as people age , age - related changes of physical function affect their ability to walk1 .
as the ability to walk in the elderly 
 decreases , there is an associated decrease in balance ability2 , 3 and independent daily 
 living activities4 and increased risk of 
 falling5 .
therefore , it is necessary for 
 the elderly to maintain the ability to walk .
the ability to walk in the elderly is often 
 represented by the walking speed .
the elderly have low vertical and antero - posterior ground 
 reaction force for support and propulsion related to slower walking speed , with a shorter 
 stride length6 .
thus , these forces can be 
 considered to be factors affecting walking speed in elderly people .
murray and 
 kory7 and finley et al.8 reported that the elderly demonstrate 
 decreased joint angles of the hip , knee , and ankle . through kinetic analysis
, it has been 
 reported that the hip and knee joint moments of the elderly were significantly lower than 
 those of young people9 .
in addition , 
 decline in plantar flexor moment and power in the elderly is related to slower walking 
 speed10 , 11 .
moreover , there are also age - related changes in walking strategy 
 in the elderly . devita and
hortobagyi12 
 reported that elderly people showed different distributions of joint moment and power as 
 compared with young people .
toda et al.13 
 reported differences in joint moment , which were related to the profiles of ground reaction 
 force between the elderly and young people .
these results indicate that the biomechanical 
 impact of aging is not solely represented as a reduction in motor function but also involves 
 a change in control strategy for walking .
local muscle movements are regulated by pools of motor neurons in the spinal cord , which 
 are part of the dispersed locomotor central pattern generator ( cpg ) network14 .
this network in the central nervous 
 system control motor behavior by modulating the appropriate amount , timing , and combination 
 of muscle activation .
muscle activation patterns of the lower extremity during various motor 
 tasks are produced by muscle modules . with regard to walking
, each muscle module corresponds 
 to a key phase of the walking cycle consistent with biomechanical subtasks in walking15 .
previous studies reported that there are age - related changes in 
 muscle modules used in the sit to stand movement17 and in preparation to make a step18 .
regarding walking , muscle activation patterns of the elderly 
 change with age8 , and differences in 
 muscle synergy might be caused by aging19 .
therefore , aging might be associated with the alternation of neural 
 control in muscle activation in various movements .
the targeted neuromotor and biomechanical 
 function , including the timing function , can only be activated by performance of appropriate 
 actions20 . in order to develop optimal 
 exercise regimens to prevent reduction of the ability to walk in the elderly ,
it is 
 necessary to understand the differences in the timing and combinations of muscle activation 
 during walking .
the purpose of this study was to examine age - related differences in muscle modules and to 
 examine the role taken by these muscle modules during walking in both males and females .
we 
 hypothesized that there are age - related alterations of the muscle coordination during 
 walking and that the support and propulsive force corresponding to these muscle modules are 
 reduced with age .
twenty elderly people , 65  years old or older and 20 younger people , aged 20 to 29  years , 
 participated in this study .
the exclusion criteria included neurologic disorders , osteoarthritis , 
 rheumatic arthritis , joint pain affecting walking , and history of surgery in the lower 
 extremities or spine .
all procedures were approved by the hiroshima international university 
 human research ethics committee and all participants gave their written , informed consent 
 prior to enrollment . in the walking trials , all participants walked while barefoot to the end of a 7  m walkway 
 at a self - selected preferred walking speed . a 3d motion analysis system with 8 infrared 
 cameras ( vicon mx ; vicon motion systems , oxford , uk ) and 8 force plates ( amti , watertown , 
 ma , usa ) was used to record kinematic and kinetic data at sampling frequencies of 100 and 
 1,000  hz , respectively .
the force plate layout was designed so as to measure the ground 
 reaction force of each limb using four force plates arranged in the longitudinal direction . 

participants were instructed to walk such that in each step they placed a foot on the left 
 or right force plate , avoiding stepping on two force plates simultaneously . 

