Gait is the manner or style of walking (Keane., 2003). Human walking is very complex and requires co-ordinate movement in the lower limb, pelvis, spine and upper limb. Body weight is shifted from the right and left lower limbs as the spine rotates and the arm swing to make a balancing effect on the shifting weight. Gait is commonly divided into two phases i.e. Stance, when foot is contact with the ground and Swing, when there is non-weight bearing (Nordin& Frankel., 2012).

Muscle Force is a way to transfer force from natural form to mechanical form within the body to drive an external object. In walking or during exercise, the force is determined by the joint torque or moment and the muscle arm to the joint centre. Therefore, to calculate muscle forces, the joint moment must be collected using a motion capture system.

There is common belief that men and women walk differently, and the previous study has found out that there are gender differences between the walking (Gait) patterns between young Male and Female Population (Cho et al., 2004). Female walking at an average speed tends to have shorter stride length and slower gait speed compared to their young male counterpart; this primarily attributed to their shorter height. It was also observed by (Kerrigan et al., 1998) that females tend to generate higher mechanical joint power from the hip and knee joints region mainly in the late stance phase as compared to male counterpart population.

The directional motive of the this study was to know the muscle forces from males and females in the general walking (gait) pattern, because it translates to injury in more dynamic activities; Osteoarthritis more prevalent in females, also in medicine various pathologies exist mainly as osteoarthritis (McKean et al.,  2007 and Boyer et al., 2008 ), Diabetes (Dingel et al., 2006 and Meisinger et al.,  2002), Non-contact anterior cruciate ligament tear (Arendt et al., 1995 and Ferretti et al., 1992) to name the few, due to increase load and force on the weight-bearing joints, thus understanding sex differences in muscle force and use of major muscle groups during gait has an immediate impact to the fields of medicine and clinical gait analysis.

This study aimed to assess muscle forces between genders during walking, and has been carried out at the Gait Biomechanics Laboratory of the Institute of Motion Analysis and Research (IMAR), Tayside Orthopaedics and Rehabilitation Technology (TORT) Centre, Ninewells, Hospital and Medical School, Dundee in 2018 – 2019. The research ethics committee approved this study of the university.

The Vicon® Motion Capture System with AMTI® force plate was used to collect the gait parameter and other biomechanical parameters, e.g. joint angle, moment, and range of motion. The muscle forces were estimated using an in-house inverse dynamic model. 

Study population

The inclusion criteria were: healthy male and female subjects aged between 18 to 60 years with no history of injury and no previous history of weakness or surgery in the lower limb. Details about each subject collected in the subject data sheet a total of 26 subjects participated in the study, which included 15 male and 11 female.

Data Collection apparatus

The data collection apparatus used in this study was:

The Vicon®motion captures system with Amti® force plates. Vicon® motion reflective markers were applied over the lower limb.

The Vicon® Motion system with Amti® force plate is a technologically advanced computer-based system with various parts for capturing joint motion and various forces component. Force plate otherwise known as force platform, is the device used primarily to measure the ground reaction force on foot during walking or other activities. In the current study, an integrated Vicon® and Amti® force plate was used to capture the movement, calculate joint angles, forces, moments and powers, using a biomechanical model called Plug-In-Gait provided by Vicon® company. 

Gait Biomechanics laboratory

The data was collected at the Gait Biomechanics Laboratory, which has a motion capturing area and twelve 1.3 mega pixels high resolution camera, located at the Tayside Orthopaedic and Rehabilitation Technology (TORT) Centre, Ninewells Hospital and Medical School, Dundee University, Scotland U.K.

Placement of reflective markers

The anatomical position of the Vicon® reflective markers was defined which was same for all the subjects in this study.

