The University of Birmingham

MRes/TDP program

Research Placement 1

HAND AND TOOL MOVEMENT VARIABILITY USING A SIMPLE HAND-TOOL:HAND AND TOOL MOVEMENT VARIABILITY USING A SIMPLE HAND-TOOL:

A PILOT INVESTIGATIONA PILOT INVESTIGATION

ALEXANDROS KARAIOSIF

Student ID No: 668800

Supervisor: Prof. Chris Miall

BIRMINGHAM 2005

INTRODUCTION

Movement variability is a critical factor for coordinated

arm or hand movements especially when someone has to do

reach to grasp movements or pointing to target movements.

Many studies in the past examined the movement variability

in attempt to identify the existence of motor learning after

a series of trials. What happens with the movement

variability when using a hand-tool after a series of

learning movements?

The aim of this study was to examine the hand and the

tool movement variability using a simple hand tool and to

test the differences between one very common grip and one

more unusual grip without vision, but with visual feedback

before and after each trial and between the baseline and the

post-learning phase.

Tool-use results in an extension of the neural

representation of visuotactile peripersonal space (e.g.

2

Holmes, 2004). As peripersonal space we can define the space

immediately surrounding our bodies. If peripersonal space

extends along the axis of a tool during tool-use, then the

typical properties of visuotactile peripersonal space should

also extend along the tools held in each hand (Holmes et al,

2004). This suggestion tells us that when using a tool with

our hands, our peripersonal space becomes bigger and we can

therefore approach the reached workspace in the same way as

if we used only our hands without the tool. On the other

hand, the use of tools to reach objects or to point to

targets, may not simply ‘extend’ our peripersonal space, but

rather that only the grips of the tool become behaviorally

relevant to visuotactile interactions associated with the

hand that holds the tool (Vindra, P. & Viviani, P., 2005).

If we have a target in front of us, then we are able to

detect, locate, orient to, and reach it. All these

operations can be distinguished according to the sector of

space in which they occur and to the action needed for

accomplishing the task (Colby, C.L., & Duhamel, J.R., 1996).

For instance, if the target of interest is located in the

3

immediate surroundings of the body (peripersonal space),

manual reaching and grasping an object, as well as pointing

a target can be achieved without locomotion. On the

contrary, if the target of interest is placed outside a

direct manual reaching (extrapersonal space-the space that

the tool cannot reach), locomotion is needed for subsequent

action to the object. Alternatively, we can use a tool to

reach and grasp far objects and to point some far targets.

In any case, we need to encode the position of the objects

or the targets with respect to the position of the body and

body parts (Berti, A., Frassinetti, F., 2000). An

interesting suggestion of Obayashi et al (2003), after their

experiments using hand-tools tell us that tool-use skill

would produce a ‘motor engram’ specific for the learned hand

and would be stored as procedural memory. Another suggestion

of Harris & Wolpert (1998), is that while we make goal-

directed arm or hand movements, such us reach to grasp or

pointing to a target movements, there is an infinite number

of possible trajectories that the hand could take to reach

the target. However humans show highly stereotyped

4

trajectories in which the velocity profiles are smooth and

symmetric for brief movements. How a reference trajectory

can be used to guide limb movements can be explained from

the equilibrium point hypothesis but this hypothesis does

not tells us how such trajectories might be computed in

tasks more complex than pointing. In the same direction the

dynamical systems view emphasizes that the composite neuro-

musculo-skeletal system is a nonlinear dynamical system that

can show interesting phenomena such as bifurcations, but

does not predict what nonlinear dynamics we should observe

in a task we don’t know very well, like a new task (Todorov,

E., 2004).

