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sensors
Article
The Piezo-resistive MC Sensor is a Fast and Accurate
Sensor for the Measurement of Mechanical
Muscle Activity
Andrej Megliˇc 1,*, Mojca Uršiˇc 1, Aleš Škorjanc 1, Srđan Đorđevi´c 2and Gregor Belušiˇc 1
1Department of Biology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia;
mojca.ursic@danceart.si (M.U.); ales.skorjanc@bf.uni-lj.si (A.Š.); gregor.belusic@bf.uni-lj.si (G.B.)
2TMG-BMC Ltd., Štihova ulica 24, 1000 Ljubljana, Slovenia; srdjand@tmg.si
*Correspondence: andrej.meglic@bf.uni-lj.si
Received: 14 March 2019; Accepted: 25 April 2019; Published: 7 May 2019
Abstract:
A piezo-resistive muscle contraction (MC) sensor was used to assess the contractile properties
of seven human skeletal muscles (vastus medialis, rectus femoris, vastus lateralis, gastrocnemius
medialis, biceps femoris, erector spinae) during electrically stimulated isometric contraction. The
sensor was affixed to the skin directly above the muscle centre. The length of the adjustable sensor
tip (3, 4.5 and 6 mm) determined the depth of the tip in the tissue and thus the initial pressure on
the skin, fatty and muscle tissue. The depth of the tip increased the signal amplitude and slightly
sped up the time course of the signal by shortening the delay time. The MC sensor readings were
compared to tensiomyographic (TMG) measurements. The signals obtained by MC only partially
matched the TMG measurements, largely due to the faster response time of the MC sensor.
Keywords:
muscle contraction sensor; tensiomyography; electrically stimulated skeletal
muscle contraction
1. Introduction
Skeletal muscles enable efficient movements of varying intensities and durations in different
movement patterns. Objective and non-invasive evaluation of muscle contractile properties is an
important tool in assessing and planning many activities related to human movement and can be
applied in physiology, physiotherapy and professional sports.
Skeletal muscles’ contractile properties are extensively studied using different measuring
methods [
1
–
4
]. Due to the invasiveness of direct methods for the determination of biomechanical
properties in human skeletal muscles through the estimation of the muscle fibre type, muscle properties
are preferably estimated through indirect measurement methods. Biomechanical properties are usually
detected by measuring the mechanical power or torque about a specific joint [
5
]. Such measurements
are non-selective, as it is generally almost impossible to measure the force or torque of an individual
muscle. Other methods involve surface electromyography [
6
–
12
], magnetic resonance imaging [
13
]
and ultrasound [
14
]. Recently, mechanomyography has been introduced. This non-invasive technique
records and quantifies the low-frequency lateral oscillations produced by the active skeletal muscle
fibres [
15
–
18
]. The signal can be detected by piezoelectric contact sensors, microphones, accelerometers
or laser distance sensors [
19
]. Another suitable method to examine skeletal muscle’ properties is
tensiomyography (TMG).
The tensiomyographic measuring technique (TMG) was devised to non-invasively measure the
biomechanical, dynamic and contractile properties of human skeletal muscles. In TMG, muscle belly
displacement is measured during the isometric muscle contraction induced externally by electrical
stimulation [
20
–
22
]. For each twitch response, five parameters are calculated from the displacement
Sensors 2019,19, 2108; doi:10.3390/s19092108 www.mdpi.com/journal/sensors
Sensors 2019,19, 2108 2 of 11
time course. The reliability of the derived contractile parameters was extensively tested [
23
–
27
].
Parameters can be used to analyse the muscle tone [
20
,
28
], fatigue [
29
,
30
] and asymmetries [
31
].
Moreover, the measured contraction time (time between 10% and 90% of the maximum value of the
muscle response) provides an important insight into the type of muscle fibre [
32
–
34
]. The correlation
coefficient between contraction time and the percentage of type 1 muscle fibres is 0.93. The usefulness
of TMG has been demonstrated in studies monitoring muscle atrophy [
35
], effects of different types
of physical exercise [
36
–
38
], endurance [
30
] and response characteristics after intensive training
periods [29].
However, TMG measurements are constrained to isometric conditions. To enable the measurements
of muscle mechanical activity during free movement in non-isometric conditions a new sensor was
developed [39].