infrared - reflecting markers were attached to 30 landmarks according to our previous 
 study13 . walking speed ( m / s )
was calculated from the position of the center of gravity ( cog ) of the 
 whole body .
stride length ( m ) was measured as the antero - posterior distance of the position 
 of the left calcaneal tuberosity marker at a heel contact and the next heel contact .
initial contact was assumed to occur when the 
 vertical reaction force exceeded 10 n , and toe off was assumed to occur in the first frame 
 following the initial contact where the vertical reaction force was < 10 n. muscle forces during walking were estimated using opensim 3.221 .
the body was modeled as a 23 degree - of - freedom linkage 
 actuated by 92 musculotendon actuators .
muscle parameters and path geometries were based on 
 the data reported by delp et al22 . 

optimal muscle fiber lengths and tendon slack lengths were scaled from a generic model to 
 fit each subject using segment dimensions as scaling factors . both ground reaction forces 
 and marker trajectories were low - pass filtered with a fourth - order butterworth filter 
 ( 6  hz )
opensim software24 was used to generate and analyze 
 simulations of walking using a single representative gait trial of each subject .
inverse 
 kinematics and inverse dynamics were subsequently applied , in conjunction with the measured 
 marker trajectories and ground reaction forces and moments , to obtain a set of dynamically 
 consistent joint angles and moments .
the static optimization problem was solved within the 
 opensim environment to determine the set of muscle forces corresponding to the prescribed 
 motion .
the objective was to minimize the sum of squares of all muscle activations in the 
 model23 .
the gluteus maximus ( gmax ) , 
 gluteus medius ( gmed ) , gluteus minimus ( gmin ) , iliopsoas ( il ) , rectus femoris ( rf ) , vastii 
 muscles ( vas ) , hamstrings ( ham ) , gastrocnemius ( gas ) , soleus ( sol ) and , tibialis anterior 
 ( ta ) were analyzed .
the non - negative matrix factorization ( nmf ) algorithm24 , 25 was used for analysis of 
 muscle synergy modules .
nmf defines the muscle activation modules by populating two matrixes 
 indicating the relative weighting of each muscle within each module and reflecting the 
 activation timing profile of the module across the gait cycle .
force values of each muscle 
 were normalized to the maximum value for that muscle so that each value fit between 0 and 1 . 
 to select the number of muscle synergies that could best reproduce the recorded data
, we 
 extracted 17 synergy matrices and synergy activation profile matrices from the muscle force 
 data matrices obtained for each subject .
then , we verified the goodness - of - fit between the 
 original data ( do ) and the reconstructed data ( dr ) matrices , to select 
 the smallest number of muscle synergies that result in an adequate reconstruction of muscle 
 responses .
we calculated the variability accounted for ( vaf ) as the ratio of the sum of 
 squared error values to the sum of the squared original dataset values [ vaf = 1  
 ( do  dr ) / do ] , which was based 
 on the entire dataset .
vaf was sensitive to both shape and magnitude of the original and 
 reconstructed data sets .
calculations of nmf were performed with matlab r2013a ( the 
 mathworks , inc . ,
in order to evaluate the relationship between age - related difference in muscle modules and 
 support and propulsive force during walking , the vertical and antero - posterior ground 
 reaction forces corresponding to the peak value of the activation timing profile of each 
 module were identified . to account for different builds ,
ground reaction force was 
 normalized to each subject s body mass ( n / kg ) . because a previous study reported that there are gender differences in age - related changes 
 in walking characteristics13
a three - way analysis of variance with the 
 number of synergies , age , and gender as factors was performed in order to determine the 
 number of contributing synergies . a two - way analysis of covariance
was performed to examine 
 the difference between the elderly and the younger and the interaction between age and 
 gender groups in muscle weightings using walking speed as a covariate .
the similarities of 
 the activation timing profiles between the elderly and the young were analyzed by 
 cross - correlation analysis in males and females , respectively .
all data were analyzed with the spss 17.0 software 
 ( spss japan inc . , tokyo , japan ) .
