Kelsey Kretchman
April 4th, 2014
HTH 308: 001 Lab
Isokinetic Leg Strength Test
Introduction:
Physical fitness is an essential element in one’s overall health evaluation to
determine if there are possible risk factors that can lead to a wide array of chronic
diseases such as diabetes, obesity and cardiovascular complications. Encompassed
in the term of physical fitness; muscular strength, cardiorespiratory endurance and
flexibility are all equally important in evaluating current standards of health and
establishing strategies to improve existing conditions. For the purpose of this lab,
emphasis was placed on determining muscular strength. Muscular strength is a key
element in maintaining quality of life, improving body composition and reducing the
possibility of developing musculoskeletal injuries (ACSM, 2014). The human body
consists of more than 600 skeletal muscles; accurately assessing each and every one
is nearly impossible. To determine overall muscular strength there is a significant
association between lean muscle mass and the strength of knee extension during a
isokinetic contraction.
A wide range of methods employing different modes of generating force can
be used to measure muscular strength. Specifically this experiment utilized the
BioDex that determined the peak torque during isokinetic contractions. An
isokinetic contraction is a subcategory of dynamic contractions meaning the length
of the muscle fibers change producing a force in order to put an object in motion.
Isokinetic implies the force generated to create a contraction remains at a fixed
velocity, or speed. The BioDex engineers the subject to exert maximal tension
throughout an entire range of motion. The combination of the consistent velocity
and recruitment of maximal effort; peak torque can be determined. Torque refers
the quantifiable measurement of force in Newton-meters (Nm) and the distance of
the lever arm. The force must revolve around an immovable fulcrum (Gandaio,
Pincivero & Ito, 2003). In this particular experiment the subject preforms extension
at the knee joint while their leg is attached to a lever arm. However, the proportion
of various muscle fibers gauges peak torque.
Skeletal muscle consists of two types of fibers, fast and slow twitch. The two
differ in response to training as a result of their ability to produce ATP, speed of
contractions, degree of force production and resistance to fatigue. Fast twitch
muscle fibers create a greater peak torque due to their increased amplitude of force
generated. Their capability to deliver highly powerful contractions is because of
their rapid Ca2+ exchange, high ATPase activity and the fast transmission rate of
action potentials (Katch, Katch & McArdle, 2010). As a result of rapid activation and
powerful force generation, fast twitch muscle fibers fatigue rather quickly.
Determining peak torque during an isokinetic contraction can therefore help in
establishing the proportion of fast and slow twitch muscle fibers. Calculating the
ratio of muscle fibers can be beneficial in recommending proper training techniques
per individual’s muscular makeup. It can also provide explanation for the potential
success or failure in a particular sporting event.
Methods:
To obtain the percentage of fast and slow twitch muscle fibers peak torque
during an isokinetic, unilateral contraction at the knee joint was first determined.
The subject was introduced to the BioDex machine and was informed of the
procedures to follow. A warm-up was first performed using a cycle ergometer at an
intensity of 2 kp. We recommended a duration of four minutes, but the subject was
encouraged to warm-up until they felt loose and could perform maximal exertion.
The subject was instructed to statically stretch their quadriceps and hamstrings of
their dominant leg. If unsure, the dominant leg would be the one they would kick a
ball if asked, or if falling forward the leg placed out to catch their self.