A muscle contraction (MC) sensor was first introduced in 2011 [
39
]. This is a surface sensor,
which transduces the deformation of the contracting muscle into resistance with four piezo-resistors
connected in a Wheatstone bridge. During the measurement, the sensor is fixed on the skin surface
above the muscle belly while the sensor tip applies pressure and causes an indentation of the skin
and intermediate layer directly above the muscle and muscle itself. The force on the sensor tip is then
measured [
39
]. In the study by
Đ
or
đ
evi´c et al. [
39
] a high correlation between elbow peak flexion force
at five target levels of maximum voluntary contraction and MC sensor measured peak tension was
observed for the biceps brachii muscle. Dynamic properties of the sensor were further investigated
in the time domain in the same muscle [
40
]. Statistical correlation between MC signal and force was
very high at 15
◦
(r =0.976) and 90
◦
(r =0.966) elbow angle. The MC sensor dynamically follows the
contractions and is thus suitable for the dynamic measurement during voluntary free motion in cases
where direct force cannot be measured. Due to differences in skin and subcutaneous tissue mechanical
properties and thickness, the MC sensor cannot be used for measurements of the absolute value of
muscle force without proper calibration [
40
]. A strong correlation between MC sensor signal and
muscle force as well as a close-to-zero delay between the peak muscle force and MC sensor signal
was shown in upper trapezius muscle during a low-severity frontal impact [41]. Mohamad et al. [42]
evaluated the sensor using functional electrical stimulation. A strong linear correlation between MC
sensor measurements and dynamometer isometric knee torque suggested that the MC sensor is able to
detect different contraction levels and fatigue of the rectus femoris muscle among individuals with
spinal cord injury [42].
The aim of this study was to evaluate the MC sensor function during stimulated twitch contractions,
to measure the effect of the sensor tip depth on the obtained signal and to compare the results with the
parallel tensiomyographic measurements.
2. Materials and Methods
2.1. Subjects
Ten female volunteers, ranging between 18 and 24 years of age participated in the study. They
were all athletes in various dance categories (hip hop, modern, ballet), 159 cm–174 cm tall, weighing
48–63 kg. Subcutaneous fat, measured using a skin fold caliper, ranged: 3.4–5.3 mm at the biceps,
20.0–20.2 mm at the thigh, 3.2–14.4 mm at the calf and 6–8.3 mm at the lower back site. All subjects
were healthy and had no known neuromuscular or musculoskeletal disorders at the time of the study.
All subjects gave their informed consent for inclusion before they participated in the study. The study
was conducted in accordance with the Declaration of Helsinki, and the Republic of Slovenia National
Medical Ethics Committee approved the experimental procedures.
Seven different muscle pairs (left and right muscle of each volunteer) were analysed: m. vastus
medialis (VM), m. vastus lateralis (VL), m. rectus femoris (RF), m. tibialis anterior (TA), m. gastrocnemius
medialis (GM), m. biceps femoris (BF) and m. erector spinae (ES). During the measurements the subject
was in a prone or supine position, depending on measured muscle. Measurements were performed under
Sensors 2019,19, 2108 3 of 11
static, relaxed conditions. The measured limb was positioned on a triangular wedge foam cushion to
keep the knee joint in natural physiognomic position—flexed for 20
◦
. Special care was taken during the
measurements of m. erector spinae to prevent breathing-movement artefacts.
2.2. Tensiomyographic (TMG) Measurements
We first performed the TMG measurements. A digital displacement sensor (TMG-BMC d.o.o.,
Ljubljana, Slovenia) was placed perpendicular to the tangential plane on the largest area above the
muscle belly. The surface area of the dome shaped sensor tip is 35 mm
2
. The force applied to the
relaxed muscle was 1.5 N and the indentation was approximately 6 mm. The measuring point was
anatomically determined on the basis of the anatomical guide for electromyographers [
43
] and marked
with a dermatological pen. Self-adhesive bipolar electrodes (Axelgaard Manufacturing Co., Fallbrook,
CA, USA) were placed symmetrically 2–4 cm distal and proximal to the sensor tip. For stimulation
we used 1 ms long square pulse, the amplitude was progressively increased (40–100 mA) to obtain a
maximal response.
2.3. MC Measurements
The MC sensor principle was introduced by
Đ
or
đ
evi´c et al. [
39
]. In brief, the sensor consists of a
supporting part (650 mm
2
surface area) made of an elliptically shaped carbon fibre reinforced epoxy
polymer. An incision forms a tonguelet to which the sensor tip is attached. The surface area of the
sensor tip applying pressure to the skin is 56 mm
2
. A piezo-resistive strain gauge is attached at the root
of the tonguelet. The strain is proportional to the force acting on the sensor tip. Muscle contraction
produces tension which causes subcutaneous tissue and skin to press on the sensor tip. The MC sensor
was produced by TMG-BMC d.o.o. (Ljubljana, Slovenia).
