Printer Friendly

Simulation of muscle activation patterns in the hip joint during normal level walking followed by sit-to-stand movement between two hip implants.

Introduction

Hip is the second largest weight bearing joint in the human body. The majority of hip failures are due to osteoarthritis, infective and inflammatory arthritis, fractured neck femur, slipped femoral capital epiphysis, avascular necrosis [1], Perthe's disease and hip impingement. Total hip replacement (THR) has a high success ratio in orthopedics. In 1911, Sir John Charnley in Germany carried out the earliest attempt for the joint replacement surgery. Several researchers modified the Charnley model and a better-suited hip prosthesis was designed [2,3].

Implants are made in different shapes and sizes. The implants should mimic the anatomical properties of femur such as, stiffness, range of motion and orientation angle similar to vivo conditions. Otherwise, it may result in loosening accompanied by pain and failure [4]. The longetivity of a hip prosthesis depends upon factors such as selection of material, design of the stem and type of implant fixation. The stem which is considered safe under static loading conditions, may fail in dynamic loading conditions, as factors change under static vs dynamic loading conditions [5,6]. In the late nineties, the stem design consisted of a small femoral head with a larger head cup. This design failed due to several reasons like neck fracturing, fatigue loading and short-term loosening of the implant. Newer designs overcome these limitations and have recommended optimal stem configurations. The design incorporated into the model used in this study is based on these recommendations [7,8].

Measuring parameters such as stiffness, Range of motion, orientation and other physical parameters in vivo is impractical. An alternative could be to simulate these conditions using a powerful biomechanics modeler. The LifeMOD[R] has the capability to create sophisticated human models. It can model human musculoskeletal joints as mechanical parameters like angle, stiffness & damping, orientation of implant fixation and range of motion. Along with these features, we can measure muscle activations, forces, moment and angle of joints for various tasks [9].

Sit to stand and walking are very common activities and are classified as Instrumental Activities of daily living [10]. These activities have been found to be difficult in people who undergo hip replacement surgery [11]. [12] calculated the minimum muscle force required for a sit-to-stand movement in subjects using static optimization and inverse dynamic method. The results exhibited a reduced dynamic hip range of motion for hip implanted leg when compared with normal leg. Studies on ground reaction force, joint moments and differences in gait kinetics, muscle activity pattern have concluded that muscle activity simulation mimic experimental data such as EMG, ground reaction forces, etc,. [13,14].

It is known that forces on the hip joint influences the muscle activation around the hip and vice versa [15]. One of the changes brought about by hip replacement surgery is the altered activation of the muscles around the hip. This has been attributed to the changes in the hip joint configuration as well as the surgical procedure itself [16]. This altered muscle activation has been shown to contribute to alterations in the gait of the patient post surgery and may adversely influence gait parameters such as the weight bearing profile [17], thereby altering the forces through the implant [13]. Since different implants have different sizes and shapes, we may assume that they may also affect the weight bearing profile of the patient. This cycle of muscles influencing weight bearing which in turn influences implant forces may have consequences both on the muscles as well as the implant. Studies have shown that muscle activation patterns change after a hip implant surgery. However, there are no studies to measure the effect of the implant itself on the activation pattern of the muscles.

The primary aim of this study is to determine muscle activation during normal level walking followed by sit-to-stand task, with and without hip implants. Initially this is simulated by inverse-forward dynamic method followed by measuring the activation acting on multiple muscles using LifeMOD[R]. Understanding this effect may be helpful in both the design of the implants as well as in the post surgical rehabilitation of the subjects.

Methods

The initial phase of this study concentrated on the selection of hip implants. Different shapes of femoral stem were considered. From a variety of hip stem designs, literature suggests that the trapezoidal cross-sectional area design in proximal region of femoral stem using titanium material as the most optimal design for load transfer [7]. Therefore, this optimized design is used in this research. The second model used is a standard, generic model present in the LifeMOD[R]. The figure 1 has shown the stem present in LifeMOD[R] and TCSA model.