After the warm-up and stretching was completed, positioning and calibrating
the BioDex was the key element in constructing accurate results. The subject’s
name, date of birth, gender, dominant limb (right or left), height in inches (in.),
weight in pounds (lbs.) and any prior surgeries or injuries were inputted into the
client profile in the computer. The subject sat in an upright, properly postured and
comfortable position. Straps were attached across the torso in an X pattern, across
the waist along the pelvic bones and across mid-thigh of the dominant leg to secure
the patient to the chair and avoid excess movement of other extremities. The straps
needed to be tight enough to avoid additional leverage but still allowed to subject to
breath in a normal fashion. Depending on which limb is dominant; the
extension/flexion leg attachment was appropriately determined, attached on the
dynamometer and securely fastened on the support with a screw. After palpating to
locate the lateral femoral epicondyle of the dominant leg, the bony landmark was
aligned with the axis of rotation of the dynamometer determined as the screw used
to fasten by adjusting the vertical and horizontal shifting adjustments for the chair
base. Once the subject was properly positioned in the chair their distal leg was
secured to the leg attachment by fastening the shin pad approximately 1½ inches
above the Achilles tendon or just below the termination of the gastrocnemius
muscle. Following the confirmation that the shin strap is tightly secured the patient
directed to fully extent their limb to verify their comfort. After adjustment of the
chair and alignment of axis of rotation was finalized, the subject’s range of motion
was established. The previous limits were cleared. The toward limit, full flexion
was determined by having the subject bring their leg as far back as possible without
hitting the chair. The away limit was determined by having the subject completing
full extension, by bring their leg as far forward as possible. The toward and away
limits were utilized as the dynamometer’s range of motion. Subsequently, the
patient’s reference angle, knee joint at a 90°, was recorded in the software’s
goniometer. Gravity was taken into consideration by having the subject fully extend
their leg, asked to relax by releasing the contraction and the limb weight was
recorded. Concluding the calibration and adjustment of the client, they were
familiarized by the instructor on the procedures to follow. 10 repetitions were to be
performed at a speed setting of 120° gradually increasing intensity throughout the
warm-up phase. On 11th repetition, without a pause, the subject was told to perform
50 leg extensions using maximal exertion during every contraction as fast and hard
as possible without stopping. Their arms were required to stay across their chest
and were given positive reinforcement and encouragement throughout the entire
process. Reminders to breath forcefully were given to aid in executing maximal
effort. After the 60th repetition, a horn was set off to signal completion of the test.
The subject was unstrapped, provided with assistance out of the chair and urged to
begin a cool down on the cycle ergometer at little to no resistance.
After the completion of the test, peak torque for contractions 11, 12, 13, 58,
59 and 60 were found. Each contraction produced a curve analysis; the highest
point on the curve was denoted as the peak torque per contraction. Data was
recorded in a table to be used for calculations later. The average peak torque for
contractions groupings 11-13 and 58-60 was obtained. Fiber type distribution of
the quadriceps in the dominant leg for the subject was computed using average peak
torque for both sets 11-13 and 58-60 entered into the equation [0.9 (x) + 5.2] --- x
denoted: [(average peak torque 11-13 – average peak torque 58-60) ÷ average
peak torque 11-13] x 100 producing the percentage of fast twitch muscle fibers. The
percentage of slow twitch was determined by subtracting fast twitch percentage
from 100. Aside from percentage of fiber distribution one last calculation was
recorded. After converting the client’s weight into kilograms peak torque to body
weight for each contraction triplet was calculated.
Results:
Table1: The average peak torque (Nm) during repetitions 11-13 and the percentage
of fast twitch muscle fibers.
Peak Torque Average (Nm) Reps: 11-13
Percentage of Fast Twitch Muscle
Fibers
30.27 Nm
50.7 Nm
58.2 Nm
42.1 Nm
84.2 Nm
26.9 Nm
39.03 Nm
42.5 Nm
5.8%
33%
58%
2.3%
40%
12.56%
30.17 %
25.63%
Perentage fast twitch muscle fibers (%)
The Effect of Peak Torque on Percentage of
Fast Twitch Muscle Fibers
100
90
R² = 0.4526
80
70
60
50
40
30
20
10
0
0
10
20
30
40
50
60
70
Average peak torque (Nm) reps: 11-13
80
90
Figure1: The correlation of average peak torque during contractions 11 through 13
and percentage of fast twitch muscle fibers in the quadriceps of the dominant leg.
The correlation of average peak torque during the first triplet of contractions; 11, 12
and 13 and the percentage of fast twitch muscle fibers in the quadriceps of the
dominant leg during a maximal isokinetic unilateral knee extension and flexion
reveals a positive trend and according to the R-value has a moderately high strength
of relationship.
Table2: The average peak torque ÷ body weight (Nm/Kg) during repetitions 11-13
and the percentage of muscle fibers.