The sensor was attached to the skin through the supporting part using double-sided adhesive
patches (Figure 1). The sensor tip was placed on the mark made on the skin during the TMG
measurements. The depth of the sensor tip indented in the skin fold was set to 3, 4.5 and 6 mm. The
depths of the sensor tip were chosen according to the TMG measurements and MC sensor technical
properties: 3.5 mm is the minimum depth limited by the MC sensor tip size; 6 mm is comparable
to the indentation of the skin and subcutaneous tissue in TMG measurements; 4.5 mm was chosen
between these two values for comparison. At greater depths, the force on the sensor tip during
muscle contraction was such that the sensor detached from the skin. The sensor was designed to
allow changing of the tip depth without removing the sensor. The stimulation electrodes remained
attached to the skin when we switched from the TMG to the MC sensor. Time between TMG and MC
measurements was around two minutes. The muscle contraction was triggered with the same current
as in TMG measurements. Two successive measurements were made for each muscle at each depth.
Sensors 2019, 19, x FOR PEER REVIEW 3 of 11
flexed for 20°. Special care was taken during the measurements of m. erector spinae to prevent
breathing-movement artefacts.
2.2. Tensiomyographic (TMG) Measurements
We first performed the TMG measurements. A digital displacement sensor (TMG-BMC d.o.o.,
Ljubljana, Slovenia) was placed perpendicular to the tangential plane on the largest area above the
muscle belly. The surface area of the dome shaped sensor tip is 35 mm2. The force applied to the
relaxed muscle was 1.5 N and the indentation was approximately 6 mm. The measuring point was
anatomically determined on the basis of the anatomical guide for electromyographers [43] and
marked with a dermatological pen. Self-adhesive bipolar electrodes (Axelgaard Manufacturing Co.,
Fallbrook, CA, USA) were placed symmetrically 2–4 cm distal and proximal to the sensor tip. For
stimulation we used 1 ms long square pulse, the amplitude was progressively increased (40–100
mA) to obtain a maximal response.
2.3. MC Measurements
The MC sensor principle was introduced by Đorđević et al. [39]. In brief, the sensor consists of
a supporting part (650 mm2 surface area) made of an elliptically shaped carbon fibre reinforced
epoxy polymer. An incision forms a tonguelet to which the sensor tip is attached. The surface area
of the sensor tip applying pressure to the skin is 56 mm2. A piezo-resistive strain gauge is attached
at the root of the tonguelet. The strain is proportional to the force acting on the sensor tip. Muscle
contraction produces tension which causes subcutaneous tissue and skin to press on the sensor tip.
The MC sensor was produced by TMG-BMC d.o.o. (Ljubljana, Slovenia).
The sensor was attached to the skin through the supporting part using double-sided adhesive
patches (Figure 1). The sensor tip was placed on the mark made on the skin during the TMG
measurements. The depth of the sensor tip indented in the skin fold was set to 3, 4.5 and 6 mm. The
depths of the sensor tip were chosen according to the TMG measurements and MC sensor technical
properties: 3.5 mm is the minimum depth limited by the MC sensor tip size; 6 mm is comparable to
the indentation of the skin and subcutaneous tissue in TMG measurements; 4.5 mm was chosen
between these two values for comparison. At greater depths, the force on the sensor tip during
muscle contraction was such that the sensor detached from the skin. The sensor was designed to
allow changing of the tip depth without removing the sensor. The stimulation electrodes remained
attached to the skin when we switched from the TMG to the MC sensor. Time between TMG and
MC measurements was around two minutes. The muscle contraction was triggered with the same
current as in TMG measurements. Two successive measurements were made for each muscle at
each depth.
The MC signal was sampled at 10 kHz using a 24-bit resolution, 25 mV/V NI 9237 module
(National Instruments, Austin, TX, USA). The sensor output response (in mV/V) was recalculated
into force using the calibration curve obtained by suspending weights (1, 2, 5, 10, 20, and 50 g) on
the tonguelet. The process of calibration, timeline of MC output response at various weights and
sensitivity graph are shown in Đorđević et al., 2011 [39]. The dependence between force and sensor
output was linear.
MATLAB (MathWorks, Natick, MA, USA) was used for data processing. Figures and Tukey’s
test, used for the time parameter multiple comparisons were done in Prism 8.0 (GraphPad
Software, San Diego, CA, USA).
Figure 1.
Muscle contraction (MC) sensor design and placement. (
a
) Four piezoresistors, connected in
Wheatstone bridge, were attached at the root of the tonguelet. Piezoresistors contact pads and cable
interface were connected with microelectronic golden wires and covered with epoxy casting compound
for protection. (
b
) The sensor was attached to the skin through the supporting part using double-sided
adhesive patches. (
c
) The depth of the sensor tip was set to 3, 4.5 and 6 mm. The sensor compressed
the skin and subcutaneous tissue, exerting pressure on the measured skeletal muscle.