the baseline demographic characteristics and spatiotemporal parameters of the study 
 subjects are presented in table 1table 1.characteristics of subjectsvariableelderlyyoungmales ( n = 10)females ( n = 10)males ( n = 10)females ( n = 10)age ( years)68.4 ( 3.0)*69.1 ( 4.3)*21.7 ( 2.1)24.1 ( 2.9)height ( m)1.65 ( 0.07)*1.50 ( 0.03)*1.71 ( 0.07)1.57 ( 0.04)weight ( kg)64.3 ( 10.0)53.9 ( 7.8)60.6 ( 5.1)48.3 ( 6.5)bmi ( kg / m)23.5 ( 2.8)*23.8 ( 3.4)*20.6 ( 1.6)19.4 ( 1.7)walking speed ( m / s)1.16 ( 0.12)*1.15 ( 0.13)*1.28 ( 0.14)1.27 ( 0.07)stride length ( % bh)72.9 ( 5.7)*73.1 ( 5.0)*78.7 ( 5.0)81.1 ( 3.7)value are shown as the mean ( standard deviation : sd).*significant difference from the young at p < 0.05.bmi : body mass index ; % bh : percent body height .
the elderly participants were significantly shorter in body height and higher 
 in bmi , but not significantly different in body mass , as compared with younger participants . 

the elderly males and females had significantly slower walking speeds , along with shorter 
 stride lengths than the younger participants .
bmi : body mass index ; % bh : percent body height the main effect of the number of synergies was significant ( f6 , 
 252 = 454.52 , p < 0.001 ) , and nmf identified five muscle modules , as vaf 
 significantly increased to the fifth of synergies ( fig . 

1.variability accounted for ( vaf ) in the determination of the number of synergies , 
 averaged over the test subjects ( n = 40)vaf indicate the ratio of consistency of both the shape and magnitude of the original 
 and reconstructed data sets . error bars span  one standard deviation ) .
there was no significant interaction between number of synergies and age 
 ( f6 , 252 = 0.61 , p = 0.72 ) , number of synergies and gender 
 ( f6 , 252 = 0.31 , p = 0.57 ) , and number of synergies , age , and 
 gender ( f6 , 252 = 0.27 , p = 0.94 ) .
when the module profiles and 
 weightings were used to reconstruct the muscle force data , they accounted for more than 90% 
 of the muscle force variance for all muscles and regions in the gait cycle .
variability accounted for ( vaf ) in the determination of the number of synergies , 
 averaged over the test subjects ( n = 40 ) vaf indicate the ratio of consistency of both the shape and magnitude of the original 
 and reconstructed data sets .
error bars span  one standard deviation muscle weightings during walking are shown in table 
 2table 2.comparison of muscle weightings indicating the relative contribution of each 
