II-33
ASSESSMENT OF GRIP FORCE CONTROL IN
PATIENTS WITH MUSCULAR DYSTROPHY
OCENJEVANJE KOORDINACIJE SILE PRIJEMA PRI BOLNIKIH Z MIŠIČNO DISTROFIJO
Gregorij Kurillo1, Tadej Bajd2, Anton Zupan2
1 Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000 Ljubljana, Slovenia
2 Institute for Rehabilitation, Republic of Slovenia, Linhartova 51, 1000 Ljubljana, Slovenia
Arrived 2004-02-16, accepted 2004-04-15; ZDRAV VESTN 2004; 73: Suppl. II: 33–8
Ključne besede: prijemanje; sila prijema; funkcionalnost
roke; mišična distrofija; sledenje
Izvleček – Izhodišča. Poglavitna slabost obstoječih metod za
ocenjevanje funkcionalnosti roke v ožjem smislu je predvsem
v subjektivnosti ocenjevanja, ki je v veliki meri odvisno od
izkušenosti terapevta. Z računalniškimi meritvami je mogoče
povečati objektivnost in natančnost postopkov merjenja sile
prijema ter ocenjevanja funkcionalnosti roke.
Metode. V raziskavi smo z računalniškim merilnim sistemom
analizirali koordinacijo sile prijema pri 12 bolnikih z mišič-
no distrofijo. Merilni sistem vključuje računalnik ter meril-
nik sile prijema, kjer je z različnimi nastavki mogoče natančno
izmeriti silo pri različnih prijemih. Merilnik je bil vključen v
nalogo sledenja sile prijema, kjer je pacient s prilagajanjem
sile prijema sledil različnim tarčam na zaslonu. Ocenjevali
smo sledenje sile pri dveh različnih nalogah: sledenje linear-
no naraščajočega signala in sinusnega signala z uporabo
petih različnih prijemov (cilindrični, lateralni, pincetni, uščip-
ni ter sferični prijem).
Rezultati. Pri sledenju linearnega signala smo ocenjevali mak-
simalno silo, ki jo je bolnik dosegel pri posameznih prijemih.
Iz rezultatov smo analizirali tudi utrujanje mišic pri izvaja-
nju naloge. Pri sledenju sinusnega signala smo ocenjevali
natančnost koordinacije sile prijema, ki je povezana s senzo-
motoričnim sistemom funkcije prijemanja. V članku so prika-
zani rezultati sledenja sile pri petih prijemih ter primerjava
med dominantno in nedominantno roko. Pri večini bolni-
kov je bila natančnost največja pri cilindričnem in lateral-
nem prijemu. Rezultati niso pokazali razlik v natančnosti
glede na dominantnost roke.
Zaključki. S predstavljenim merilnikom sile je mogoče na-
tančno meriti silo pri različnih prijemih. Rezultati so poka-
zali, da je opisani merilni sistem mogoče uporabiti za ocenje-
vanje natančnosti koordinacije sile prijema pri bolnikih z
mišično distrofijo, ugotavljanje prisotnosti tremorja ter oce-
njevanje utrujanja posameznih mišic.
Keywords: grasping; grip force; hand functionality; muscu-
lar dystrophy; tracking
Abstract – Background. The majority of hand functionality
tests are based on qualitative assessment which largely de-
pends on the experience of the therapist. Computer-assisted
methods can provide more objective and accurate measure-
ments of the grip force and other parameters related to grasp-
ing.
Methods. We analysed the grip force control in 12 patients
with muscular dystrophy using the tracking system developed.
The system consists of a grip-measuring device with end-
objects assessing the force applied in different grips. The
device was used as input to a tracking task where the patient
applied the grip force according to the visual feedback from
the computer screen. Each patient performed two tasks which
consisted of tracking a ramp and sinus target.
Results. We analysed the maximal grip force as assessed in the
ramp task and the tracking accuracy of the sinus task. The
results are compared among five different grips (cylindrical,
lateral, palmar, pinch and spherical grip), applied with domi-
nant and non-dominant hand. The results show no signi-
ficant difference in tracking accuracy between the dominant
and non-dominant hand.