In this musculoskeletal simulation, the movement consisted of normal level walking followed by sit-to-stand task. The normal level walking is for two steps followed by sit-to-stand from the chair. We used sit-to-stand and normal level walking to represent the most common activities performed as a part of instrumental activities of daily living [IADL].The movement pattern includes the motion, anthropometric data and kinematics for the subject [18]. The simulation is done at 50Hz i.e., 50 frames per second. Initially, the subject walks on a normal level surface with the right leg first and takes 3 seconds to complete and in the fourth second, the subject prepares to sit with both the legs adjacent to each other to sit in the chair. In the fifth and sixth second, the sit-to-stand task is performed and in the seventh second, the subject gets ready for the next move. The complete simulation lasts exactly 7 seconds as shown in figure 2. The study was divided into three case scenarios,

In the first case, the simulation was performed without any implants.

In the second case, the right hip was implanted with an existing model of the hip implant in LifeMOD[R]

In the third case, the right hip was implanted with the TCSA model.

In all the three cases, the left hip remains intact. For all the three cases, we have compared the muscle activation of five muscles that are required for the sit-to-stand and walking. The five muscles are Adductor Magnus, Gluteus Maximus, Gluteus Medius, Rectus Femoris and Iliacus.

Computational procedure

The anthropometric data of the subject is 36-year-old male, 1.7 meter in height and 77 kg in weight for all 3 cases. The joint parameters, marker set and motion data values are taken as per the Total hip replacement manual in LifeMOD[R] software [9]. Only the lower part [locomotion system] is modeled for the human subject body. The incorporated LifeMOD[R] database was used by various research studies [19-22]. The lower part of the locomotion system consists of segments like lower torso, right upper leg, right lower leg, right feet, left upper leg, left lower leg and left feet. All the individual segments are connected by passive joints based on the subject-specific skeleton data. To perform this simulation, the motion agent data in the form of spline data is utilized to move the human musculoskeletal model. The movement is modeled for the subject and biomechanically controlled by equilibrium analysis with motion agent. Initial tension/ contraction of the muscle and stability of the human musculoskeletal subject is performed in inverse dynamic simulation. This is followed by forward dynamic simulation with disabled motion agents. The modeling and simulation of human locomotion system is modeled in LifeMOD[R] [18].

Objectives of the study

Our study had three objectives.

To investigate if there is a difference in the activation between affected and unaffected sides.

To assess if a difference exists in muscle activation between the two prosthesis.

To analyze the muscle activation between the two prosthesis

In all the simulation, the anthropometric data was unchanged. The simulation used only the lower part of the body. The muscle activation was generated for both the lower limbs and the data was analyzed for the difference in activation. In next step, we compared the two prosthesis [existing vs. TSCA] for differences in muscle activation. In the third step we analyzed the difference between the two prosthesis and the differences between the two lower limbs [implanted vs. normal] to understand the changes that the implants bring about in the activation.

Results

Activation of the affected side Vs unaffected side

We found a significant difference among the left and right leg under three cases. The figure 3 has shown the activation characteristics of muscle under three cases [i.e., without implant, existing Model and TSCA Model]. The amplitudes of activation for adductor magnus muscle is 33, 35 and 34 respectively for all three cases in left leg and in the right leg are 23, 5 and 4. The amplitudes of Gluteus Maximus muscle are 43, 42 and 45 for the left leg and in right leg is 44, 27 and 26 for all three cases respectively. The amplitudes for Gluteus Medius [Glu medius] muscle are 35, 36 and 34 for the left leg and activation in right leg is 26, 6 and 5 for all three cases.

The Iliacus muscle [Iliacus] is 27, 26 and 26 in left leg and in the right leg is 9, 3 and 2 in amplitude for all three cases. The activation characteristic of Rectus femoris [Rec femoris] muscle is 35, 36 and 39 and in right leg is 38, 12 and 8 in amplitude for all three cases respectively. This amplitude is calculated by sum of individual muscle activation pattern in the simulation for 7 seconds. From these results we can see that the left leg [i.e., unaffected limb] has the higher activation values when compared to right leg. In right leg, only in the first case the muscles are activated and for other two cases has we found activation to be less in the affected limb when compared to the implanted limb.