 muscle within the corresponding modulemoduleagegendergmaxgmedgminilrfvashamgassolta1elderlymales ( n=10)0.99 ( 0.83)2.22 ( 0.92)2.24 ( 0.72)0.10 ( 0.24)1.00 ( 0.75)2.30 ( 0.91)0.20 ( 0.50)0.06 ( 0.09)0.52 ( 0.63)1.27 ( 1.00)females ( n=10)1.55 ( 1.17)2.07 ( 1.07)2.11 ( 1.01)0.34 ( 0.74)1.57 ( 0.65)2.14 ( 0.98)0.17 ( 0.18)0.02 ( 0.09)0.42 ( 0.56)1.02 ( 1.13)youngmales ( n=10)0.68 ( 0.51)2.58 ( 0.93)2.50 ( 0.76)0.24 ( 0.50)1.53 ( 0.83)1.86 ( 0.85)0.01 ( 0.26)0.07 ( 0.09)0.44 ( 0.59)0.83 ( 0.63)females ( n=10)0.86 ( 1.01)2.35 ( 0.81)2.11 ( 0.74)0.02 ( 0.06)1.66 ( 0.73)2.02 ( 0.53)0.10 ( 0.26)0.13 ( 0.25)1.28 ( 0.66)0.41 ( 0.51)2elderly males ( n=10)0.95 ( 0.73)1.27 ( 0.58)1.39 ( 0.48)1.50 ( 1.16)0.56 ( 0.50)0.05 ( 0.11)0.17 ( 0.20)3.72 ( 0.37)3.92 ( 0.34)0.84 ( 0.80)females ( n=10)1.32 ( 0.61)0.87 ( 0.71)0.80 ( 0.60)1.89 ( 1.54)1.12 ( 0.78)0.65 ( 1.25)0.18 ( 0.27)3.24 ( 1.18)4.11 ( 0.74)1.64 ( 1.05)youngmales ( n=10)0.43 ( 0.29)0.94 ( 0.60)1.21 ( 0.40)2.15 ( 0.88)0.57 ( 0.45)0.02 ( 0.07)0.11 ( 0.14)3.14 ( 0.95)3.60 ( 0.56)0.21 ( 0.31)females ( n=10)0.95 ( 0.70)0.84 ( 0.45)0.91 ( 0.51)1.76 ( 0.72)0.46 ( 0.33)0.11 ( 0.17)0.28 ( 0.44)3.69 ( 0.69)3.90 ( 0.37)0.87 ( 0.66)3elderly males ( n=10)0.08 ( 0.17)0.16 ( 0.34)0.26 ( 0.33)1.97 ( 0.82)2.61 ( 0.25)1.34 ( 0.79)0.05 ( 0.08)0.02 ( 0.04)0.30 ( 0.29)0.38 ( 0.45)females ( n=10)0.46 ( 0.65)1.02 ( 1.49)1.03 ( 1.39)2.19 ( 1.28)2.25 ( 1.11)1.37 ( 0.78)0.09 ( 0.09)0.53 ( 0.64)0.80 ( 1.21)0.87 ( 0.62)youngmales ( n=10)0.41 ( 1.30)0.10 ( 0.23)0.47 ( 0.33)2.75 ( 1.31)2.63 ( 1.22)0.73 ( 0.75)0.32 ( 0.65)0.17 ( 0.36)0.38 ( 0.32)0.26 ( 0.66)females ( n=10)0.14 ( 0.20)0.45 ( 0.68)0.40 ( 0.31)2.63 ( 0.63)2.54 ( 0.51)1.34 ( 0.42)0.11 ( 0.12)0.04 ( 0.12)0.26 ( 0.31)0.37 ( 0.44)4elderly males ( n=10)1.51 ( 1.17)0.32 ( 0.11)0.27 ( 0.16)0.84 ( 1.19)0.11 ( 0.23)0.04 ( 0.09)2.15 ( 1.17)0.73 ( 0.51)0.06 ( 0.06)1.57 ( 1.19)females ( n=10)2.07 ( 0.86)0.09 ( 0.21)0.27 ( 0.21)0.36 ( 0.33)0.02 ( 0.01)0.04 ( 0.10)2.87 ( 0.29)2.08 ( 1.13)0.29 ( 0.35)1.28 ( 1.03)youngmales ( n=10)1.74 ( 1.03)0.26 ( 0.07)0.45 ( 0.33)0.18 ( 0.21)0.01 ( 0.04)0.00 ( 0.00)2.71 ( 0.51)1.58 ( 1.26)0.19 ( 0.37)0.58 ( 0.60)females ( n=10)2.70 ( 0.53)0.08 ( 0.11)0.55 ( 0.74)0.48 ( 0.32)0.03 ( 0.07)0.01 ( 0.04)2.82 ( 0.34)1.77 ( 0.90)0.13 ( 0.21)0.95 ( 1.21)5elderly males ( n=10)2.01 ( 1.09)0.74 ( 1.00)1.00 ( 0.82)0.95 ( 0.93)0.11 ( 0.19)0.49 ( 0.43)0.86 ( 1.13)0.31 ( 0.25)0.32 ( 0.59)2.42 ( 1.65)females ( n=10)1.25 ( 0.87)0.40 ( 0.58)0.55 ( 0.59)0.91 ( 1.17)0.44 ( 0.80)0.60 ( 0.84)0.34 ( 0.57)0.41 ( 0.43)0.13 ( 0.25)2.74 ( 1.28)youngmales ( n=10)1.39 ( 1.05)0.60 ( 0.83)1.01 ( 0.86)0.45 ( 0.39)0.30 ( 0.52)0.95 ( 0.79)0.21 ( 0.23)0.11 ( 0.17)0.00 ( 0.00)2.56 ( 1.03)females ( n=10)2.12 ( 1.32)0.51 ( 0.51)0.85 ( 0.41)1.03 ( 0.77)0.34 ( 0.90)0.70 ( 0.47)0.43 ( 0.80)0.18 ( 0.23)0.16 ( 0.37)3.18 ( 1.11)value are shown as the mean ( standard deviation : sd).*significant difference from the young at p < 0.05significant difference from the young females at p < 0.05 . module 1 primarily contributes to weight acceptance in early stance .
