SUGISAKAMASANORI

Journal of Robotics, Networking and Artificial Life
Vol. 9(2); September (2022), pp. 121–127
ISSN (Online):2352-6386; ISSN (Print):2405-9021
https://alife-robotics.org/jrnal.html

Research Article

Development of “iWakka Game” for evaluation of hand dexterityin children with developmental coordination disorder
Masakazu Nomura1, Moe Nishiya2, Yoshifumi Morita1, Hideo Yamagiwa3

1
Department of Electrical and Mechanical Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku,
Nagoya, Aichi 466-8555, Japan
2
Electrical and Mechanical Engineering Program, Department of Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Gokisocho, Showa-ku, Nagoya, Aichi 466-8555, Japan
3
Tokyo Metropolitan Tobu Medical Center, 3-3-25 Shinsuna, Koto-ku, Tokyo, 136-0075, Japan

ARTIC LE INFO
Article History
Received 25 November 2021
Accepted 24 March 2022

Keywords
Rehabilitation
Hand dexterity
Evaluation

ABSTRACT

Our previous study developed a testing and training device, “iWakka,” for the adjustability forgrasping force. Moreover, we developed “iWakka Game” for autistic patients. In this study, weinvestigated the applicability of the iWakka Game in children with developmental coordination
disorder (DCD). We developed a small grasping body and improved its evaluation method. It was
experimented on four children with DCD. Consequently, they completed the evaluation task,
which enabled the extraction of hand dexterity characteristics.

© 2022 The Author. Published by Sugisaka Masanori at ALife Robotics Corporation Ltd
This is an open access article distributed under the CC BY-NC 4.0 license(http://creativecommons.org/licenses/by-nc/4.0/).

Children with developmental coordination
disorderdiagram of the system. The control box acquires thevoltage value of strain signal and transmits it to the iPad
via Bluetooth. The iWakka Viewer converts the voltage
value into the corresponding grasping force, and shows thegrasping force and the target grasping force on the iPad

1. Introduction
In daily life, hands and fingers play an important role suchas grasping a cup and handling chopsticks and forks with
an appropriate force. The adjustability for grasping force(AGF), defined in Ref. 1, is one of the motor functions of
the fingers and is the ability to grasp an object with anappropriate force. In our previous study, a training andtesting device, “iWakka,” for the AGF was developed.1
iWakka comprises a grasping body, “Wakka,” and ameasurement device. The measurement device compriseda control box, an iPad, and “iWakka Viewer.” The control
box consists of an amplifier circuit, a microcontroller
board, and a BLE module. Figure 1 shows the block

Corresponding author’s E-mail: m.nomura.733@nitech.jp, m.nishiya.456@nitech.jp, morita@nitech.ac.jp, ot_trc@mtrc.jp

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Fig. 1. The block diagram of the system.

movement speed is almost the same. Gonsalves et al.
found that 10-12-year-old children with DCD had a slower
hand path speed, greater wrist extension, and greater elbow
flexion than typically developed children while playing
VR games.10 However, few studies have focused on thecharacteristics of hand dexterity using game-based devices.
The purpose of this study was to investigate theapplicability of the iWakka Game to children with DCD
and to propose a small-sized device and an evaluation
method of the characteristics by subdividing hand
dexterity.

screen. They adjusted their grasping force to be closer tothe target grasping force. The measurement sampling time
was 0.1 s, the measurement range was 0–500 g, and theresolution was 1.6 g. Morita et al. and Toshima et al.
observed from Refs. 2 and 3 that adding iWakka toconstraint-induced (CI) movement therapy had therapeutic
effects in patients after a stroke. To apply iWakka to
autistic patients, we also developed “iWakka Game” byimproving the game quality of the original one with theLodz University of Technology and the Center of Autism
Diagnosis and Therapy, Lodz, Poland.4
Developmental coordination disorder (DCD) is acommon neurodevelopmental disorder characterized by
impairments in the development of both fine and grossmotor skills.5 Asonitou et al. showed that children with
DCD differed significantly from those without DCD
performing at a lower level on motor and cognitive tasks.6
To improve their skills, motor interventions based on
virtual reality is preferable for children with DCD because
training with Nintendo Wii may be particularly beneficial
for children, owing to its motivating aspects.7 Moreover,
Waelvelde et al. revealed that children with DCD were
delayed in ball catching and seemed to use different
movement strategies compared to younger, typicallydeveloping children.8 Because grasping is the basic ability
for various activities, therapists need to evaluate thecharacteristics of hand dexterity and plan more effective
training for their hands. Li et al. designed a marker-lessvisual-motor tracking system to capture the body tomonitor children’s behavior in fine motor tasks.9 They
found that the visual movement speed of children with
DCD or at risk of DCD is slower than that of typicallydeveloping children to focus on the target while their hand