Differences in muscle activation between the two prostheses

On further investigation of the muscle activation for the two prostheses, small changes in their muscle activation are noticed. Figure 4 explains the individual muscle activation amplitudes for all three cases. The x-axis states the three cases and y-axis states the amplitude of difference in muscle activation. Therefore, the obtained values for the difference in muscle activation for right and left leg in without implanted case is Rec Femoris [7.75], Glut Medius [8.06], Glut Maximus [8.06], Add magnus [18.28] and Iliacus muscle [1.44]. In other two cases such as existing model value is 25.09, 31.06, 16.54, 31.06 and 24.29 in amplitude, and for TCSA model, value is 31.29, 29.30, 21.14, 29.30 and 25.45 respectively.

For all the five primary muscle, the difference in activation is obtained as sum of muscle activation pattern. In the first case [i.e., without Implant] there is not much difference. Therefore, it has the minimum amplitude in figure 3. In the standard and TCSA model, we found a difference so the muscle amplitudes are higher when compared to that of without implant case.

Analysis of muscle activation

Generally, most of the chosen muscles are active in maneuver. Among the five muscles, it is found that the muscle amplitude is much higher in the Gluteus Maximus and Rectus Femoris. Figure 5 shows the level of muscle amplitude in y-axis, the left [unaffected] and right [implant] leg for higher active gluteus Maximus and Rectus Femoris muscle is plotted. The other three muscles are also active but comparatively less active when compared to these two muscles.

Discussion

Activation of the affected side Vs unaffected side

We found a difference in the activations between left and right hip. In patients with hip replacement surgery we can attribute these changes to various factors such as, inhibition of the muscle post surgery, due to trauma to the muscles etc,., In the simulation we feel that the changes are due to altered kinematics of the implanted hip as well as the biomechanical factors such as stiffness changes. These results are similar to [16] who also found significant difference in post surgery. The possible lateral shift of center-of-mass position to non-operated leg is noticeable which may also be the reason for the differences in activation between the two sides.

Differences in muscle activation between the two prostheses

There is a small difference between the two prostheses. This difference may be the change in the design of the TCSA model, and this model weighs approximately 10 grams less than the existing model. This could be an important factor in causing the difference. The prosthesis may generate different moments in different direction based on the position of the implants relative to the femur. The trapezoidal nature could alter the load transfer from the head to the shaft of the femur [23]. The trapezoidal shape that has been found to be more effective in transferring the load from the head to the distal part of the femur may have also contributed to the difference.

Analysis of muscle activation

On further analysis of the muscle activation, it was found that Gluteus maximus and Rectus Femoris are the two most important contributors of torque that is generated. Gluteus maximus is seen to be most active during the sit-to-stand task, as well as having a constant activity. Gluteus maximus is a prime mover of the hip joint and it is required for all movements that involve anterior movement of the femur. This could be because of weakness of the Glut medius, the Gluteus maximus may work as a prime mover of the hip as well as stabilizer of the hip joint during sit-to-stand and walking. This may explain why the Gluteus Maximus of the left hip is more active than the implanted limb.

Similarly, Rectus Femoris is also found to be active during the sit-to-stand as well as other tasks. The activity of Rectus Femoris can be attributed to the fact that is can act as the prime mover of the hip flexion in case of lack of activity of the other muscles around the hip. Rectus Femoris is a part of the Quadriceps and originates from the anterior inferior iliac spine and is therefore unaffected by the implant, which puts the muscle in a position to move the femur inspite of the other muscles not being active. This could be the reason why Rectus Femoris is found to be active during tasks that requires the femur to move anteriorly or cause hip flexion. Further, we found adductor magnus to be the third most active muscle, in the absence of the prime mover. Adductor magnus may activate to stabilize and mobilize the femur during walking and sit-to-stand.

Conclusion

This paper identified the muscle activation in hip joints during normal level walking and sit-to-stand task for the subjects with and without implant. The alteration of existing femoral stem with trapezoidal cross-sectional femoral stem altered the activation pattern of the muscle across the hip. There is a difference in the muscle activation pattern between the affected and unaffected limbs. We found that the shape alters the muscle activation pattern across the hip and that the muscle, which seems to be the most active during activity are the Gluteus Maximus and Rectus Femoris. This suggests that the shape and mass of the prosthesis may change the activation of muscles across the hip. These factors may be important in future for selection of an implant. It may also help in rehabilitation by giving information about the activity of muscle with respect to the shape of the implants. Therefore, in this study the muscle activations for common activities such as a normal level walking and a sit-to-stand task has been observed successfully.