moreover , muscle weighting of sol exhibited significant interaction between 
 age and gender , and only elderly females had significantly lower muscle weighting as 
 compared with young females .
the muscle weightings of the gmax , rf , and ta significantly 
 increased in the elderly .
in addition , there was significant interaction between age and gender in the 
 muscle weighting of the gas , and only elderly females had significantly higher muscle 
 weighting as compared with young females .
module 4 contributes to deceleration of the leg 
 motion and preparation for weight acceptance in late swing .
the 
 muscle weighting of the gas significantly increased in the elderly , although the 
 contribution was small .
* significant difference from the young at p < 0.05 significant difference from the young females at p
< 0.05 the cross - correlation coefficient between the elderly and young people was large ( r > 
 0.70 ) in all modules in both males and females , and the activation timing profiles of the 
 elderly and young people were highly similar ( table 
 3table 3.similarity of activation patterns of muscle modules between the elderly and the 
 youngmodule 1module 2module 3module 4module 5males0.97 * 0.97 * 0.79 * 0.94 * 0.78*females0.95 * 0.97 * 0.79 * 0.97 * 0.75*values are cross - correlation coefficients of activation profiles . the correlation 
 coefficient ( r )
values are cross - correlation coefficients of activation profiles . the correlation 
 coefficient ( r )
is interpreted as large ( r > 0.7).*p < 0.05 the ground reaction force profiles corresponding to each muscle module are presented in 
 table 4table 4.comparison of vertical and antero - posterior ground reaction force profiles 
 corresponding to each muscle moduleground reaction force ( n / kg)moduleelderlyyoungmales ( n = 10)females ( n = 10)males ( n = 10)females ( n = 10)vertical18.41 ( 1.79)8.67 ( 1.63)9.68 ( 1.76)10.26 ( 0.86 ) 28.93 ( 0.72 ) 9.36 ( 0.43 ) 9.49 ( 0.98)8.81 ( 0.70)37.95 ( 2.21 ) 7.85 ( 2.09 ) 8.38 ( 3.18)9.40 ( 0.78)4 0.08 ( 0.08 )   0.06 ( 0.09 )   0.04 ( 0.06 )   0.08 ( 0.06 ) 53.74 ( 3.86 ) 5.20 ( 3.15 ) 5.45 ( 1.00)5.92 ( 2.56 ) antero - posterior11.49 ( 0.55)1.56 ( 0.36)1.85 ( 0.37)1.93 ( 0.28)20.24 ( 0.13)0.61 ( 0.41 )   0.61 ( 0.37 ) 0.42 ( 0.25)31.61 ( 0.30)1.57 ( 0.37)1.92 ( 0.73)2.32 ( 0.35)40.00 ( 0.01 ) 0.00 ( 0.04 ) 0.00 ( 0.03)0.03 ( 0.03)50.54 ( 0.69 ) 0.54 ( 0.46 ) 0.86 ( 0.46)0.80 ( 0.44)value are shown as the mean ( standard deviation : sd ) .
positive and negative values of antero - posterior ground reaction force indicate 
 anterior and posterior components , respectively .
significant difference from the young males at p < 0.05 .. both the vertical and antero - posterior components corresponding to module 1 
 were significantly lower in the elderly as compared with younger people .
antero - posterior 
 component corresponding to module 3 of the elderly was significantly lower than that of the 
 young .
in addition , the antero - posterior component corresponding to module 2 was 
 significantly lower in the elderly males than that in the young males . value are shown as the mean ( standard deviation : sd ) .
positive and negative values of antero - posterior ground reaction force indicate 
 anterior and posterior components , respectively .
this study investigated age - related differences in the muscle control for support and 
 propulsion during walking in both males and females .