Percentage of Fast Twitch Muscle
Average Peak torque ÷ body weight
Fibers
(Nm/Kg) Reps: 11-13
0.3422 (Nm/Kg)
0.87 (Nm/Kg)
1.1 (Nm/Kg)
0.6 (Nm/Kg)
1.04 (Nm/Kg)
0.51 (Nm/Kg)
0.536 (Nm/Kg)
0.74 (Nm/Kg)
5.8%
33%
58%
2.3%
40%
12.56%
30.17%
25.63%
Percentage of fast twitch muscle
fibers (%)
The Effect of Peak Torque ÷ Body Weight on
the Percentage of Fast Twitch Muscle Fibers
100
90
80
70
60
50
40
30
20
10
0
R² = 0.7421
0
0.2
0.4
0.6
0.8
1
Peak torque ÷ body weight average (Nm/kg) reps: 11-13
1.2
Figure2: The correlation of peak torque ÷ body weight average during
contractions 11 through 13 and percentage of fast twitch muscle fibers in the
quadriceps of the dominant leg.
The correlation of peak torque ÷ body weight average during the first triplet of
contractions; 11, 12 and 13 and the percentage of fast twitch muscle fibers in the
quadriceps of the dominant leg during a maximal isokinetic unilateral knee
extension and flexion reveals a positive trend and according to the R-value has an
extremely high strength of relationship.
Calculations: (Client’s data)
Body weight: 115 lbs x
Contraction #
Peak torque
Peak torque ÷
body weight (kg)
1 kg
2.2 lbs
=
52. 27 Kg
11
12
13
Average
58
59
60
Average
16.1
0.31
27.1
0.52
37.5
0.72
26.9
0.51
26.5
0.51
30.3
0.58
30.6
0.59
29.1
0.56
Fast Twitch Fiber % = 0.9 (x) + 5.2
--- x = [(average peak torque 11-13 – average peak torque 58-60 ÷ average
peak torque 11-13) x 100]
x = [(26.9 – 29.1 ÷ 26.9) x 100]
x = - 8.18 * absolute value
% = 0.9 (8.18) + 5.2
Fast Twitch Fiber % = 12.56 %
Slow Twitch Fiber % = 100 % -- Fast Twitch Fiber %
% = 100 – 12.56
Slow Twitch Fiber % = 87.44 %
Percent Fatigue = [(average peak torque ÷ body weight reps: 58-60) –
(average peak torque ÷ body weight reps: 11-13) ÷ (average peak torque ÷
body weight reps: 11-13)] x 100
[(0.56) – (0.51) ÷ (0.51)] x 100
Percent Fatigue = 9.8 %
Discussion:
The comparison of individual’s average peak torque during contractions 11
through 13 and percentage of fast twitch muscle fibers in the quadriceps of the
dominant leg demonstrated a positive trend meaning there is a statistical possibility
that the graph would continue in an upward fashion with additional subjects.
According to its’ R-value (Figure 1. R=0.6728) there is a moderately high strength of
relationship. This translates into the statistical possibility that the higher one’s
average peak torque is associated with a higher percentage of fast twitch muscle
fibers. Furthermore, the comparison of one’s average peak torque divided by their
body weight and percentage of fast twitch muscle fibers display a positive trend as
well. Considering its’ R-value (Figure 2. R=0.8615) there is a reasonably higher
strength of relationship between the variables. One can conclude that factoring an
individual’s body weight into peak torque performed results in a stronger
correlation. The higher PT/BW value statistically speaking the higher the
percentage of fast twitch muscle fibers are likely to be. Apparent in the two graphs
are outliers that differ from the projected trend. These could be an outcome of
human calculation error for example, not converting pounds into kilograms prior to
calculating PT/BW. This would create an end result, failing to represent accurate
proportion of muscle fibers.
On average, people possess 45-55% of slow twitch muscle fibers or type I
among the body’s major muscle groups. The remaining percentage is attributed to
fast twitch muscle fibers or type II is further subdivided into IIa and IIb. Slow twitch
fibers are associated with aerobic generation of energy, meaning there an
abundance of mitochondria, which processes oxygen efficiently. The well-organized
system of managing oxygen creates for greater levels of myoglobin, the hemoglobin
cell of the muscle, creating a red appearance during a staining, as well (Schiaffino &
Reggiani, 2011). These fibers thus are more suitable for prolonged light to
moderate intensity. Due to the makeup of these fibers ATP regeneration is a result
of the Kreb’s cycle and electron transport chain and the plentiful amounts of oxygen
allow them to fatigue at a much slower pace. On the opposite end of the spectrum,
fast twitch fibers are associated with anaerobic energy supply primarily through
glycolysis. Their degree of fatigability is much greater as a result of their quick,
forceful generation of energy. In general fiber distribution is genetically
predetermined especially in the extreme events of elite, world-class athletes (Katch,
Katch & McArdle, 2010). With consistent training, there can be some modifications
in switching the shift from one type being dominated versus the other.