Often visual feedback is needed to make or perform

movements towards to a target. These movements are amongst

the most frequently performed movements of our movement

repertoire. These movements are most accurate when the hand

is visible throughout the movement towards a visible target

(Desmurget, Rossetti, Prablanc, Stelmach, & Jeannerod,

1995), but they become less accurate when the hand is not

visible during movement execution (Carrozzo, McIntyre, Zago,

5

& Lacquaniti, 1999) and are least accurate when the target

is no longer visible as movement unfolds (Lemay & Proteau,

2001). Studies investigating the role of visual information

in aiming movements towards remembered targets commonly use

one of three types of methodologies. The target was

presented and then: a) the lights of the experimental room

were turned off, b)spectacles worn by the participants

turned from transparent to translucent, or c) the

participants were asked to close their eyes, prior to

movement initiation. In the present study, the methodology

was used was very close to second type described above, as

the participants had visual feedback before the movement

initiation, but with the raising of the tool to point the

target, their visual field was interrupted from the special

goggles they had putted on their eyes. Regardless of the

methodology used, the authors concluded that the increase in

error noted when pointing to remembered targets in

comparison to visible targets was caused by the withdrawal

of visual information about target location (Lemay &

Proteau, 2001). Therefore, it is possible that the absence

6

of a visual background during movement execution may have

negatively affected the endpoint accuracy of a pointing

movement to a remembered target. In this regard, recent

evidence suggests that surrounding the target with a

structured visual background facilitates evaluation of the

distance (but not of the direction) between the starting

position of the hand and the target location when the

elements composing that background are located between the

starting base and the target location (Lemay, M., Gagnon, S.

& Proteau, L. 2004). The scientists recently reported

evidence that visual feedback from the hand contributes to

on-line control of reaching throughout the full extent of

the movement. A number of control strategies could be based

solely on feedback about hand position. A visual feedback

controller might steer to maintain a predetermined visual

path, making corrective adjustments whenever sensory

feedback indicates that the position of the hand has

deviated from the desired trajectory. Adaptation studies

provide evidence that the motor system does attempt to

maintain preferred kinematic trajectories, such as straight-

7

line paths (Shadmehr and Mussa-Ivaldi, 1994). Paillard

(1996), has argued that both position and motion feedback

contribute to controlling hand movements, but in different

movement phases: a fast homing-type strategy based on visual

motion is used during the initial part of movements, and a

slower position-based strategy is used for final end-phase

adjustments. The two-phase proposal is based on the

intuition that motion acuity remains high in the periphery,

whereas position acuity decreases sharply with retinal

eccentricity. A far target can become near if we can reach

it, no matter what means we use, the hand or a tool

(Saunders, J.A. & Knill, D.A., 2004). Yu & Buchanan (2004),

tell us that movement amplitude is a non specific control

parameter and the visual information for such movements is

used in the adjustment of antagonist activity (Van der

Meulen, J.H. et al, 1990).

The purpose of this study was to investigate the changes

in hand variability and the changes in tool-grip

variability, using a simple, but rather unusual, hand-tool

before and after the learning phase in comparison between a

8

very common and easy tool-grip and an unusual hold of the

tool, while vision is interrupted during the hand movement.

With this study we wanted to see the changes in hand and

tool movement accuracy and variability of target-pointing

movements after repeated movements to access accuracy and

variability before and after training.

We didn’t expect any changes in the hand movement or tool

movement variability after the learning phase, either for

the common grip or the unusual grip of the movement in all

the testing conditions (NH). We hypothesized that training

would reduce the tool variability but not necessary the hand

movement variability. In addition we expect to find that the

hand movement variability will increase after the training

phase. The hypothesis for this is that the subjects will be

focused to the target-pointing than the appropriate hand

movement, and may increased variability of the hand to

ensure accurate positioning of the tool.

METHODS

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Participants: 15 volunteer subjects were used for the purpose of

the study (11 male-4 female, 13 right-handed-2 left handed,

age 28,53±7,87 years), and they were separated randomly in

three experimental groups (Table 1).

Table 1: Testing details for the participants.