Limitations and future work

Our study used the anthropometric data of a 36-year-old male, however except in traumatic injuries most of the hip replacement surgeries occur in the later ages. Since age is a factor in the activation of the muscles, it may be considered a limitation. We modeled only few muscles of the hip and knee region, more muscles will be required to study the effect of the implants on the synergistic actions of the muscles. Further studies using experimental data to validate the muscle activation using other anthropometric data such as bone density values, EMG, Ground reaction forces, etc., will help predict the activation patterns more accurately.

Future work will focus on adding the medullary revascularization [24] concept in trapezoidal cross-sectional femoral stem for hip implants by using an optimization tool. However, the results obtained will purely depends on the anthropometric data of the subject including the gait pattern and alignment of hip implant fixation and will not necessarily be the same for different tasks.

References

[1.] Jonsson B, Larsson SE. Functional improvement and costs of hip and knee arthroplasty in destructive rheumatoid arthritis. Scand J Rheumatol. 1991;20(5):351-7.

[2.] Kayabasi O, Ekici B. Probabilistic design of a newly designed cemented hip prosthesis using finite element method. Mater Des. 2008;29(5):96371.

[3.] Kayabasi O, Ekici B. The effects of static, dynamic and fatigue behavior on three-dimensional shape optimization of hip prosthesis by finite element method. Mater Des. 2007;28(8):2269-77.

[4.] Tipper J., Firkins P., Besong A., Barbour PS., Nevelos J, Stone M., et al. Characterisation of wear debris from UHMWPE on zirconia ceramic, metal-on-metal and alumina ceramic-on-ceramic hip prostheses generated in a physiological anatomical hip joint simulator. Wear. 2001 Oct;250(112):120-8.

[5.] Kayabasi O, Erzincanli F. Finite element modelling and analysis of a new cemented hip prosthesis. Adv Eng Softw. 2006 Jul;37(7):477-83.

[6.] Senalp AZ, Kayabasi O, Kurtaran H. Static, dynamic and fatigue behavior of newly designed stem shapes for hip prosthesis using finite element analysis. Mater Des. 2007;28(5):1577-83.

[7.] Sabatini AL, Goswami T. Hip implants VII: Finite element analysis and optimization of cross-sections. Mater Des. 2008;29(7):1438-46.

[8.] Shankar S, Boobalan V. Investigation on Various Proximal Femoral Stem Shapes for Human Hip Prosthesis Using Finite Element Concepts. Trends Biomater Artif Organs. 2013 Aug 19;27(4):153-61.

[9.] LifeMOD Tutorials | Total Hip Replacement [Internet]. [cited 2013 Oct 30]. Available from: http://www.lifemodeler.com/LM_Manual/T_hip.shtml

[10.] Dall PM, Kerr A. Frequency of the sit to stand task: An observational study of free-living adults. Appl Ergon. 2010 Jan;41(1):58-61.

[11.] Boonstra MC, Schreurs BW, Verdonschot N. The Sit-to-Stand Movement: Differences in Performance Between Patients After Primary Total Hip Arthroplasty and Revision Total Hip Arthroplasty With Acetabular Bone Impaction Grafting. Phys Ther. 2011 Apr 1;91(4):547-54.

[12.] Yoshioka S, Nagano A, Hay DC, Fukashiro S. The minimum required muscle force for a sit-to-stand task. J Biomech. 2012 Feb 23;45(4):699705.

[13.] Fang L, Jia X, Wang R. Modeling and simulation of muscle forces of trans-tibial amputee to study effect of prosthetic alignment. Clin Biomech. 2007 Dec;22(10):1125-31.

[14.] Park S-Y, Lee S-Y, Kang HC, Kim S-M. EMG analysis of lower limb muscle activation pattern during pedaling: Experiments and computer simulations. Int J Precis Eng Manuf. 2012 Apr 1;13(4):601-8.