2. iWakka GameThe iWakka Game shown in Figure 2, was developed totrain and test the grasping force. The brown bird in theiWakka Viewer in Figure 3 rises when the Wakka isgripped and falls when it is released. When a task begins,

Fig. 2. iWakka Game.

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Table 1. Comparison of the small-sized andoriginal Wakka.

Spring constant [N/m]Outer diameter [mm]Height [mm]Weight [g]Small-sized
Wakka

5.96 × 102
54
80
81

Original
Wakka

4.82 × 102
65
80
112

Before testing using the iWakka Game, a preliminary
experiment was conducted to verify its applicability tochildren with DCD. We determined the three parameters
required to complete the tasks appropriately. The distance
between the bird and cloud was 100 g. The measurement
range was 150–400 g. The speed was 2.97 mm/s from theright to the left of the screen on the iPad.

Fig. 3. iWakka Viewer.

the target waveform with red stars moves from the right tothe left. The participants were instructed to acquire redstars with the bird’s beak by controlling its vertical
position and being careful not to contact the cloud placed
above and below the bird. The waveform pauses when thebird contacts the cloud, which means that the error
between the value of the target waveform and the bird’s
vertical position exceeds a certain threshold. It resumes
when the bird leaves the cloud. This is an assist functionthat encourages the participants to reduce errors. In otherwords, the total time of contact is considered to be theassist time. The contact state is referred to as the assisted
period.
The therapist determined three setting parameters anda target waveform considering the patient’s condition. The
three parameters are the distance between the bird and thecloud, the measurement range, and the speed at which the
waveform flows from the right to the left. The distance
between the bird and the cloud corresponds to theallowable force that does not cause the waveform to pause.
The iWakka Game has nine types of waveforms, such as
staircase, slope, and sine waves.
The AGF was evaluated from the mean absolute error
between the value of the target waveform and the bird’s
vertical position, which indicates the grasping force bygrasping the Wakka.

3.2. Grasping device
A small-sized grasping body Wakka was developed toreduce the outer diameter by 83%. This was decided basedon the requirements of the therapists and the ratio of thelength from the wrist to the tip of the middle finger. The
average ratio is 190–220 mm for adults and 150–190 mm
for elementary school children. The relationship between
the amount of deformation and the force of the device islinear. Table 1 lists a comparison of the small-sized andoriginal Wakka. The spring constant of the small-sized
Wakka was 5.96 × 102 N/m, implying that grasping it witha force of 60.8 g produced a deformation of 1 mm.
3.3. Evaluation method for hand dexterity
We propose an evaluation method to extract hand dexterity,
in addition to the number of stars acquired in the previous
study. The waveform shown in Figure 4 was selected toevaluate the characteristics of hand dexterity. Total timewas 93 s and the total number of stars was 47.
3.3.1. AGF

3. iWakka for Children with DCD
3.1. Setting parameters and a target waveform
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We evaluated the AGF for each isometric muscle activity(IC) to hold an object with a constant grasping force,
concentric muscle activity (CC) to grip it while increasing
the grasping force, and eccentric muscle activity (EC) torelease it while decreasing the grasping force. The
waveform was subdivided into the IC, CC, and EC
sections and the ranges of the grasping forces. The IC wasevaluated twice at 150 g. The first evaluation was
performed 3 s after the start of the experiment. The CC andEC were evaluated in four sections of the grasping force

Fig. 4. Target waveform and sections to be evaluated.

range. The average absolute error between the grasping
force and target grasping force in each section was
calculated as the 𝐴𝐴𝐴𝐴𝐴𝐴, as shown in Eq. (1).
𝐴𝐴𝐴𝐴𝐹𝐹(∗) =

𝑁𝑁(∗)

1
�|𝑓𝑓𝑑𝑑 (𝑘𝑘) − 𝑓𝑓(𝑘𝑘)| [g]
𝑇𝑇(∗)
𝑘𝑘=1

Table 2. Subject information.