Age Hand SexGroup Averag

eSTDEV Right Left Male Female

Handle-hold 29,4 11,61 4 1 3 2Distant-hold 29,4 5,94 5 0 4 1Backward-

hold26,8 6,42 4 1 4 1

Total 28,53 7,87 13 2 11 4Materials: A simple, but unusual hand-tool was used. The tool

was very easy to use for the participants (Fig.1). Two

sensors (Polhemus System) were attached in the middle of the

metacarpus of the dominant hand and on the tool,

respectively. Each sensor measured six variables: The X, Y

and Z direction and the azimuth, the elevation and the roll

of the sensor after each movement. For the purpose of this

study, only the X and Y direction were used. The X direction

was the anterior-posterior direction to the participants’

body and the Y direction was the lateral direction to the

10

participants’ body. During the experimental phase, each

participant had to wear a pair of goggles (Plato Goggles),

which didn’t allow vision during the movement. The Plato

Goggles were linked to the starting position button so that

raising the tool from the starting position interrupted

automatically the visual field. In other words, the

participants didn’t have vision during pointing to the

target movement, but only before the initiation and after

the end of the movement. At the end of the movement, the

experimenter pushed an other button linked with the Plato

Goggles, which opened the visual field to the participants

and allowed them to get feedback about their movement.

HH- BH PH DHFigure1: The hand-tool

Procedure: Each participant was seated as comfortably as

possible in a chair in front of a desk. On the desk, there

was a white cardboard (60X50 cm) with a button used for the

11

starting position (SP) in the middle of the cardboard very

near to the body of the participant (Fig. 1A in the

Appendix). On the cardboard, there were also three big red

dots serving as targets at a distance of 15 cm away from the

SP. The three targets made a semicircle and the right (RT),

middle (MT) and left target (LT) were positioned at a 45˚

from each other. First, each participant performed the

movement from the SP to each target 30 times, in sequence

starting from the RT and finished to the LT (10 timesX3

targets) with the common grip (Pen-hold) and after that with

the unusual grip (Testing-hold). This procedure was the

baseline phase. After the baseline phase, the participants

did the learning phase in which they were trained only in

the testing condition without measurement for 40 times to

each target (3X40 times). The difference between the

baseline and the learning phase was that in the learning

phase the participants did 40 times the pointing movement to

each target and then went to the next target. In addition

the participants wore the Plato Goggles during the learning

phase but vision was allowed throughout practice. Finally,

12

after the learning phase the participants were tested using

the same procedure as the baseline but in this phase (Post-

Learning phase) the order of the trials was changed; they

did first the Testing-hold condition (10 times X3 targets)

and after that the Pen-hold condition (10 times X3 targets).

The participants were asked to do the pointing movements, as

accurate as possible, but not as fast as possible, because

the duration of the movements were not taken in to account.

Design: In the present study, we examined three experimental

groups with five subjects each. Each experimental group was

trained and examined in one testing condition but all three

groups were examined in the Pen-hold condition. Participants

were randomly assigned to one of the three training

conditions (Distant-hold, Handle-hold and Backward-hold

conditions) and each group was named from the training

condition. Thus we had the Distant-hold group (n=5), the

Handle-hold group (n=5) and the Backward-hold group (n=5).

The conditions were the Distant Condition (DC), in which the

participant hold the tool like a pen from the distant point

(DH in Fig.1), the Handle Condition (HC), in which the

13

participant hold the tool from the handle (HH in Fig.1) and

finally the Backward Condition (BC), in which the

participants hold the tool from the handle, but with the tip

of the tool under their elbow (BH in Fig.1). We measured the

hand-variability using the Standard Deviation (SD) of the

distance between the hand and the three targets (n=30

trials) and the tool variability defined as the SD of the

distance between the tool and the three targets (n=30

trials) and the mean tool absolute error (n=30 trials).

Absolute error was defined as the distance between the

sensor of the tool and the target, using the equation:

Error=

All three variables were analyzed using a 2X3 ANOVA with

repeated measures on Training (pre, post). The dependent

variables were the hand and tool variability, which were

calculated from the SD of the distance between the two

sensors and the target, and the absolute tool error, which

was calculated from the distance between the tool and the

targets. The independent variables were the two testing

14

phases (baseline and post-learning phases) and the three

experimental conditions (Distant-hold, Handle-hold,

Backward-hold). In addition we examined if there were any

differences in the Pen-hold condition between the baseline

(pre-training) phase and the post-learning phase, and among

the three experimental groups. Finally the pre-training

phase for the Pen-hold condition was compared for the tool

variability. The variance between subjects was compared with

the variance within each subject. In other words the SD for

subjects and the SD between the subjects means was

calculated (within and between subjects factor).