Equipment management before testing

For appropriate equipment management, we did the initial setup of the software, camera and force plate calibration, removing any artefact from camera and force platform. Camera and the embedded force plate

Preparation of the subject

Subject’s anthropometric data were collected (Height, weight, body mass index, leg length, knee width, and ankle width). Then subjects were asked to expose the lower half of their body and they stood in an anatomical position to allow the placement of Vicon® reflective markers. The reflective markers were applied. Double-sided sticky tape was used to keep the markers in position on the body. A total of 20 reflective markers were used. After this, the walking area was shown, and a normal walking pattern was demonstrated to the subjects to minimise the error during normal walking (gait) cycle.

Data analysis and statistical consideration

The data gathered from all the subjects was assessed carefully using the Plug-in-Gait model, Plug-in-Gait model was used for the lower limb analysis and the model uses direct pose estimation for correlating and computing the position and orientation of each segment based on three tracking markers.

These data were checked and labelled in the Nexus, Labelling under the pre-set protocol through manual labelling. After labelling Nexus pipeline was used for labelleling trial frame.

Once labelling is done, Plug-In-Gait used to calculate joint parameters, i.e., joint angle, forces, moments and power. Also, we manually set three events, i.e., foot strike, foot off and foot strike to define a gait cycle. Finally, the result from Plug-in-Gait was exported as an Excel CSV files and was input into an in-house dynamic model to estimate muscle forces.

Statistical analysis was performed using the SPSS software. The analysis was carried out through multivariate (dependent variable), fixed factor (gender) and covariate as ID, while in main effects we select as descriptive statistic and estimation of effect size was used to scrutinize the results to conclude.

Calculating muscle force

Calculating muscle force, we have used the inverse dynamic method to estimate the muscular forces. Mathematical optimisations have been developed with different objective parameters.

In producing a joint moment, muscles in and around the joint optimally distribute their forces in accordance so that the total muscle force and power reaches to a minimum. With the mathematical formulation (optimisation), the problem can be expressed as follows.

Minimum                                                                       (1)

or:   Minimum                                                          (2)

Subject to      (3)

where f_i (t) muscle force (N) in the muscle at time t; v_i (t) muscle velocity in ith muscle at time t; n the number of muscles; F a vector of muscle forces; A the matrix of moment-arm of muscles; M a vector of joint moments; In our objective study, all musculoskeletal data were collected from the subject measurement itself. Overall the data collected for kinematics and kinetics were done using Vicon® motion capture system and AMTI® force platform, while all the muscle forces for a various muscle group and joints were calculated through the in house model.

Twenty-six participant participated in this study, and they aged between 18 to 60 years (Mean age Male: 32 years; Female: 32 years) with eleven female and fifteen male participant.

Table Ⅰ: Anthropometric Data for male and female

Data shows no significant difference in the anthropometric parameters of male and female. Gait parameters shows there is a significant difference between female to male foot off and ankle width. Female shows an earlier foot off and smaller step width in comparison to male. Males are showing higher cadence then female, Right cadence in male (Mean: 116 step/min) while right cadence in female (Mean: 115 step/min), Left cadence in male (Mean: 116 step/min), Left cadence in female (Mean: 114 step/min).Walking speed is more in male Right: Left (1.269 m/sec: 1.280 m/sec). Foot off is earlier in female, with a mean value of right: left foot off (57.60%:57.90%).

Step width is higher in male in comparison to female. Female has width of 0.147 m on the right and 0.148 m on the left side while male who has 0.213 m in right side and 0.202m in the left side. This value shows that female has a narrower step width in comparison to male.

Muscle force in major muscles

Depicts that Men generated higher forces in almost all major muscle groups than females except Rectus femoris, Vastus, Illiacus, and Soleus, where female generated higher force than males.

Table II: Maximum and minimum force within male and female group

Joint Parameters

Joint parameters depicts significant difference in hip and ankle angle (female>male) with knee moment R.O.M (female>male) ankle moment (female>male).