Conclusions. The results obtained in tracking the ramp target
showed that the method could be used for the assessment of
the muscle fatigue, providing quantitative information on
muscle capacity. The results of the sinus-tracking task showed
that the method can evaluate the grip force control in dif-
ferent types of grips, providing information on hand dexteri-
ty, muscle activation patterns or tremor.
Introduction
Grasping is one of the most important and complex human
activities. The functionality of the hand can be promoted by
using different objects or tools for the interaction with the
environment. The key goal of grasping is a stable grasp of the
object where the fingers have to apply forces that satisfy con-
straints of the object and the task (1). The accomplishment of
the task depends on the selection of suitable hand posture and
accurate grip force control where different muscles of the
hand are activated in synergy to produce appropriate pres-
sure on the object surface (2). Accurate grip force control is
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essential in performing daily activities such as grasping of fra-
gile objects, resistance to external forces (e. g. holding a spoon)
and applying movement to the object (e. g. turning a knob,
opening a jar) (2).
The functionality of the hand depends on the motion range of
the fingers and wrist, grip strength and dexterity (3). Central
nervous system injury, hand injury or muscular weakness can
greatly reduce the ability to grasp and manipulate objects in
daily activities. In rehabilitation and therapy, different tests are
used to assess patient’s muscle strength and hand mobility (3,
4). The assessment of individual muscles activity (e. g. EMG)
and joint motion range can provide only a partial information
on patient’s hand functionality because of difficult muscle iso-
lation during the assessment, the influence of patient’s motiva-
tion and other physiological and biomechanical factors affect-
ing the clinical assessment (3–6). The grip-strength testing is
mainly focused on the measurement of the maximal voluntary
grip force that provides information on short-duration muscle
strength (7). The grip strength is usually assessed using diffe-
rent mechanical dynamometers that measure the level of the
applied grip force providing no information on the direction
and dynamics of the force. The dynamometers used are often
not suitable for accurate measurements of low-level forces
because their measurement range is too large in respect to
the force applied (7). Possibility of detection of small changes
in grip strength following therapy or progression of disease is
therefore limited. In daily living 90% of activities can be
accomplished by the grip forces under 40 N (8) and in this
context the maximal voluntary grip force reflects only a par-
tial information on the hand functionality (3). The functionality
of the hand depends on the functional force that can be
applied while manipulating the object. In precision grips the
requirement is mainly on the accuracy of the applied force,
while in power grips the level of the force is more important
(1).
A drawback of the existing tests originates mainly from the
subjectivity of the assessment which largely depends on the
experience of the therapist. An objective hand functionality
assessment is important in evaluation of the progress of the
therapy. Computer assisted methods can increase the accu-
racy and objectivity of the assessment by providing quantita-
tive measurements on sensory-motor functions of the hand
which affect the grip force control and dexterity. In this paper
we propose a grip-force tracking system for the assessment
of sensory-motor functions related to grasping. Tracking can
be defined as a controlled movement or force application with
visual feedback on the performance of the task (9). Tracking
tasks have been used previously to assess the development of
human sensory-motor functions (10), coordination of grip
force in Parkinson’s disease (11), to train hemiplegic patients
(12) and to assess grip force control in healthy persons (13).
Most of the previous studies focused only on one type of grip.
We believe that it is essential to evaluate different grips used
in performing daily activities to obtain an objective informa-
tion on hand functionality.
Instrumented objects have been proposed previously (14–
16) to assess the grip forces acting on objects which are in
shape and size similar to the objects used in daily living. Such
instruments allow real-time measurement of the grip force
while performing different tasks. We have built a grip-mea-
suring device with end-objects of different shapes to assess
the forces in different types of grips. The selection and size of
the end-objects was based on the upper extremity part of the
Fugl-Meyer evaluation method (4). The grip-measuring
device allows real-time measurement of the grip force provid-
ing information on direction and dynamics of the applied force
(17). The device was used as input to a tracking task, where a
person applied the grip force according to the visual informa-
tion from the computer screen. The proposed tracking sys-
tem was used to evaluate grip force control in 12 patients with
muscular dystrophy (MD). We studied the grip force control
in five different grips: cylindrical, lateral, palmar, pinch and
spherical grip.