Sensors 2019,19, 2108 4 of 11
The MC signal was sampled at 10 kHz using a 24-bit resolution, 25 mV/V NI 9237 module (National
Instruments, Austin, TX, USA). The sensor output response (in mV/V) was recalculated into force
using the calibration curve obtained by suspending weights (1, 2, 5, 10, 20, and 50 g) on the tonguelet.
The process of calibration, timeline of MC output response at various weights and sensitivity graph
are shown in Đorđevi´c et al., 2011 [39]. The dependence between force and sensor output was linear.
MATLAB (MathWorks, Natick, MA, USA) was used for data processing. Figures and Tukey’s test,
used for the time parameter multiple comparisons were done in Prism 8.0 (GraphPad Software, San
Diego, CA, USA).
3. Results
The typical MC sensor recording is presented in Figure 2. The time course of muscle contraction
shows a rapid onset due to the action of the fast contractile elements, resulting in the first peak within a
few tens ms after the stimulus. The slower contractile elements reach the peak activity within >100 ms
after the stimulus. The subsequent relaxation follows a simpler time course. Five parameters were
extracted from the measured response of the muscle belly to the electrical stimulus:
Sensors 2019, 19, x FOR PEER REVIEW 4 of 11
Figure 1. Muscle contraction (MC) sensor design and placement. (a) Four piezoresistors, connected
in Wheatstone bridge, were attached at the root of the tonguelet. Piezoresistors contact pads and
cable interface were connected with microelectronic golden wires and covered with epoxy casting
compound for protection. (b) The sensor was attached to the skin through the supporting part using
double-sided adhesive patches. (c) The depth of the sensor tip was set to 3, 4.5 and 6 mm. The
sensor compressed the skin and subcutaneous tissue, exerting pressure on the measured skeletal
muscle.
3. Results
The typical MC sensor recording is presented in Figure 2. The time course of muscle
contraction shows a rapid onset due to the action of the fast contractile elements, resulting in the
first peak within a few tens ms after the stimulus. The slower contractile elements reach the peak
activity within >100 ms after the stimulus. The subsequent relaxation follows a simpler time course.
Five parameters were extracted from the measured response of the muscle belly to the electrical
stimulus:
Dm—maximal force.
Td—delay time (from 0 to 10% of Dm).
Tc—contraction time (from 10% of Dm to 90% of Dm or 90% of the first explicit peak
amplitude. The criterion for identifying the first peak in the couple was a drop in the signal for 2%.
Ts—sustain time (signal >50% of Dm).
Tr—relaxation time (signal drops from 90 to 50% of Dm).
Figure 2. Typical MC sensor recording. Parameters extracted from measured response: Td—delay
time, Tc—contraction time, Ts—sustain time, Tr—relaxation time, Dm—maximal force. Zero time
corresponds to the start of electrical stimulus.
Measurements of seven different muscles made with TMG and MC sensor at three different
sensor tip depths were compared. Signals from a single muscle are presented in Figure 3a–d;
signals from all muscles are presented in supplementary Figure S1. To compare the signals from the
two sensors, Pearson correlation coefficient was calculated between the synchronized data points
from the two measurements in the same muscle (Table 1). The average correlation coefficient R
between TMG and MC signal was at the different depths of sensor tip (3, 4.5, 6 mm): R
(3 mm)
= 0.72,
R
(4.5 mm)
= 0.76, R
(6 mm)
= 0.76. The only exception was the muscle erector spinae, where the correlation
coefficient was considerably lower and surprisingly the highest at the shallowest depth R
(3 mm)
=
0.62.
Figure 2.
Typical MC sensor recording. Parameters extracted from measured response: Td—delay
time, Tc—contraction time, Ts—sustain time, Tr—relaxation time, Dm—maximal force. Zero time
corresponds to the start of electrical stimulus.
Dm—maximal force.
Td—delay time (from 0 to 10% of Dm).
Tc—contraction time (from 10% of Dm to 90% of Dm or 90% of the first explicit peak amplitude.
The criterion for identifying the first peak in the couple was a drop in the signal for 2%.
Ts—sustain time (signal >50% of Dm).
Tr—relaxation time (signal drops from 90 to 50% of Dm).