Data Analysis & Statistical Analysis: Before each measurement the

sensors were calibrated putting the sensor 1 (sensor on the

tool) first at the SP and after in each target. After the

data collection from the Polhemus System, the data were

transferred and transformed in Microsoft Excel files with

Matlab 7.0 for Microsoft Windows. The Polhemus System

collected six variables from each sensor (X, Y, Z direction

and azimuth, elevation and roll) and in addition the time

between each movement. With a special program of Matab 7.0

15

we took only the X and Y direction of each sensor. For the

absolute error, the distance between the tool and the target

was calculated using the Matlab 7.0 program. The data from

each participant were analyzed using the Microsoft Excel

program. Finally the statistical analysis was done using the

SPSS 10.0 for Windows statistical package.

RESULTS

In the present study, the differences in the pre- and

post-learning phase between the three testing conditions, as

well as the differences between the three testing conditions

in comparison with the pen-hold condition, were measured.

The differences looked for were the hand and the tool

variability, defined from the SD of the distance between

hand, tool and target in the forward and the lateral axes (X

and Y direction) and the absolute error between the tool and

the target for the three testing conditions .In addition the

differences in the Pen-hold condition, before and after the

learning phase in each testing condition as well as the

comparison with all subjects and the three experimental

16

conditions separated for the baseline phase of the Pen-hold

condition was examined.

Hand and Tool Variability

Tool variability-X direction: No significant differences between the

pre and post-learning phase in the tool variability were

found in the forward axis in comparison among the three

testing conditions (p>0.05). From the data (Table 2), we can

see that in the Handle-hold condition the variability was

increased while in the Distant-hold and Backward-hold there

were no differences before and after the learning phase.

Tool variability-Y direction: No significant differences between the

pre and post-learning phase in the tool variability were

found in the lateral axis (Y direction) in comparison among

the three testing conditions (p>0.05). After the learning

phase, the variability in the Handle-hold condition

decreased and increased in the Backward-hold condition while

no changes were observed in the Distant-hold condition

(Table 2).

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Table 2: Baseline and Post learning phase in testing

condition in tool variability

Distant-hold Baseline

Post learning phase

Direction x y x ySub ID : 1

1,059469

0,629625

4,4397406

2,337561

2 1,78668

7,57784

1,4555031

1,318095

3 0,66633

0,682287

2,4648796

0,661691

5 0,705733

0,77898

0,5303671

0,5138

6 0,487338

0,561921

0,6712042

0,489589

Handle-holdSub ID : 7

0,903959

0,846992

0,6120774

0,569401

10 0,663442

0,936904

0,7990104

0,786035

11 0,465034

0,464172

0,594801

0,764385

14 0,725956

0,622366

0,6876331

0,655233

15 0,534706

0,722586

0,6912727

0,769281

Backward-holdSub ID 4

1,475545

1,101538

1,6521843

5,798419

8 1,201128

0,632167

1,631607

1,047669

9 0,787275

0,551744

1,5404224

0,70447

12 0,972305

0,86971

1,2200237

0,613716

13 1,014478

0,790673

0,8227249

0,851925

Tool variability for the Pen-hold condition-X direction: No significant

differences after the learning phase were found for the Pen-

18

hold condition in the forward axis (X direction) and among

the three conditions (p>0.05). Only after the Backward-hold

condition, the variability in the Pen-hold condition

decreased, but in the other two conditions no changes were

found (Table 3).

Tool variability for the Pen-hold condition-Y direction: No significant

differences in Pen-hold condition (Y direction) after the

learning phase were found between the three conditions

(p>0.05). Like the X direction, only after the Backward-

hold the variability in the Pen-hold condition decreased,

but in the other two conditions no changes were found (Table

3).