this study revealed that , in the 
 elderly , there were age - related changes in the coordination of muscles around the ankle and 
 that muscles of the lower extremity exhibited co - contraction in late stance .
in addition , 
 these age - related alterations of muscle control might be associated with support and 
 propulsive forces during walking .
these findings support our hypothesis that there are 
 age - related alterations in muscle coordination during walking , and that the support and 
 propulsive force corresponding to these muscle modules are reduced in the elderly .
the timing and composition of each module obtained in this study corresponded to key phases 
 of the gait cycle , consistent with the biomechanical subtasks of walking . in this study
the activation pattern in each module was 
 approximately consistent with previous studies16 , 
 26 .
moreover , the timing and shape of 
 these modules were similar between the elderly and young people in both males and females . 

ivanenko et al.16 reported that there 
 were common basic patterns , even when walking conditions were changed .
the age - related 
 change of the underlying activation timing profile might be small too .
on the other hand , 
 there were age - related alternations in the contribution of muscles to each module . the 
 pattern and combination of muscle activation
are regulated by interneurons in the spinal 
 cord that are part of the dispersed cpg14 .
elderly people had changed the combinations of muscles rather than 
 the activation pattern in order to achieve the walking subtasks .
these muscles 
 generate vertical and backward accelerations of the center of gravity and contribute to 
 support and braking of the body27 . 
 moreover , the contribution of the ta significantly increased in the elderly .
the ta also 
 generates vertical and backward accelerations of the center of gravity in early stance27 .
elderly people have muscle weakness of 
 the lower extremity , especially in the leg extensors28 .
consequently , muscles of the ankle joint as well as the hip and 
 knee joints also participate in weight acceptance .
in addition , the contribution of the sol 
 was large only in young females and significantly decreased in elderly females .
the sol also 
 generates only a small amount of vertical and backward accelerations of the center of 
 gravity in early stance27 and may assist 
 support and braking of the body in young females . especially in females , there are 
 age - related changes in the muscle coordination of the ankle in early stance .
both the 
 vertical and antero - posterior components corresponding to this module were significantly 
 lower in the elderly as compared to the younger people .
the age - related alteration of ankle 
 control in early stance may affect the support and braking force .
the gas and sol contributed in late stance to generate vertical and forward accelerations 
 of the center of gravity , and they contribute to support and propulsion on the body27 .
moreover both elderly males and females 
 had significantly high muscle weightings of the gmax , rf , and ta .
this result suggested that 
 many muscles in the lower extremity in late stance were co - contracting in the elderly . 

co - contraction of lower extremity muscles can be predictive of performance in a dynamic 
 balance test29 and risk of falling during 
 walking30 in the elderly . 

co - contraction of lower extremity muscles in late stance in the elderly may compensate for 
 low balance ability .
only elderly males had a significantly lower anterior component of 
 ground reaction force corresponding to this module compared with young males .
therefore , 
 co - contraction in late stance may lead to low propulsive force with a slow walking speed in 
 elderly males . on the other hand
, there was no difference in this force between the elderly 
 and young females .
the elderly females may have generated propulsive force using various 
 muscles , and there was a gender difference in the effect of co - contraction in late stance on 
 propulsive force .
the rf and il contributed to support , braking , and propulsion of the body in early and late 
 stance .
neptune et al.31 found that the 
 hip flexors , il , and rf made larger contributions to swing initiation and trunk propulsion , 
 respectively .
the muscle weighting of the il in the elderly significantly decreased for this 
 module , and the antero - posterior component corresponding to this module in the elderly was 
 significantly lower than that in the young .
therefore , functional decline of the il in the 
 elderly affected propulsion in late stance , and the elderly depended on the rf in 
 performance of the stance - to - swing transition . moreover , only elderly females had a large 
 muscle weighting of the gas .
support , braking , and propulsion due to this module was 
 performed by co - contraction between the hip flexor and the ankle plantar flexor in the 
 elderly females .
the ground reaction force 
 corresponding to this module was very small , and this module was not directly involved in 
 the generation of ground reaction force .
the ham is activated to decelerate the leg during 
 the swing phase in preparation for foot contact27 .