Measurements of seven different muscles made with TMG and MC sensor at three different sensor
tip depths were compared. Signals from a single muscle are presented in Figure 3a–d; signals from
all muscles are presented in Supplementary Figure S1. To compare the signals from the two sensors,
Pearson correlation coefficient was calculated between the synchronized data points from the two
measurements in the same muscle (Table 1). The average correlation coefficient Rbetween TMG and
MC signal was at the different depths of sensor tip (3, 4.5, 6 mm): R
(3 mm)
=0.72, R
(4.5 mm)
=0.76,
R
(6 mm)
=0.76. The only exception was the muscle erector spinae, where the correlation coefficient was
considerably lower and surprisingly the highest at the shallowest depth R(3 mm) =0.62.
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Table 1. Correlation coefficients R between tensiomyographic (TMG) and muscle contraction (MC)
sensor measurements at the three different sensor tip depths (3, 4.5 and 6 mm). The highest
coefficients in each muscle are bolded.
Muscle R
(3 mm)
R
(4.5 mm)
R
(6 mm)
vastus medialis 0.78 0.83 0.84
rectus femoris 0.72 0.80 0.84
vastus lateralis 0.68 0.74 0.76
tibialis anterior 0.74 0.77 0.71
gastrocnemius medialis 0.68 0.76 0.72
biceps femoris 0.69 0.68 0.66
erector spinae 0.62 0.49 0.44
The increase in the depth of the sensor tip resulted in an increase of the amplitude (Dm) of the
measured signal (Figure 3b–d). The increase was ×1.7–×3.0 and ×2.0–×4.8 when the depth of the tip
was increased from 3 to 4.5 and 6 mm, respectively. The lowest increase was in the muscle tibialis
anterior (×1.7 and ×2.0).
Figure 3. Response of vastus medialis to twitch stimulation measured with tensiomyographic
(TMG) (a) and MC sensor at three tip depths: 3 mm (b), 4.5 mm (c) and 6 mm (d). Solid line, average
values (n = 20, left and right muscles of 10 subjects were measured); envelope, SD. Average signal
from both sensors has been normalised to maximum (e). (f) shows first 100 ms of the normalised
signals from panel e. In some recordings, a small peak appears 4 to 5 ms after the start of the
stimulus. The short duration of the peak (less than 0.5 ms) indicates non-physiological origin.
Figure 3.
Response of vastus medialis to twitch stimulation measured with tensiomyographic (TMG)
(
a
) and MC sensor at three tip depths: 3 mm (
b
), 4.5 mm (
c
) and 6 mm (
d
). Solid line, average values
(n=20, left and right muscles of 10 subjects were measured); envelope, SD. Average signal from both
sensors has been normalised to maximum (
e
). (
f
) shows first 100 ms of the normalised signals from
panel e. In some recordings, a small peak appears 4 to 5 ms after the start of the stimulus. The short
duration of the peak (less than 0.5 ms) indicates non-physiological origin.
Table 1.
Correlation coefficients Rbetween tensiomyographic (TMG) and muscle contraction (MC)
sensor measurements at the three different sensor tip depths (3, 4.5 and 6 mm). The highest coefficients
in each muscle are bolded.
Muscle R(3 mm) R(4.5 mm) R(6 mm)
vastus medialis 0.78 0.83 0.84
rectus femoris 0.72 0.80 0.84
vastus lateralis 0.68 0.74 0.76
tibialis anterior 0.74 0.77 0.71
gastrocnemius medialis 0.68 0.76 0.72
biceps femoris 0.69 0.68 0.66
erector spinae 0.62 0.49 0.44
The increase in the depth of the sensor tip resulted in an increase of the amplitude (Dm) of the
measured signal (Figure 3b–d). The increase was
×
1.7–
×
3.0 and
×
2.0–
×
4.8 when the depth of the tip
was increased from 3 to 4.5 and 6 mm, respectively. The lowest increase was in the muscle tibialis
anterior (×1.7 and ×2.0).
Sensors 2019,19, 2108 6 of 11
The time courses of the muscle response to electrical stimulus vary depending on the muscle and
the chosen method (Figure 3e). In general, we distinguish two basic types: single and double peak
signal. The two peaks were usually better resolved in recordings with the MC sensor. However, the
frequency of occurrence of double peaks was for some muscles almost identical in both measuring
techniques. In measurements from gastrocnemius medialis and vastus medialis, the double peaks
were present in 95% of TMG recordings and 95–100% (depending on the sensor depth) recordings with
MC sensor. However, in vastus lateralis, biceps femoris and rectus femoris, the double peaks were
present in only 30% of TMG and in 85–95% of MC recordings. The tibialis anterior muscle was an
exception with the double peaks occurring in only 25% of recordings, regardless of the sensor type.