Table 3: Baseline and Post learning phase in Pen-hold tool

variability

Distant-Hold Baseline

Post learning phase

Direction x Y x ySubject ID 1

1,65204

1,463724

2,111038

0,25534

2 0,547644

0,543752

0,351737

0,258408

3 0,910138

0,47337

0,348444

0,30825

5 0,476486

0,350551

0,378915

0,245511

6 0,395375

0,267663

0,282097

0,282767

19

Handle-hold7 0,4912

780,3667

440,6141

620,466647

10 0,681211

0,57396

0,965486

0,487795

11 0,424484

0,571845

0,387061

0,415336

14 0,643539

0,531257

0,57267

0,613552

15 0,515668

0,416812

0,738473

0,497489

Backward-hold

4 4,72362

8,745338

0,614162

0,466647

8 0,53344

0,574467

0,965486

0,487795

9 0,475685

0,632329

0,387061

0,415336

12 0,606672

0,414809

0,57267

0,613552

13 0,600696

0,548116

0,738473

0,497489

.

Hand variability-X direction: No significant differences were found

(p>0.05) in the comparison between the three testing

conditions, before and after the learning phase in the

forward axis (X direction). No changes were found in any

testing condition after the learning phase (Table 4).

Hand variability-Y direction: No significant differences were found

(p>0.05), also in the comparison between the three testing

conditions before and after the learning phase in the

20

lateral axis (Y direction). Like the vertical axis, no

changes in any testing condition were found (Table 4).

Table 4: Baseline and Post learning phase in testing

condition in hand variability.

Distant-hold Pre Post learning phase

Direction X y x ySub ID : 1

0,902534 1,130585

3,935467

2,320299

2

4,521559 4,896958

1,38383

0,87573

3 0,817564 0,700154

2,488164

0,945122

5 0,754459 0,791846

0,530367

0,5138

6 0,487338 0,561921

0,671204

0,489589

Handle-holdSub ID : 7

1,075425 2,170135

0,677855

0,921668

10 0,597356 1,774718

0,517599

0,89504

11 0,507711 0,519823

0,523253

0,596489

14 0,799451 1,041686

0,855322

0,905514

15 1,152314 1,8663 0,770844

0,723158

Backward-holdSub ID 4

4,200499 2,397459

2,813842

9,95163

8 1,23402 3,150227

1,511697

1,820551

9 1,224126 5,902264

1,945542

1,865922

12 1,07618 1,406727

1,002427

1,778659

13 1,03964 1,739993

1,027234

2,306269

.

21

Hand variability for the Pen-hold condition-X direction: No significant

differences were found (p>0.05) for the Pen-hold condition

after the learning phase in the testing condition in the

forward axis (X direction). No changes were found either for

the Handle-hold or the Distant-hold condition, while in the

Backward-hold condition the variability decreased (Table 5).

Hand variability for the Pen-hold condition-Y direction: Similar results

with the X direction were found for the lateral axis (Y

direction). No significant differences in the Pen-hold

condition in the comparison between before and after the

learning phase in the testing condition (p>0.05), but the

variability after the Backward-hold condition was decreased,

while no changes were found in the other two testing

conditions, the Distant-hold and the Handle-hold conditions

(Table 5).

Table 5: Baseline and Post learning phase in pen-hold hand

variability.

Distant-hold Pre Post learning phase

Direction x y x ySubject ID 1

1,635242

1,437285

2,361368

0,235533

2 0,6719 0,5705 0,4552 0,40929

22

06 79 1 73 1,7703

090,6016

840,7677

890,41252

45 0,4064

190,3973

580,3789

150,24551

16 0,3953

750,2676

630,2820

970,28276

7Handle-hold

7 0,574858

0,44618

0,777288

0,533507

10 0,657299

0,643891

0,943692

0,509214

11 0,321767

0,582538

0,405174

0,434408

14 0,877131

0,650831

0,736115

0,738609

15 0,774204

0,490139

0,659938

0,584481

Backward-hold4 5,1407

227,8188

160,7772

880,53350

78 0,7942

760,6167

060,9436

920,50921

49 0,5473

240,6549

850,4051

740,43440

812 0,6876

920,4065

310,7361

150,73860

913 0,6542

660,6184

770,6599

380,58448

1

Absolute Error for the tool

No significant differences were found between the

baseline and the post-learning phase in both the forward and

the lateral axes (X and Y direction), for the comparison

between the three experimental conditions and the Pen-hold

condition for the absolute error of the movement (p>0.05).