(1)

where (∗) denotes the section, 𝑓𝑓(𝑘𝑘) denotes the measured
grasping force, and 𝑓𝑓𝑑𝑑 (𝑘𝑘) denotes the target grasping
force. 𝑇𝑇(∗) denotes the time taken for the section and 𝑁𝑁(∗)
denotes the number of data points for the section. 𝑇𝑇𝐼𝐼𝐼𝐼1 is
6s, 𝑇𝑇𝐼𝐼𝐼𝐼2 is 9 s, and 𝑇𝑇 for each of the CC and EC sections
is 5 s. Because the measurement sampling time is 0.1 s,
𝑁𝑁𝐼𝐼𝐼𝐼1 is 60, 𝑁𝑁𝐼𝐼𝐼𝐼2 is 90, and 𝑁𝑁 for each of the CC and EC
sections is 50. However, if the bird contacts the cloud, then𝑇𝑇(∗) and 𝑁𝑁(∗) is extended to the section. This implies thatthe time of contact with the cloud was included in thecalculation. The target grasping force at the start of thecontact continues until the end of the contact. The smaller
the AGF, the higher is the AGF ability.

Sub
ject

Age

Sex

1

6

Male

2

5

Male

3

7

Male

4

9

Male

DiseaseDCD, and at riskof Dysarthria
DCD
DCD, ASD, andADHD
At risk of DCD

MABC-2
Manual Dexterity
6
6
10
5

4. Experiments and Results
4.1. Subjects
The four patients are listed in Table 2. All patients werediagnosed with DCD or were at a risk of developing DCD.
The iWakka was used with the dominant hand. The
MABC-2 is designed to identify and describe impairmentsin the motor performance of children and adolescents 3 to
16 years old.11 Three types of assessment items were used.
The maximum score for each item was 19. Manual
dexterity is one of them, and the test content for each isdifferent for the three bands: 3 to 6, 7 to 10, and 11 to 16
years old.

3.3.2. AGF in unassisted periods
The longer the assist periods when the bird is in contact
with the cloud, the larger the 𝐴𝐴𝐴𝐴𝐴𝐴. In other words, whenthe AGF is evaluated in both the assisted and unassisted
periods using Eq. (1), the AGF in the assisted periods
significantly affected that in the unassisted periods.
Focusing on the fact that the grasping force can be adjusted
appropriately even in the unassisted periods, we evaluatedthe AGF only in the unassisted periods, which is referred
as to the 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢 . The 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢 was calculated using Eq. (1).
Note that 𝑇𝑇(∗) and 𝑁𝑁(∗) do not include the assisted periods
and are constant values. Moreover, we also evaluated theassist time for each section. The assist time was defined as
the sum of the times the assist was performed in eachsection.

4.2. Characteristics of hand dexterity
Figures 5, 6, 7, and 8 show the 𝐴𝐴𝐴𝐴𝐴𝐴 and 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢 of
Subjects 1, 2, 3, and 4, respectively. Figure 9 shows theassist time of all subjects. Figure 5 shows that the 𝐴𝐴𝐴𝐴𝐴𝐴 and
𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢 in all EC sections were greater than in all CC124

sections respectively. This means that Subject 1 was worse
at decreasing the grasping force than at increasing it.
Figure 9 shows that Subject 1 required assistance only in
the EC4 and IC2 sections. Therefore, the 𝐴𝐴𝐴𝐴𝐴𝐴 and 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑎𝑎
were the same except in the EC4 and IC2 sections. On theother hand, Figure 9 shows that Subject 2 required
assistance in the CC1, CC2, CC3, and EC1 sections. Thismeans that Subject 2 was worse at increasing the grasping
force than at decreasing it. Figure 6 shows that the 𝐴𝐴𝐴𝐴𝐴𝐴 in
the CC1, CC2, CC3, and EC1 sections were greater thanthe 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢 respectively. This means that with assistance,
Subject 2 was able to adjust his grasping force in theunassisted periods. Focusing on IC sections, the 𝐴𝐴𝐴𝐴𝐴𝐴 of
Subject 1 in the IC2 section was greater than in the IC1
section and the assist time occurred in the EC4 and IC2

Fig. 5. AGF of Subject 1.