The depth of the MC sensor tip had little impact on the Tc, Ts and Tr (with the exception of Tr
parameter in vastus medialis) time course parameters. Statistically significant differences between
different tip depths were observed in the parameter Td in four out of seven muscles (exceptions were
gastrocnemius medialis, erector spinae and biceps femoris). The Td time in vastus medialis, rectus
femoris, vastus lateralis and tibialis anterior shortened with the increasing tip depth on average for
19.3% and additional 3.0% for an increase from 3.0 to 4.5 and 6 mm.
When compared to TMG measurements, Td times were shorter when measured with MC sensor
(Figure 3e,f; Figure 4a,b) with the exception of erector spinae where no statistically significant differences
were found between TMG and MC measurements. On average Td was shorter for 20.3 to 26.5% at the
middle depth of the sensor tip compared to TMG.
Sensors 2019, 19, x FOR PEER REVIEW 7 of 11
Figure 4. Comparison of four different temporal parameters extracted from responses of muscle
belly to electrical stimulus, measured with TMG and MC. (a) Delay time, Td; (b) contraction time,
Tc; (c) sustain time, Ts (d) relaxation time, Tr. Measurements with TMG are compared to those with
MC sensor at three different depths (3, 4.5 and 6 mm). Asterisks indicate the level of statistical
significance (* P<0.05, ** P<0.01, *** P<0.001). Mean values and standard deviations are shown.
4. Discussion
Two sensors, MC and TMG, were used to evaluate the contraction in different types of
muscles—short, long, one and two jointed, phasic and postural. The lowest correlation coefficient
between TMG and MC sensor signal was measured in erector spinae. In contrast to other measured
muscles that are simpler, resembling a spindle interconnecting two parts of a limb, erector spinae is
a bundle of muscles and tendons varying in size and structure at different parts of the vertebral
column. In the lumbar region, where the measurements were made, it is a large, thick fleshy mass.
Its contraction results in a muscle displacement with a less pronounced muscle belly. As the MC
sensor moves together with the muscle, the pressure on the sensor tip is in such case smaller
resulting in lower signal. Stimulation of erector spinae increases the back lordosis, affecting TMG
measurements, as the sensor does not move together with the back. Nevertheless, the time
parameters between the two methods for this muscle are fairly well matched with the exception of
Tc times, which are shorter in MC measurements.
In other muscles, the correlation between TMG and MC measurements was between 0.66 and
0.84, depending on the MC sensor tip depth. We assume that the signals differed in the shape of
their time course mainly due to the different mass of the two sensors. The MC sensor, which is
much lighter and has a lower inertia can, therefore, respond more rapidly to changes in the muscle
tension, and detects smaller differences. The faster responsively of the MC sensor is also visible in
shorter Td and Tc times and in higher number of double peaks which are also more pronounced
(Figure 3e,f). The variability in presence and distinctiveness of double peaks caused substantial
scattering of the Tc values, especially in MC measurements. To avoid this we measured maximal
slopes. A linear function was fitted to 10 ms segments of the signal, normalised to maximal
displacement or force. The maximal slopes of the signal (Figure 5) calculated show similar trends as
in Tc times (Figure 4b) with much smaller standard deviations.
Figure 4.
Comparison of four different temporal parameters extracted from responses of muscle belly to
electrical stimulus, measured with TMG and MC. (
a
) Delay time, Td; (
b
) contraction time, Tc; (
c
) sustain
time, Ts (
d
) relaxation time, Tr. Measurements with TMG are compared to those with MC sensor at
three different depths (3, 4.5 and 6 mm). Asterisks indicate the level of statistical significance (
*P<0.05
,
** P<0.01, *** P<0.001). Mean values and standard deviations are shown.
Similar results were obtained for the parameter Tc with 20.4 to 33.0% shorter times measured
with MC sensor on middle depth than with TMG (Figure 3e,f). Longer times were measured on
vastus lateralis and erector spinae muscle (for 26.6 and 34.5% respectively) although the difference was
not significant.
Sensors 2019,19, 2108 7 of 11
Statistically significant differences in Ts times were measured in three muscles—vastus lateralis,
erector spinae (between TMG and all three depths) and biceps femoris (between TMG and MC at 6 mm
depth). While the times measured with MC sensor were shorter in biceps femoris and erector spinae
(16.0% and 27.3%) they were longer in vastus lateralis (70.5%, 60.8% and 60.7% for 3, 4.5 and 6 mm MC
sensor tip depth).
The least differences between the two methods were found for the Tr parameter (Figure 4d). The
significant difference was found only in vastus medialis, erector spinae (between TMG and MC at
3 mm depth) and biceps femoris (between TMG and MC at 6 mm depth).