Because of these results, no t-tests or post-hoc tests were

23

made for the differences between the three experimental

conditions.

Absolute error in the forward axis (X direction) for the trained conditions:

Almost significant differences were found in the comparison

between the baseline and the post-learning phase for the

three testing conditions in the forward axis (F(2,12)=3.194,

p= 0.077). The absolute error decreased in the Handle-hold

condition and increased in the Distant-hold condition. No

changes were found for the Backward-hold condition (Fig. 2).

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Figure 2: Absolute error in comparison between the Baseline

and the Post learning phase in the X direction for the

testing conditions.

Absolute error in the lateral axis (Y direction) for the trained conditions: No

significant differences (p>0.05) were found for the

comparison between the baseline and the post-learning phase

for the three testing conditions in the lateral axis (Y

direction). Despite the absence of significant difference in

the absolute error in the Backward-hold condition, after the

learning phase, error was decreased, but for the Handle-hold

and the Distant-hold no changes were found (Fig.3).

25

Figure 3: Absolute error in comparison between the Baseline

and the Post learning phase in the Y direction for the

testing conditions.

Absolute error in the forward axis (X direction) for the Pen-hold condition: No

significant differences (p>0.05) were found in the

comparison between the baseline and the post-learning phase

for the Pen-hold condition in the forward axis (X

direction). No changes were found after the Handle-hold and

the Distant-hold conditions, but for the Backward-hold

condition, the absolute error was increased but in the

26

different direction: before the learning phase in the

testing condition, the participants tend to overshoot the

target with the tip of the tool, while after the learning

phase tend not to overshoot to the target (Fig.4)

Figure 4: Absolute error in for the Pen-hold condition (pre-

post-learning phase-Y direction).

Absolute error in the lateral (Y direction) axis for the Pen-hold condition:

Almost significant differences were found in the comparison

between the baseline and the post-learning phase for the

Pen-hold condition in the Y direction (F(2,12)=3.165,

27

p=0.079). The absolute error increased after the Distant-

hold training, but after the Handle-hold and the Backward-

hold conditions, no changes were found (Fig. 5).

Figure 5: Absolute error in for the Pen-hold condition (pre-

post-learning phase-Y direction).

Comparison in the Pen-hold performance for all the subjects

and the testing conditions:

The comparison of tool movement variability in the

baseline phase for the Pen-hold condition between all the

28

subjects together and the subjects in their testing group

separately showed that the variance within subjects factor

was larger than variance between each subject (Graph1). It’s

clear that the tool variability is bigger only in the

baseline of the Backward-hold condition but in total the

variability is bigger for all the subjects (Graph 2).

Tool variability in baseline betw een subjects and the testing conditions

0

0,5

1

1,5

1 2X-Y Direction

SD

SD for all subjects

SD for the testingconditions

Graph 1: Comparison between all subjects and the three

testing conditions in Pen-hold Baseline phase.

29

Tool variability in baseline betw een subjects and the three conditions separetely

00,51

1,5

1 2 3 4All subjects-Distant/Handle/Backw ard-hold

SD

X DirectionY Direction

Graph 2: Comparison between all subjects and the three

testing conditions separately in Pen-hold Baseline phase.