moreover , both elderly males and females had significantly high 
 muscle weightings of the ta .
the ta generates vertical and backward accelerations of the 
 center of gravity in early stance30 .
the 
 ta in module 1 of the elderly also had significantly high muscle weightings .
it follows that 
 the ta of the elderly greatly contributed to preparation of foot contact from late stance to 
 early stance .
the ta contributes to weight acceptance at initial contact through co - activation of the 
 gmax .
the ankle of the elderly accepted their body weight by 
 co - contraction between dorsiflexors and plantar flexor at initial contact .
the weightings of muscles in the ankle were significantly different between the elderly and 
 the young in all modules .
de vita and hortobagyi12 reported that 
 the elderly showed a redistribution of joint moments and powers , which emphasized proximal 
 extensors and de - emphasized distal extensors compared with the young .
32 , reported that peak ankle joint power 
 generation at pre - swing decreased in the elderly .
it is necessary for improvement of the 
 elderly s ability to walk to inprove ankle control in addition to muscle strengthening , 
 because the influence of functional decline with age is readily apparent in the ankle joint 
 during walking . in this study ,
generally , surface electromyography ( semg ) is often used for the analysis of 
 muscle activity during motion .
however , the results of semg are affected by not only the 
 amount of muscle activity but also the thickness and conductivity of the skin and 
 subcutaneous fat .
basmajian et al.33 
 reported that the integrated value of muscle activity potentials and the muscle force during 
 isometric contraction have a linear or curvilinear relationship . on the other hand ,
the 
 muscle tension force determined by musculoskeletal simulation in the present study was 
 calculated from kinematics data , kinetic data , and physical parameters obtained by the 
 three - dimensional motion analysis system , with the uncertainties inherent to the used model . 

as estimated muscle tension forces were analyzed , it is necessary to confirm the reliability 
 of the estimated data .
the waveform of the muscle force obtained in this study is similar to 
 the waveform of the muscle activity of the lower limbs reported by winter34 .
therefore , the reliability for estimated 
 data of the muscle tension force used in this study was assumed to be good .
first , the model used in this study was 
 identical of the young and the elderly .
the influence of muscle mass difference between the 
 young and the elderly can be removed by normalization according to the subject s body 
 weight , and the dimensions of the segments can be scaled to match the subject in opensim . 

however , viscoelastic changes in muscles and deformation of the spine could not be 
 incorporated into the model . in the future , in order to perform musculoskeletal simulation 
 with higher accuracy , it is necessary to develop a model and simulation system incorporating 
 the physical features of the subject , such as age , gender , and joint deformity .
second , this 
 study showed that muscle modules during walking changed with age , but we were unable to 
 identify the causative factor of the difference in muscle modules between the elderly and 
 young people .
elderly people experience a functional decline in the musculoskeletal system 
 and nervous system with aging .
further studies are required to determine the relationship 
 between muscle control during walking and physical function in the elderly .
 [ purpose ] this study examined age - related differences in muscle control for support and 
 propulsion during walking in both males and females in order to develop optimal exercise 
 regimens for muscle control . [ subjects and methods ] twenty elderly people and 20 young 
 people participated in this study . 
 coordinates of anatomical landmarks and ground reaction 
 force during walking were obtained using a 3d motion analysis system and force plates . 
 
 muscle forces during walking were estimated using opensim . 
 muscle modules were obtained by 
 using non - negative matrix factorization analysis . 
 a two - way analysis of covariance was 
 performed to examine the difference between the elderly and the young in muscle weightings 
 using walking speed as a covariate . 
 the similarities in activation timing profiles between 
 the elderly and the young were analyzed by cross - correlation analysis in males and 
 females . 
 [ results ] in the elderly , there was a change in the coordination of muscles 
 around the ankle , and muscles of the lower extremity exhibited co - contraction in late 
 stance . 
 timing and shape of these modules were similar between elderly and young people . 
 
 [ conclusion ] our results suggested that age - related alteration of muscle control was 
 associated with support and propulsion during walking . 
INTRODUCTION
SUBJECTS AND METHODS
RESULTS
DISCUSSION