Methods
A. Grip-Measuring Device
We designed a grip-measuring device (Figure 1) to assess the
grip forces in different type of grips. The instrument is based
on the force transducer JR3 (JR3, Inc., Woodland, USA) capa-
ble of measuring three-dimensional forces, providing infor-
mation on the grip strength and direction of the applied force.
The sensor is attached to a metal construction allowing the
transfer of forces from the end-object to the sensory unit. The
grip-measuring device can be fitted with different end-objects
which have the shape of objects used in daily living, such as a
pencil, thin plate, ball and cylinder. Each measuring object is
divided along the longitudinal axis into two symmetrical parts
that shape into the full object when attached to the device.
The selection and size of the objects was based on the upper
extremity part of the Fugl-Meyer hand evaluation method (4).
When the person grasps the end-object, the force sensor
measures the grip force on the object. The grip-measuring
device was calibrated to measure forces up to 100 N (equiva-
lent mass of 10 kg). The resolution of the measured force is
0.01 N (0.001 kg) in the measuring range of 0–25 N (0–2.5
kg), 0.03 N (0.003 kg) in the range of 25–50 N (2.5–5 kg) and
about 0.05 N (0.005 kg) in the range of 50–100 N (5–10 kg).
The device was connected to a personal computer with a data
acquisition card where the grip force data were sampled with
a frequency of 100 Hz.
Figure 1. The grip-measuring device with different end-
objects used for the measurement of grip forces (above). The
block scheme of the grip-force tracking system for the hand
functionality assessment (below). The patient applies the grip
force to the grip-measuring device according to the visual
feedback from the computer screen.
B. Tracking Task
The goal of the tracking task was to apply the grip force on the
grip-measuring device according to the visual information from
D02.p65 5.6.2004, 5:0134
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the computer screen (Figure 1 below). The person was pre-
sented with a target signal indicated in blue colour and the
measured grip force response indicated in red colour. A blue
ring located in the centre of the screen moved vertically
according to the target signal, leaving a blue trail that moved
from the centre of the screen to the left representing the time
history of the signal. The measured response was presented
with a red spot whose vertical position corresponded to the
grip force applied perpendicularly to the end-object surface
of the grip-measuring device. The patient’s task was to bring
the red spot inside of the blue ring and to track the position of
the ring by applying the appropriate grip force to the grip-
measuring device. The tracking task was programmed in
Matlab-Simulink (The MathWorks, Inc., Natick, USA). The com-
plexity of the tracking task could be adjusted by selecting the
shape of the target signal (e. g. ramp, sinus, rectangular shape),
setting the level of the required grip force and changing dy-
namic parameters of the target (e. g. frequency, speed). Se-
lecting the appropriate task allows the assessment of the grip
force control and dexterity in different grips, quantification of
muscle fatigue, detection of tremor and assessment of reac-
tion time (9).
C. Experiments
We analysed the grip force control in 12 right-handed patients
(P1–P12; 3 female, 9 male patients) with muscular dystrophy.
We assessed the tracking performance in five different grips:
pinch, palmar, lateral, spherical and cylindrical grip, evaluat-
ing the dominant and non-dominant hand. Two different track-
ing tasks were selected for the experiment. The first task con-
sisted of tracking a ramp target that increased in 15s from the
initial value of 0N to the final value of 30N for the pinch and
palmar grip, 60N for lateral and 70N for spherical and cylindri-
cal grips. The patient was instructed to follow the target as
long as possible and if unable to exert higher force, to keep
the grip until the end of the trial which lasted 32 seconds. The
second task consisted of tracking a sinus target with frequency
of 0.1Hz. The amplitude of the signal was set at about 30% of
the patient’s maximal grip force as assessed in the ramp trial.
The patient was asked to follow the moving target as accura-
tely as possible by applying an appro-
priate force on the grip-measuring de-
vice. Each trial lasted 32 seconds.