DISCUSSION

In the present study, no significant differences were

found between the baseline and the phase after the training

condition for each one of the three testing conditions or

the Pen-hold condition. A possible explanation for this

finding maybe is the fact that the learning phase was

designed in such way that it was totally different from the

30

testing phase. In the testing phase the sequence of the

movements was repeated after the end of the movements in the

three targets (10 timesX3 targets), but in the learning

phase the participants made 40 times the same movement to

the target before they go to the next target (3 targetsX40

times). There is a possibility that the sequence of the

movement and the mode of motor execution affect the learning

of the new motor activity. Another possibility is the fact

that negative motor transfer could exist for different motor

stimulus (Obayashi et al, 2004). Maybe the way that the

participants did the pointing movements affects strongly the

learning ability of them, in such way that when they did the

movement in different way in the post-learning phase, the

different motor program affects the hand movement. In

addition the interrupted visual field of the participants

during the pointing movements seemed not to affect the

movement execution because no differences were found in any

testing condition.

This experiment was done with participants, individuals

without any mental or motor problem. It would be interesting

31

to repeat this experiment in future studies, with

participants, people with motor movement coordination

problems and mainly in children with Developmental

Coordination Disorder or with autism and in generally

children with developmental problems or problems in the

cerebellum, in an attempt to find any differences after the

learning phase of this kind of experiments.

A very interesting finding is the fact that in the Pen-

hold condition for both forward and lateral axes (X and Y

direction), in the comparison between before and after the

learning phase only after the Backward-hold condition, the

hand and the tool variability were decreased very much, but

not significantly. Maybe there is a possibility that the

training phase in different tool grips affects the Pen-hold

performance with a great effect after the Backward-hold

condition. A possible explanation for this finding is that

the Backward-hold condition was very difficult to be

performed because the tip of the tool was under the

participants elbow and the participants made the pointing

movements more by chance rather than by purpose and because

32

of that, the Pen-hold condition for the post-learning phase

seemed very ‘easy’ for the participants so they performed

better.

Another interesting finding of this study is the fact

that despite the absence of significant differences, it’s

clear from the tables of the results (Tables 2, 3, 4 & 5)

that there were big individual differences between the

participants’ performance for all the testing conditions and

between the two directions. In general, the data analysis

showed no significant differences and we can say that these

findings are random and were created from the big

individuals differences between the participants.

In addition we tried to find if the between subjects

factor was bigger than the within subjects factor. For this

attempt the baseline phase for the Pen-hold condition was

examined. The tool variability in the target pointing for

all the subjects defined as the within subjects factor (SD)

and the tool variability in the target pointing in

comparison between the three testing conditions defined as

the between subjects factor. If within subjects factor was

33

bigger, more participants in each group needed for the

future studies to find significant differences. On the other

hand, if between subjects factor was bigger, more trials for

each participant in each experimental condition were needed.

The results didn’t show any statistical difference between

the two factors, but from graphs 1 and Graph 2 it’s clear

that the tool variability was bigger for all the subjects

(within subjects’ factor). From this finding we can say that

more participants are needed for each experimental group to

have more accurate and reliable results.

In the present study the Experimental Hypothesis did not

verified because we didn’t find any statistical significant

differences in the measurement of the Depended Variables and

on the other hand we must confirm the Null Hypothesis. Any

differences were found in the comparison between the pre-

learning phase (Baseline) and the post-learning phase for

all the measurements and any almost significant differences

maybe were made by chance and not as result of motor

learning for the pointing movements.

34

In conclusion we can say that more accurate and well

designed experiments will be done to have more reliable

results and the effects of motor learning in the hand

movement performance to be showed.

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APPENDIX

LT MT RT+ + +

SP ( )

Figure 1A: The targets on the cardboard.

38

Table 1A: Sample of Data Analysis (Microsoft Excel file).