Maximum hip angle is found higher in female with 33 degree mean in comparison to male with 29 degree mean, whereas hip angle range of motion is 41.79 degree in comparison to male with 40.95 degree. Knee angle range of motion is also higher in female in comparison to male with a mean 58.96 degree to 56.62 degrees in male. Ankle range of motion is found to be higher in the male with mean 35.81 degrees in comparison to female with mean 30.18 degree.

A Joint moment in the hip is found to be higher in females with mean 12 Nm/Kg, while that of males is mean 8.41 Nm/Kg. Knee joint moment mean 11.37 Nm/Kg in females and mean 10.27 Nm/Kg in males. Ankle joint moment is 24.57 Nm/Kg in females while mean 17.20Nm/Kg in males.  

The study aimed to assess the muscle force difference between the genders (male: female) during normal walking; 26 participants participated in the study of which 11 were females and 15 males; all participants were healthy adult aged between 18 to 60 years (Mean age: 32 year). The Vicon® motion capture system was used to collect the joint kinematic and kinetic data for each subject during their regular walking pattern.

The muscular forces operate human walking, and it is produced by achieving an imbalance of forces (Erdemir et al., 2007), thereby achieving acceleration of the body. Any disturbance in musculoskeletal and neurological entity causes much concern on the health system of a country (Woolf et al., 2012) which may arise from any disease, aging process, or any injury.

Estimation of force during walking is helpful in relation to the cause of musculoskeletal–nervous system, e.g., cerebral palsy, stroke. Joint surgery (knee arthroplasty) can produce overloading of joint or reduce load on the joint, which can result in dysfunction in neurocontrol thereby weakening the locomotion control leading to various entity, one of the most typical examples can be falls in elderly. Thus understanding the muscle forces can help us to identify those muscles which are active or inactive and one can plan the rehabilitative and treatment protocol in accordance.

Musculoskeletal injuries and pathology are increasing in number due to a better diagnostic tool and other clinical research tools, one of which is the biomechanical tool from which one can estimate the injury and can do effective treatment management (Fraysseet al., 2009).

Simultaneously gait analysis also plays a crucial role in analysing these joints, for instance, looking for kinetic chain in sporting individual with its effect on pre and post gait analysis.

The biomechanical analysis not only gives us the best supporting measure for treatment but also gives us the changes and varied adaptation in patient movements which ultimately guide us for a better rehabilitation treatment which can achieve overall functional independence (Erdemir et al., 2007). 

Major studies trend in recent era gait analysis has focussed much on the elderly and risk of falling which can further lead to physical frailty and dependence in a day to day social activity (Similia et al., 2015). Recent advancement in gait research has come up with a lot of preventive protocol and rehabilitative exercise (Jill et al., 2018). Falling injury is a significant burden on a health care system of any country, thus showing gait analysis importance in its preventions in elderly. There are other related studies which have been started to show the importance of biomechanical analysis in varied musculoskeletal pathology, but few studies on muscle force effect on joint for various pathology entities in the lower limb (Brunner et al., 2013).

Recent studies in gait analysis even have started focusing on the effect of falling in outdoor footway environment (Cheng et al., 2014). Biomechanical gait analysis plays a crucial on various joints, especially weight-bearing joint like knee joint through which one can diagnose a new pathological condition (Abid et al., 2019). All parameters of gait with angle, moment, and range of motion give an influential impact on various musculoskeletal as well as neuromuscular pathological entities in its diagnosis.

In our study, gait cycle showed early foot off in females in comparison to male due to increasing in walking speed (Bruening et al., 2015), and step width of female was narrower than the male counterpart (Cho et al., 2004).

In our study, female are producing significant difference (p <0.001) in the maximum muscle force of Rectus femoris, Vastus and Soleus muscles where they are producing a more significant amount of force than males. Literature also suggests that the most common causes in musculoskeletal pain and disability in knee joint are due to atypical joint kinetics during gait (Andriacchi et al., 2004). It has been noted that females have a two to three times more risk factor for the degenerative joint disorder, mainly osteoarthritis in comparison to male gender (Buckwalter et al., 2000).