During the test the patient was sitting in
a wheelchair in front of the computer
screen, with the forearm resting on a
hand-support. For the maximal perfor-
mance of the grip the elbow was posi-
tioned in a 90° flexion and the shoulder
was in a neutral position (6). The grip-
measuring device was located in the
proximity of the patient’s hand to allow
a neutral wrist position. If a patient was
unable to perform the grip within the
required hand and arm position due to
muscle contractures, the position and
orientation of the grip-measuring device
were adjusted to find the most adequate
posture. The patients were required to
maintain consistent grip during the as-
sessment and were not allowed to use
‘trick’ movements. During the test the
patient’s hand posture was monitored
by a therapist. The patients performed
several test trials to get familiar with the
task and the measuring procedure. Most
of the patients required about 3–5 test
trials of each task. The patients then
performed two trials of each tracking task with 30–45 s of rest
in between. The better result of the two trials was considered
in further analysis.
D. Analysis
The performance of the ramp task was quantified by the aver-
age maximal grip force sustained for the duration of 5s at the
point where the target first reached its maximal value (time
interval 17–22 s) (Figure 2). The assessed grip force was used
also for the selection of the amplitude for the sinus task where
the amplitude was set at about 30% of the maximal force as
obtained in the ramp task.
We assessed the performance of the sinus tracking by calcu-
lating the relative root mean square error (rrmse) between
the sinus target Y
T
 and the measured output force Y
O
 (9):
Figure 2. The results of the ramp tracking as assessed in the patients P9 and P12
using cylindrical and palmar grip. The results show that both patients were able to
exert the required grip force level in cylindrical grip but their force decreased be-
cause of muscle fatigue. Both patients produced much lower force in palmar grip.
The error was calculated over a time period T (30 s interval),
where the initial two seconds of the trial, used for the adjust-
ment of the grip, were excluded from the analysis. The rela-
tive tracking error describes the accuracy of the tracking which
depends on the control of the muscles used in the particular
grip. The error is normalised by the maximal value of the tar-
get signal to allow an objective comparison between the re-
sults obtained in different grips and patients.
Results
The results of the ramp test reflect the patient’s grip force
control when gradually increasing the grip force. The ramp
test can be also used to assess the muscle fatigue while using
different grips. Figure 2 shows the tracking results of the ramp
test as performed by two patients (P9 and P12) who showed
similar results in the maximal grip force value while using the
cylindrical and palmar grip. The maximal grip force of the
patient P9 in the cylindrical grip was about 65N. The patient
KURILLO G, BAJD T, ZUPAN A. ASSESSMENT OF GRIP FORCE CONTROL IN PATIENTS WITH MUSCULAR DYSTROPHY
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II-36 ZDRAV VESTN 2004; 73: SUPPL II
Figure 3. The maximal grip forces of the 12 patients with muscular dystrophy as
assessed in the ramp task compared within different grips. (* Patient was not able to
perform the indicated grip.)
Figure 4. The results of the sinus track-
ing as assessed in the patients P9 and
P12 using cylindrical and palmar grip.
The tracking results of the first patient
show more abrupt muscle activation
pattern that unables the patient to gra-
dually increase or decrease the grip
force. Both patients produced larger
tracking error in palmar grip as com-
pared to the cylindrical grip.
was not able to retain the same force
level until the end of the trial. The de-
crease of the grip force was about 18%
in 15s. The patient P12 tracked the tar-
get more accurately and reached a simi-
lar force level but the decrease of the
grip force was about twice as large (40%
in 15 s) compared to the first patient.
The results of the palmar grip (Figure
2) show that both patients lacked the
required muscle force to reach the final
target value. The patient P9 reached
about 20% of the required force level
and the patient P12 about 45%. The grip
force of the patient P12 decreased for
about 30% of the exerted force at the
end of the trial.
In our experiment the ramp test was
used to obtain the maximal grip force
values for the individual patients, which
were later used for setting the required
peak target level of the sinus task.