[15.] Lewis CL, Sahrmann SA, Moran DW. Anterior Hip Joint Force Increases with Hip Extension, Decreased Gluteal Force, or Decreased Iliopsoas Force. J Biomech. 2007;40(16):3725-31.

[16.] Foucher KC, Hurwitz DE, Wimmer MA. Do gait adaptations during stair climbing result in changes in implant forces in subjects with total hip replacements compared to normal subjects? Clin Biomech. 2008 Jul;23(6):754-61.

[17.] Talis VL, Grishin AA, Solopova IA, Oskanyan TL, Belenky VE, Ivanenko YP. Asymmetric leg loading during sit-to-stand, walking and quiet standing in patients after unilateral total hip replacement surgery. Clin Biomech Bristol Avon. 2008 May;23(4):424-33.

[18.] Baritz M, Cotoros D. Modeling and simulation of human locomotion system structure and behavior by dedicated software #x2014; LifeMode. 2011. p. 1-4.

[19.] Areiza DA, Brosses ES, Mommers X, Bonnet AS, Zwetyenga N, Lipinski P. Asymmetric kinematics and dynamics of the temporomandibular joint without pain: a case report. Comput Methods Biomech Biomed Engin. 2013;16(sup1):297-9.

[20.] Dao TT, Marin F, Ho Ba Tho MC. Influence of anthropometrical and geometrical parameters of the bones and muscles on musculoskeletal model of the lower limbs. Comput Methods Biomech Biomed Engin. 2009;12(sup1):91-2.

[21.] Huynh KT, Gibson I, Jagdish BN, Lu WF. Development and validation of a discretised multi-body spine model in LifeMOD for biodynamic behaviour simulation. Comput Methods Biomech Biomed Engin. 2013 Apr 28;

[22.] Stops A, Wilcox R, Jin Z. Computational modelling of the natural hip: a review of finite element and multibody simulations. Comput Methods Biomech Biomed Engin. 2012;15(9):963-79.

[23.] Senanayake SMNA, Gopalai AA. Human Motion Regeneration using Sensors and Vision. 2008. p. 1032-7.

[24.] Yang C-T, Wei H-W, Kao H-C, Cheng C-K. Design and test of hip stem for medullary revascularization. Med Eng Phys. 2009 Oct;31(8):994-1001.

V. Boobalan (a), S.N. Omkar (a), D.V. Ramesh (b) & S. Shankar (c)

(a) Department of Aerospace Engineering, Indian Institute of Science, Bangalore 560012, India.

(b) Department of Physiotherapy, M.S. Ramaiah Medical College, Bangalore 560054, India.

(c) Department of Mechatronics Engineering, Kongu Engineering College, Anna University Erode 638052, India.

Corresponding author: S.N. Omkar; omkar@aero.iisc.ernet.in

Received 6 November 2013; Accepted 1 December 2013; Available online 1 March 2014

Fig 4: Difference in muscle activation for right and
left limbs under three conditions

Difference in activiation: (RIGHT-LEFT) in lower Limbs
under three conditions

Rectus Femoris     7.75   25.09   31.29
Gluteus Medius     8.06   31.06   29.30
Gluteus Maximus   -1.44   16.54   21.14
Adductor magnus    8.06   31.06   09.30
Iliacus           18.26   24.29   25.45

Note: Table made from bar graph.
COPYRIGHT 2014 Society for Biomaterials and Artificial Organs
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2014 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:Original Article
Author:Boobalan, V.; Omkar, S.N.; Ramesh, D.V.; Shankar, S.
Publication:Trends in Biomaterials and Artificial Organs
Article Type:Report
Date:Jan 1, 2014
Words:3613
Previous Article:Use of nano-bioglass scaffold enhanced with mesenchymal stem cells for rat calvarial bone tissue regeneration.
Next Article:Nano-rough topography of the scaffold enhances osteoblast attachment: a review.
Topics:

Terms of use | Privacy policy | Copyright © 2021 Farlex, Inc. | Feedback | For webmasters |