short-latency EMG responses are around 35 ms and long-latency EMG responses are around 60 ms [14]. Macefield etal. also report that the long-latency EMG response is largerand more robust, and is more important for the automaticcontrol of the grip force. The response latency time ofgrip force response in HVE experiments was 180 ms, whileEliasson et al. [8] reported the grip response latency around70 ms.

In HVE experiment the grip force response was triggeredby cutaneous stimulation of mechanoreceptor, while in GVEexperiments the grip force response was triggered by a visualstimulus. Visual information is processed by an area of cere-bral cortex also refereed to as a visual cortex. Processing isorganized hierarchically with extensive feedback and parallelprocessing [15]. Average reaction time to visual stimulusin humans is in range of 305 to 454 ms, with mean valuearound 380 ms [16]. Median response latency time of gripforce response in GVE experiments was 480 ms. For boththe HVE and GVE experimental conditions the grip forceresponse latency was at least 100 ms longer than cited in theavailable literature [8], [16].

Grip response rise time Tr was found to be 150 ms andvirtual experiment independent. Eliasson et al. [8] reportsgrip force rise time was about 100 ms, which is 50 msshorter. The longer rise time can be contributed to the factthat peak grip force reported by Eliasson et al. was 12 N,while in present experiments the grip force peak FGmax wasin range 25 to 50 N for HVE experiments and 12 to 25 Nfor GVE experiments. Decrease of the grip force after gripforce peak is in GVE experimental conditions slower than inHVE experimental conditions.

Brewer et al. [17] have used visual-feedback distortionto enhance the rehabilitation. In their research they havefound that visual feedback dominates cutaneous/kinestheticfeedback. Gerovich et al. [18] also made similar observation.However, our results show that cutaneous part of informationresults in more pronounced grip response (higher force peakFGmax in HVE experiments than in GVE experiments) thanvisual part of information. The differences are due to natureof the tasks. Brewer et al. [17] instructed their subjects to flexthe index finger against the virtual spring until the desiredforce/distance was reached which is basically tracking taskand is thus related to precision, while in our research the taskwas to ensure adequate grip force for stable grasp. This ismore rudimentary demand than the precision of the grip andshows that dominance of the visual vs. cutaneous/kinestheticfeedback or vice versa is task dependant.

Similar as in preloading phase, in the static loading phase

the grip forces in the HVE and the GVE experimentalconditions were not significantly different. Grip force of 3.5N would be sufficient for resisting the load force for both theHVE and GVE experimental conditions, yet the grip forcewas almost twice as big (around 6.5 N for both experimentalconditions).

Obviously, the cutaneous information from mechanorecep-tors and cutaneomuscular reflex results in much faster andstronger grip response and shorter dynamic loading phase.While the grip force peak FGmax in HVE experimentsdepends on the amplitude of the load force [11], in GVEexperimental conditions the grip force 3.5 N would besufficient to stop the sphere, yet all the subjects respondedwith an increase of grip force above the necessary level, butstill significantly lower than in HVE experiments.

V. CONCLUSIONS AND FUTURE WORK

Grip force response to cutaneous stimulation ofmechanoreceptor (haptic cue) and visual cue wereinvestigated and discussed in this paper. Grip forceresponse has distinctive skewed bell shape for both theHVE and GVE experimental conditions. Differences occurin latency of the grip force response, amplitude and theduration of the grip force response in the dynamic loadingphase. The underlying neural control mechanisms are brieflydiscussed. Though different, both neural control mechanismsresult in muscular response and increased muscular work forachieving the goal of the experiment: stopping the sphere.

Current investigation clearly shows the differences inresponses that can be expected in adult healthy subjects tohaptic or visual virtual environment. Since haptic plus visualor only visual environments are common in advanced reha-bilitation technology this investigation shows the potential ofthe two kinds of the virtual environments. Graphical virtualenvironment and force measuring transducers are simplesystems suitable for motor rehabilitation [3], however onlylimited number of neurological pathways is included in theinteraction. Haptic virtual environments trigger additionalneurological pathways thus enhancing the neurorehabilita-tion. Force feedback might be costly and more complicatedto construct, but it can potentially provide benefit because ofthe decrease of cognitive demand due to its intuitive nature,which is important in neurorehabilitation, where emphasisis on motor-control improvements rather than on cognitivework.

This investigation has produced valuable insight into re-sponses in haptic and visual virtual environments in healthyadult subjects. The motivation for the study was to testthe proposed experimental setup and to acquire the gripresponses of the healthy subjects. Future work will in-clude the realization of presented experiments with improvedmethodology on subject with motor disabilities, different agegroups and also subject with different levels of experiencesin virtual environments. Presented apparatus also allows thedesign of new experiments for studying grip action.

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Proceedings of the 2007 IEEE 10th International Conference on Rehabilitation Robotics, June 12-15, Noordwijk, The Netherlands

VI. ACKNOWLEDGMENTSThe authors acknowledge the financial support from the

Slovenian Research Agency (ARRS).

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