4. Discussion
Two sensors, MC and TMG, were used to evaluate the contraction in different types of
muscles—short, long, one and two jointed, phasic and postural. The lowest correlation coefficient
between TMG and MC sensor signal was measured in erector spinae. In contrast to other measured
muscles that are simpler, resembling a spindle interconnecting two parts of a limb, erector spinae
is a bundle of muscles and tendons varying in size and structure at different parts of the vertebral
column. In the lumbar region, where the measurements were made, it is a large, thick fleshy mass. Its
contraction results in a muscle displacement with a less pronounced muscle belly. As the MC sensor
moves together with the muscle, the pressure on the sensor tip is in such case smaller resulting in
lower signal. Stimulation of erector spinae increases the back lordosis, affecting TMG measurements,
as the sensor does not move together with the back. Nevertheless, the time parameters between the
two methods for this muscle are fairly well matched with the exception of Tc times, which are shorter
in MC measurements.
In other muscles, the correlation between TMG and MC measurements was between 0.66 and
0.84, depending on the MC sensor tip depth. We assume that the signals differed in the shape of their
time course mainly due to the different mass of the two sensors. The MC sensor, which is much lighter
and has a lower inertia can, therefore, respond more rapidly to changes in the muscle tension, and
detects smaller differences. The faster responsively of the MC sensor is also visible in shorter Td and
Tc times and in higher number of double peaks which are also more pronounced (Figure 3e,f). The
variability in presence and distinctiveness of double peaks caused substantial scattering of the Tc
values, especially in MC measurements. To avoid this we measured maximal slopes. A linear function
was fitted to 10 ms segments of the signal, normalised to maximal displacement or force. The maximal
slopes of the signal (Figure 5) calculated show similar trends as in Tc times (Figure 4b) with much
smaller standard deviations.
Sensors 2019, 19, x FOR PEER REVIEW 8 of 11
Figure 5. Maximal slopes of signals. Measurements with TMG are compared to those with MC
sensor at three different depths (3, 4.5 and 6 mm) and their maximal slopes are averaged. Mean
values and standard deviations are shown.
The depth of the MC sensor tip influenced mostly the amplitude of the signal. In all measured
muscles, the force increased with the increasing tip depth. A relatively small increase in the tibialis
anterior was due to a thin layer of soft tissue between the sensor and bone. Strong curvature of this
part of the leg also prevented the firm attachment of the MC sensor to the skin especially at the
maximal sensor tip depth. Upon removing the MC sensor, we discovered that the bond between
skin and sensor in tibialis anterior has been loose on several occasions with the 6 mm MC sensor
depth. In such cases, we reattached the sensor and repeated the measurement. In general, out of the
three preset values the medium depth of 4.5 mm is the best compromise between the signal
amplitude and firm contact.
In general, the signals from the MC sensor had shorter Td and Tc parameters (Figure 4) and
larger slopes (Figure 5) than the signals from the TMG sensor, which we attributed to the faster
response of the MC sensor. To verify this assumption, both sensors were tested with a mechanical
actuator and laser vibrometer. Indeed, the MC sensor was capable of following a 10 ms ramp
displacement while the TMG sensor had substantially slower response (Supplementary Material
1.2, Figure S2). Even though the MC sensor is slightly less robust than the TMG sensor it appears to
be more suitable for the measurements in fast muscles. For more comprehensive comparison of
mechanical properties of both sensors further measurements need to be done.
5. Conclusions
We measured a stimulated isometric contraction of seven muscle pairs (6 on leg and 1 on back)
in ten healthy volunteers aged 18 to 25. Firstly, a tensiomyographic (TMG) measurement was done,
with the sensor perpendicular to the skin overlying the muscle belly and self-adhesive stimulating
electrodes 2–4 cm distally and proximally of the sensor tip. Then, at the site of the placement of the
TMG sensor, a MC sensor was attached using double-sided adhesive patches. The stimulation
parameters were the same as for the TMG measurements. Sensor tip depth was adjusted to 3, 4.5
and 6 mm. For each measurement the delay (Td), contraction (Tc), sustain (Ts) and relaxation (Tr)
time was extracted from the measured response of muscle belly on electrical stimulus. The average
correlation coefficient between TMG and MC measurement for vastus medialis, rectus femoris,
vastus lateralis, gastrocnemius medialis, and biceps femoris at all three depths of sensor tip was
0.74. The exception was the erector spinae muscle with lower average correlation coefficient (r =
0.52). The depth of the sensor tip affected the measured force but had little influence on the
Figure 5.
Maximal slopes of signals. Measurements with TMG are compared to those with MC sensor
at three different depths (3, 4.5 and 6 mm) and their maximal slopes are averaged. Mean values and
standard deviations are shown.