Fig. 6. AGF of Subject 2.

Fig. 8. AGF of Subject 4.

Fig. 7. AGF of Subject 3.

Fig. 9. Assist time of each section.

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movements necessary for daily life. This result leads
therapists to plan more effective hand dexterity training.
Since the applicability of the iWakka Game tochildren with DCD was demonstrated, our future studies
will involve collecting data on healthy children by age andon children with DCD by age and disability to gain
knowledge.

Table 3. Number of stars acquired.
Subject

Number of stars acquired

1

32

2

32

3

35

4

41

Acknowledgements
We would like to thank Professor Grzegorz Granosik andAssistant Professor Igor Zubrycki of the Lodz Universityof Technology, Poland, for their helpful advice on thispaper.

sections. It indicates that he had a low ability to hold at 150
g after decreasing the grasping force. The 𝐴𝐴𝐴𝐴𝐴𝐴 and 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢
of Subject 3 were the same shown in Figure 7 because he
did not need any assistance in all sections. This means thathe could adjust their grasping force appropriately withoutcausing significant errors. Subject 4 needed little
assistance because the assist time is 0.2 s at EC1. 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢
was 2.1 g smaller than 𝐴𝐴𝐴𝐴𝐴𝐴 at EC1 shown in Figure 8. It
was possible to extract hand dexterity by comparing
different sections of the 𝐴𝐴𝐴𝐴𝐴𝐴 . However, the 𝐴𝐴𝐴𝐴𝐴𝐴 wasinsufficient because it couldn’t evaluate the effect of theassist. Using the 𝐴𝐴𝐴𝐴𝐹𝐹𝑢𝑢𝑢𝑢 and assist time in addition to the
𝐴𝐴𝐴𝐴𝐴𝐴 allowed us to evaluate the effect of the assist.
Table 3 lists the number of stars acquired. The numberof Subjects 1 and 2 was the same. However, they had
different hand dexterity characteristics, as shown in Figure
5, 6 and 9. Subject 4 acquired more stars than Subject 3.
Consequently, it was observed that assistance was
effective in helping subjects acquire stars in the weaksections.
5.

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Conclusion

We observed that the iWakka Game was applicable
not only to autistic patients but also to children with DCD,
aged 5–9 years, by using the small-sized grasping device,
Wakka, and appropriate setting parameters. Moreover, theproposed evaluation method enabled the extraction ofhand dexterity characteristics for each child. By
subdividing the AGF into the IC, CC, and EC sections, andby considering assistance, we were able to evaluate thesubjects’ hand dexterity from various perspectives
compared to the evaluation by the number of stars. They
had different characteristics of holding, gripping, andreleasing in each range of grasping force, which they were
not good at. Improving each ability can enhance the hand126

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Mr. Hideo Yamagiwa
He is a Pediatric Occupational
Therapist at Tokyo Metropolitan
Tobu Medical Center, Japan. He
graduated from Chiba Medical
Technology College, Japan.

Authors Introduction
Mr. Masakazu Nomura
He received his Master's degreefrom the Department of Electricaland Mechanical Engineering,
Graduate School of Engineering,
Nagoya Institute of Technology,
Japan in 2020. He is currently aDoctoral course student at Nagoya
Institute of Technology, Japan.

Ms. Moe Nishiya

Dr. Yoshifumi Morita

She received her bachelor’s degreefrom the Department of Electricaland Mechanical Engineering,
Nagoya Institute of Technology,
Japan in 2020. She is currently amaster course student at Nagoya
Institute of Technology, Japan.

He is a Professor of Department ofElectricalandMechanicalEngineering, Graduate School ofEngineering, Nagoya Institute ofTechnology, Japan. His researchinterests are robot motion control,
support control for humanmachine cooperative system, andrehabilitation support robot.

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