Condition Target X direction

Y direction

Variability

Pen-Baseline

1 33,28449 -15,56722

48,85172

1 33,73643 -14,2744

48,01083

1 33,42084 16,728951

16,69189

1 32,54439 14,648546

17,89585

1 34,22188 13,786425

20,43546

1 33,72903 15,286512

18,44252

1 43,9045 4,00138 39,903122 25,89432 -

0,552346

26,44666

2 27,5935 0,5614819

27,03202

2 34,77428 -12,8337

0

47,60798

2 33,76354 -15,1071

8

48,87072

2 34,96653 -13,2939

5

48,26048

2 32,69515 -13,4134

3

46,10859

2 34,17489 -14,2769

9

48,45188

3 34,05006 16,152907

17,89715

3 28,58162 0,5933991

27,98822

3 28,16681 - 28,61277

39

0,445959

3 28,17609 0,2232948

27,9528

3 47,53833 -0,39648

3

47,93481

3 26,90479 0,0201715

26,88461

3 27,49983 -0,17675

5

27,67659

Test-Baseline

1 34,48636 15,837245

18,64912

1 34,04907 13,485299

20,56377

1 30,33386 12,691483

17,64238

1 29,92792 14,814522

15,1134

1 29,76784 12,594606

17,17323

1 28,05754 13,747579

14,30997

1 32,01244 14,014135

17,99831

1 30,3935 14,150015

16,24348

1 32,41052 14,49556

17,91496

1 28,12239 15,998617

12,12378

2 35,53282 -14,9025

1

50,43533

2 34,50259 -16,6823

1

51,18491

2 35,43769 -12,2626

8

47,70037

2 34,78015 -13,8178

1

48,59797

2 35,67748 -12,2303

8

47,90786

40

2 34,35573 -12,8683

6

47,22409

2 35,18735 -13,6333

3

48,82068

2 36,02712 -12,0247

7

48,05189

2 36,16554 -12,4695

1

48,63506

2 36,61262 -12,2818

1

48,89443

3 30,53613 -2,76465

33,30079

3 26,64792 -1,59041

1

28,23833

3 27,57796 -1,07029

8

28,64826

3 28,15766 -1,68301

8

29,84068

3 25,97632 -1,75553

1

27,73186

3 27,36675 -0,41592

5

27,78268

3 27,82526 -1,33562

4

29,16089

3 25,39134 -0,58775

5

25,9791

3 27,09937 -1,28915

7

28,38853

3 28,81702 -1,36608

4

30,1831

41

Table 2A: Sample of Data Analysis for the variability pre-post training

Distant-Hold M1 M2baseline ALL x y x ySub ID : 1

1,059469

0,629625

0,902534 1,130585

2 1,78668

7,57784

4,521559 4,896958

3 0,66633

0,682287

0,817564 0,700154

5 0,705733

0,77898

0,754459 0,791846

6 0,487338

0,561921

0,487338 0,561921

Handle-Hold M1 M2baseline ALL x y x ySub ID : 7

0,903959

0,846992

1,075425 2,170135

10 0,663442

0,936904

0,597356 1,774718

11 0,465034

0,464172

0,507711 0,519823

14 0,725956

0,622366

0,799451 1,041686

15 0,534706

0,722586

1,152314 1,8663

Backward-Hold

M1 M2

baseline ALL x y x ySub ID 4

1,475545

1,101538

4,200499 2,397459

8 1,201128

0,632167

1,23402 3,150227

9 0,787275

0,551744

1,224126 5,902264

12 0,972305

0,86971

1,07618 1,406727

13 1,014478

0,790673

1,03964 1,739993

42

Distant-Hold M1 M2testing ALL x y x ySub ID : 1

4,439741

2,337561

3,935467 2,320299

2 1,455503

1,318095

1,38383 0,87573

3 2,46488

0,661691

2,488164 0,945122

5 0,530367

0,5138 0,530367 0,5138

6 0,671204

0,489589

0,671204 0,489589

Handle-Hold M1 M2testing ALL x y x ySub ID : 7

0,612077

0,569401

0,677855 0,921668

10 0,79901

0,786035

0,517599 0,89504

11 0,594801

0,764385

0,523253 0,596489

14 0,687633

0,655233

0,855322 0,905514

15 0,691273

0,769281

0,770844 0,723158

Backward-Hold

M1 M2

testing ALL x y x ySub ID 4

1,652184

5,798419

2,813842 9,95163

8 1,631607

1,047669

1,511697 1,820551

9 1,540422

0,70447

1,945542 1,865922

12 1,220024

0,613716

1,002427 1,778659

13 0,822725

0,851925

1,027234 2,306269

43