Sensors 2019,19, 2108 8 of 11
The depth of the MC sensor tip influenced mostly the amplitude of the signal. In all measured
muscles, the force increased with the increasing tip depth. A relatively small increase in the tibialis
anterior was due to a thin layer of soft tissue between the sensor and bone. Strong curvature of this part
of the leg also prevented the firm attachment of the MC sensor to the skin especially at the maximal
sensor tip depth. Upon removing the MC sensor, we discovered that the bond between skin and sensor
in tibialis anterior has been loose on several occasions with the 6 mm MC sensor depth. In such cases,
we reattached the sensor and repeated the measurement. In general, out of the three preset values the
medium depth of 4.5 mm is the best compromise between the signal amplitude and firm contact.
In general, the signals from the MC sensor had shorter Td and Tc parameters (Figure 4) and larger
slopes (Figure 5) than the signals from the TMG sensor, which we attributed to the faster response of
the MC sensor. To verify this assumption, both sensors were tested with a mechanical actuator and
laser vibrometer. Indeed, the MC sensor was capable of following a 10 ms ramp displacement while
the TMG sensor had substantially slower response (Supplementary Material 1.2, Figure S2). Even
though the MC sensor is slightly less robust than the TMG sensor it appears to be more suitable for the
measurements in fast muscles. For more comprehensive comparison of mechanical properties of both
sensors further measurements need to be done.
5. Conclusions
We measured a stimulated isometric contraction of seven muscle pairs (6 on leg and 1 on back)
in ten healthy volunteers aged 18 to 25. Firstly, a tensiomyographic (TMG) measurement was done,
with the sensor perpendicular to the skin overlying the muscle belly and self-adhesive stimulating
electrodes 2–4 cm distally and proximally of the sensor tip. Then, at the site of the placement of
the TMG sensor, a MC sensor was attached using double-sided adhesive patches. The stimulation
parameters were the same as for the TMG measurements. Sensor tip depth was adjusted to 3, 4.5 and
6 mm. For each measurement the delay (Td), contraction (Tc), sustain (Ts) and relaxation (Tr) time was
extracted from the measured response of muscle belly on electrical stimulus. The average correlation
coefficient between TMG and MC measurement for vastus medialis, rectus femoris, vastus lateralis,
gastrocnemius medialis, and biceps femoris at all three depths of sensor tip was 0.74. The exception
was the erector spinae muscle with lower average correlation coefficient (r =0.52). The depth of the
sensor tip affected the measured force but had little influence on the normalized time course, except on
the parameter Td, which decreased with the increasing tip depth. The measured parameters obtained
with the MC sensor were partially in agreement with the tensiomyographic measurements. Td and Tc
times were on average shorter for 24.2% and 25.7% respectively. The exceptions are Td times in erector
spinae and Tc times in erector spinae and vastus lateralis where the times were shorter in TMG. Ts and
Tr times were more comparable between MC sensor and TMG. Statistically significant differences in Ts
times between MC and TMG measurements were obtained in biceps femoris, erector spinae and vastus
lateralis while Tr times were different in biceps femoris, erector spinae and vastus medialis although
only between TMG and MC at 3.5 and 6 mm tip depth.
We can conclude that the MC sensor enables the measurement of the mechanical muscle properties.
However, the extracted time parameters cannot be directly compared to the ones measured with
the TMG. The MC sensor can respond more rapidly and consequently allowing a better separation
between fast and slow fibres in the muscle. Since muscle architecture changes during contraction are
complex [
44
] further studies are needed to understand all the components of the signal and the origin
of differences between signals from both sensors.
Supplementary Materials:
The following are available online at http://www.mdpi.com/1424-8220/19/9/2108/s1,
Figure S1: Response of muscles to twitch stimulation measured with tensiomyographic (TMG) (black line) and MC
sensor at three tip depths: 3 mm, 4.5 mm and 6 mm (colour lines). Average values (n=20) are shown. Muscles:
rectus femoris (
a
), vastus lateralis (
b
), tibialis anterior (
c
), gastrocnemius medialis (
d
), biceps femoris (
e
), erector
spinae (
f
). Figure S2: Response of TMG (
a
) and MC (
b
) sensors to a mechanical displacement (black and red line).
Grey line shows the displacement measured with the laser vibrometer.
Sensors 2019,19, 2108 9 of 11
Author Contributions:
Conceptualization, A.M.; Formal analysis, A.M.; Investigation, M.U.; Methodology, A.Š.
and G.B.; Writing—original draft, A.M. Writing—review & editing, S.Đ. and G.B.
Funding: This research received no external funding.
Conflicts of Interest: The authors declare no conflict of interest.
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