Particular sporting events favor one type over the other in order to
physiologically achieves the demands placed by the activity being performed. Events
predominantly recruiting slow twitch muscle fibers, inversely not needing a high
percentage of fast twitch fibers are associated with higher aerobic challenges such
as marathon running. Genetically engineered with the distribution of 20% fast
twitch fibers, meaning 80% slow twitch would be ideal in an event like crosscountry skiing a predominantly aerobic activity (Katch, Katch & McArdle 2010). The
spread of 40% fast twitch and 60% slow twitch is associated with the standard
trained individual who regularly exercises but does not concentration on either
metabolic system (Katch, Katch, & McArdle, 2010). An individual who contains 60%
fast twitch fibers and 40% slow twitch is switching over to more anaerobic system
dominance. Events like competitive weightlifting would be an example (Hoffman,
2014). Olympic sprinters can be genetically predisposed with up to 80% of fast
twitch muscle fibers (Forshaw, 2013). At maximal testing, like the isokinetic
contraction performed to exhaust the quadriceps recruited fast twitch muscles
fibers because of the criteria of executing all out effort as fast a possible. The fast
twitch muscles fibers produce, the greatest generation of energy but fatigue rather
quickly which is demonstrated in the drop of peak torque towards the end of the
test. The lack of requiring oxygen depletes the current storage of oxygen without
creating more. With increased activity, lactic acid starts to build up and with the
presence of hydrogen and lack of oxygen to buffer or regulate the body’s internal
environment becomes disturbed. The increase rate of roaming hydrogen’s
decreases the pH level, making for an acidic environment. The decrease in pH
causes irritation of the nerve endings on the neuromuscular junctions. The irritation
is responsible for the burning sensation felt when approach ultimate fatigue (Katch,
Katch, & McArdle). When performing at maximal exertion, essentially all fibers are
recruited but the fast twitch will fatigue the quickest then the slow twitch will exert
their supplies then inevitably no more activity can be performed.
Summary:
Measuring one’s peak torque during an isokinetic contraction of the
quadriceps through a knee extension/flexion can assist in determining the range of
muscle fiber proportions. The knowledge of fiber percentage can be beneficial in
areas of delivering evidence to support reasoning behind individual’s performing
different physical events. Specifically in areas of elite athletes, the distribution of
fibers, which is usually genetically predetermined, explains the nature of their
incredible performance. Luckily, there is area to transform fibers per training
effects.
Works Cited:
American College of Sports Medicine & Kaminsky, L. A. (Ed.) (2014). ACSM’s health
related physical fitness assessment manual. Baltimore, MD & Philadelphia, PA:
Wolters Kluwer| Lippincott Williams & Wilkins
Foreshaw, G., (2013). Slow-twitch and fast-twitch muscle fibers. Physiothery and
fitness.
Gandaio, C. B., Pincivero, D. M., & Ito, V., (2003). Gender-specific knee extensor torque,
flexor torque, and muscle fatigue responses during maximal effort contractions.
European Journal of Applied Physiology. 80(2), 134-141. doi:
10.1007/s00421-002-0739-5
Hoffman, J., (2014). Neuromuscular system and exercise. In A. N. Tocco (Ed.) ,
Physiological aspects of sports training and performance. (2nd ed.) (pp. 3-18)
Champaign, Il: Human Kinetics.
Katch, F. I., Katch, V. L., McArdle, W. D., (2010). Exercise physiology: Nutrition, energy
and human performance (7th ed.). Baltimore, MD & Philadelphia, PA: Wolters
Kluwer| Lippincott Williams & Wilkins
Schiaffino, S. & Reggiani, C., (2011). Fiber types in mammalian skeletal muscles.
American Physiological Society. 91. doi: 10.1152/physrev.00031.2010