In our study, significant group of muscles around the knee joint, mainly Rectus femoris, Vastus showed increased muscle force in female with comparison to male genders which could be a factor for increasing load within knee joint which is one of the most prevalent causative factors for degenerative changes within knee joint mainly the osteoarthritis (Mills et al., 2013).

Studies supported, that change in the angle and moment of a joint could be a causative factor in various degenerative changes in various joints (Arden et al., 2006). In our study, we can also see the significant difference (p < 0.001) in the hip, knee and ankle angle in female where we have noticed increased angle in comparison to the male genders, while maximum knee moment range of motion increased in the female genders in comparison to their male counterparts.    

There are various muscular and foot injuries which are common in young athletes, mainly muscle strain, apophysitis, severs disease, little league elbow, Osgood slater’s disease, patellofemoral pain syndrome (Adrian et al., 2003) which can lead to debilitating condition and can be assessed early with assessment of gait parameters.

Studies signify the importance of muscle force in reducing the incidence of injury among the athletic population. Some studies have suggested that force production depends on the cross-sectional area of muscle and muscular strength (Jone et al., 2008).

Gait parameter also varies from male to female genders. Several studies have been done to correlate the differences. It has been observed that step length is higher in male in comparison to female and other studies suggested higher cadence in female than men. The various study noted that with increasing age, the step length reduced without much difference in cadence, as reduction of cadence is believed to be due to a reduction in step length. No significant difference has been found between genders in height and step length variation though step width shows significance differences in most of the studies, it is noted that male has wider ankle width while female has a narrower ankle width thereby hypothesising its relation with pelvis width or q angle (quadriceps angle). Gait variation is generally tended to show the difference as the age increases the necessary parameters have also seen to change more exponentially than in younger age group.

Though study showed statistical difference in certain parameters of muscle forces, joint moment and gait parameters but clinical relevance cannot be assured where values are closer to each other, e.g. step width of gait parameters, mean Illiacus muscle forces and knee moment in joint parameters.

Limitation of study

Though this study has analysed the muscular force, joint angle, moment, and range of motion with gait analysis parameter, its related parameters like power could have been added the more results in terms of work and energy consumption. Similarly electromyography could have given correlation with that of muscular force generation within the different muscle group. Factors which could have impacted the muscle force are the different speed within the participant which could have impacted the muscle force. Another aspect could be the sample size, which was limited, and a further increase could have given a broader prospect in results.

Recommendation

As biomechanical gait analysis with different parameters has widely used in the musculoskeletal injury prospect, a future study could focus on the cause of increased muscle force between genders with a specified speed plus strict parameters in term of ideal height, as some studies have shown speed can impact on the results. Various age groups could be, and its impact could also be noted, as certain studies have analysed the correlation among different age groups. Muscle force correlation with electromyography by getting maximum voluntary contraction could give a definitive correlation with the calculated inverse dynamic muscular force. Correlation within the male and female groups can bring up more pathological entities in the foot, ankle and lower limb musculoskeletal and neurological condition as well as in various sporting discipline.

The study has been conducted to assess the muscle force between genders. The data was collected using the Vicon® system and AMTI® force plate. Also, muscle forces were   calculated by an in-house inverse dynamic model.

This study shows maximum higher muscle forces generated in all the primary group of muscle in males except in Illiacus, Rectus femoris, Vastus, Soleus where female showed the greater force than males (p<0.001). The study shows an increased range of motion of hip in female and ankle in male. Gait cycle showed that female has earlier foot off and shorter step width in comparison to a male counterpart.

This study was among the few were the forces were compared between the genders in normal walking pattern, result have shown significant difference in the muscle force among males and females where all the major muscle group showed larger muscle forces in male genders except in the muscle group hip flexor and knee extensors where female has shown more force which could be contributing factor in early degenerative changes in weight bearing joints though further studies are required to validate.

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