Figure 3 shows the results of the maxi-
mal grip force as assessed in 12 MD
patients who performed the tracking
task using five different grips (cylindri-
cal, lateral, palmar, pinch and spherical
grip). The patients P4, P5 and P11 were
not able to exert higher-level grip for-
ces in any of the grips tested. Only the
patients P1, P3, P6 and P7 were in posi-
tion to perform the task within the re-
quired grip force levels. The rest of the
patients completed the task with aver-
age results. The results of the grip for-
ces of the individual patient can be used
to assess the fatigue of the muscles (18)
used in the observed grips.
Figure 4 shows the results of the sinus
task as assessed in the same two patients
(P9 and P12) using the cylindrical and
palmar grip. The patient P9 performed
the task with less accuracy compared
to the patient P12, where larger rela-
tive tracking error can be observed. The
error increased in both patients when
performing the task with the palmar
grip. The results of the patient P9 show
that the grip force trajectory is not
smooth which reflects more abrupt
muscle activation pattern that unables
the patient to gradually increase or de-
crease the force.
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II-37
The relative tracking errors assessed
and compared among the patients are
presented in Figure 5. The results are
shown for different grips while per-
forming the task with the dominant and
non-dominant hand. The patients P1, P3,
P5, P6, P8 and P12 produced lower
tracking errors in all grips with respect
to the other patients. The lower track-
ing error suggests a better grip force
control resulting in greater hand func-
tionality. We can conclude that the
patients who could perform the task
more accurately while applying diffe-
rent grips have more enhanced muscle
control. Analysis of the results within
patients showed that the largest track-
ing errors were produced in pinch and
palmar grip while the errors in the cy-
lindrical, lateral and spherical grips were
smaller. There was no significant diffe-
rence found between the dominant and
non-dominant hand (one-way ANOVA,
p=0.326), except for the patients P7
and P10 who produced lower tracking
errors with non-dominant hand.
Conclusions
The purpose of this paper was to pre-
sent the method for the evaluation of
the grip force control in patients with
muscular dystrophy. The use of compu-
ter assisted methods for hand functiona-
lity assessment can increase the object-
ivity of the evaluation. The grip-
measuring device developed can be
used for the assessment of the functional
force applied while grasping objects
similar to objects used in daily living. The
device can measure the grip force with
much greater accuracy as compared to
the mechanical dynamometers, which
are commonly used in rehabilitation en-
vironment. The high accuracy of the
measurement allows detection of small changes in grip strength
following therapy or progression of disease. The grip force
can be measured in real-time providing the information on the
direction and level of the applied force while assessing func-
tional grips used in daily activities.
The results obtained in tracking of the ramp target showed
that the method can be used for the assessment of the muscle
fatigue, providing quantitative information on the muscle
fatigue while performing grips used in daily activities. Accu-
rate and objective evaluation of the muscle fatigue is needed
when evaluating the progress of disease or the effect of thera-
py on the patient (18). The results of the sinus-tracking task
showed that the method can evaluate the grip force control in
different types of grips, providing information on hand dex-
terity, muscle activation patterns or to detect tremor. The re-
sults obtained in the patients with muscular dystrophy showed
that most patients produced larger tracking errors in palmar
or pinch grip compared to the other grips. Their tracking
accuracy improved in cylindrical and lateral grip. The patients
with higher hand functionality showed less significant dif-
ferences between the grips tested.
The majority of the patients participating in this investigation
expressed positive opinion about the grip-force tracking sys-
tem. We believe that the cognitive feedback delivered to the
patients could have also a positive therapeutical value. The
tracking system can be applied as a training assistive device
where the difficulty of the tasks would be increased through-
out the therapy promoting in this way patient’s hand mobility
and grip force control. A similar grip-force tracking system
with a low-cost force sensor could be developed on the basis
of the results obtained and used at rehabilitation institutions
for the evaluation of grasping and grip force control.
Acknowledgements
The authors would like to thank the patients who participated in
the study, the therapist Bojan Čeru for the help with the experi-
ments, and the Ministry of Education, Science and Sport, Republic
of Slovenia for financing this research.
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Figure 5. Relative tracking error of the 12 patients with muscular dystrophy as
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muscles used in the particular grip. (* Patient was not able to perform the indicated
grip.)
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