dopamine - replacement therapy at the early stage of parkinson 's disease ( pd ) improves motor and nonmotor complications . in the advanced stage , however , motor fluctuation is a frequent and disabling problem . up to 50% of patients exhibit motor fluctuation and resistance to medication after the first five years of treatment [ 13 ] . motor fluctuation is estimated by explanations or patients ' diaries , though they are subjective and not quantitative [ 4 , 5 ] . how far are the complaints of patients reliable , that is , how far do they reflect the actual motor fluctuation ? to address this question , motor fluctuation must be objectively quantified for comparison . gait disorders are cardinal symptoms in pd and can be easily quantified since gait movements are defined by three parameters : the cadence ( steps / min ) , the floor reaction force , and stride [ 6 , 7 ] . thus , gait disorders can be physiologically a good model for the quantitative analysis of difficulties in motor execution . to examine motor fluctuation , we developed a long - term monitoring portable device , gait rhythmogram ( pgr ) that measures distinguishably the accelerations induced by gaits [ 811 ] . our previous studies using this new device showed that the range of changes in cadence and gait acceleration was narrow , suggesting that pd patients find it difficult to shift gait parameters in response to varying situations during walking [ 10 , 11 ] . furthermore , we reported a decrease in cadence during the off time , when the pd patients manifested bradykinesia or marked instability , and an increase in the cadence while the patients walked with short - stepping , festination , or freezing of gait [ 8 , 9 ] . the results suggested that various complex pathophysiological changes underlying parkinsonian symptoms can be simply expressed as changes in cadence . long - term monitoring of changes in gait cadence , therefore , can theoretically be used to provide a quantitative measure of motor fluctuation . since this method appears to detect deficits in motor execution , it can , therefore , detect motor fluctuation with a higher sensitivity than the examination of movement poverty by monitoring acceleration by various movements . the aim of the present study was to determine the relationship between complaints of pd patients and true motor fluctuation . for this purpose , daily profiles of motor symptoms must be identified . in the present study , in addition to measuring the cadence , we simultaneously measured changes in the amplitude of gait accelerations , since such amplitude correlates with floor reaction forces and the floor reaction forces are known to decrease during off time [ 8 , 9 ] . by simultaneously tracing alterations in cadence and acceleration , a better identification of motor fluctuation would be possible . using this pgr , we recorded continuously the daily profiles of 54 patients with pd ( age : 71.4  7.0 years , mean  sd , 30 men and 24 women ) . they represented all patients admitted to tokyo medical university hospital between june 2009 and may 2010 , who could walk unaided and showed no peak - dose dyskinesia during  on  time . they included 4 patients with modified hoehn and yahr stage 1.5 , 14 with stage 2 , 10 with stage 2.5 , 24 with stage 3 , 1 with stage 3.5 , and 1 with stage 4 . the clinical status was examined using unified parkinson 's disease rating scale ( updrs ) motor score  on  state   ( table 1 ) . we also included 17 height - matched normal control subjects ( age : 64.7  4.5 years , 8 men and 9 women ) . matching for age and height was based on the finding that gait cycle and floor reaction forces are influenced by these two parameters . all procedures were conducted in accordance with the guidelines of the ethics committee of our institution . the pgr is a small device ( size , 8  6  2  cm , weight , 80  g ) that measures three dimensionally ( ax , ay , and az ) the accelerations accompanied by ( 1 ) limb and trunk movements and ( 2 ) those induced by step - in and kick - off during gait , as reported previously [ 8 , 9 ] . the pgr is attached to the waist of the patient and records the above signals at a sampling rate of 10  msec . when recording is completed , the absolute values of acceleration vectors ( a ; a = ax + ay + az ) are calculated and graphically displayed on the pc . the acceleration vectors caused by stepping can be distinguished from those by other limb and trunk movements or by unexpected artifacts , based on the mathematical method of  pattern matching  [ 8 , 9 ] . since the acceleration wave induced by gait motion was morphologically similar in each patient , correlation was mathematically tested between the concerned waves and the template . after the identification of gait - induced acceleration , the peak - to - peak interval is automatically detected to calculate the duration of a single gait cycle , in addition to the amplitude of gait accelerations . changes in gait cadence ( steps per minute ) and gait acceleration cycle were examined during 24  hrs . probable gait off  group and  probable gait good  group , based on changes in the cadence throughout the day . when corresponding changes were observed between the two gait parameters , we classified these patients into  definite gait off  group and  definite gait good  group . in patients of the latter two groups , we examined the relationship between the gait findings and subjective complaints . in contrast , if no corresponding change was observed , we reserved the assessment of the gait profile and excluded these patients for comparison between gait and subjective records . gait fluctuation was suspected when patients walked with a large fluctuation of the cadence , that is , deviation from the intersubject mean  1sd of the normal controls . the interindividual mean  sd of the normal controls was 110  12 steps / min . thus , the cutoff levels set in the present study were < 98 and > 122 steps / min . first , all activity - related changes were excluded . a simultaneous increase in cadence and acceleration second , gait off was considered to occur only when the cadence change was accompanied with a decrease in acceleration under the interindividual mean  2sd of the normal control . since the interindividual mean  sd of the normal control was 2.78  0.42/sec , the cut - off level was set < 1.94  m / sec . patients were considered to walk well throughout the day without motor fluctuation when walking was achieved with a small fluctuation that was within the interindividual mean  1sd of the normal control . since the interindividual mean  sd of the normal control was 110 12 steps / min , the cut - off levels were set between 98 and 122 steps / min . absence of gait fluctuation was considered when the cv ( coefficient variance ) of the acceleration was less than the interindividual mean + 1sd of the control . we considered that the unusual fluctuation occurred when the acceleration cv was beyond mean + 1sd of the control . since the interindividual mean  sd of the normal controls was 0.20  0.04 patients were asked to classify their symptoms into good , not good , and bad . at every hour , patients recorded in their diaries these subjective comments . forty - one of the 54 patients showed a large cadence fluctuation that deviated from the interindividual mean  1sd of the normal controls ( patients with probable gait off ) . for example , in the patient shown in figure 1(a ) , both the cadence and acceleration increased at 1000 and 1100 , when she was doing housekeeping work and walking outside according to patient 's diary . after excluding the activity - related changes , we checked whether or not the cadence change was accompanied by a decrease in gait acceleration , that is , below the interindividual mean  2sd of the normal control . the decreased cadence corresponded to the decrease in the amplitude of the acceleration ( figures 1(a ) and 1(b ) ) . the bradykinetic decrease in cadence was associated with a simultaneous decrease in acceleration at 1800 . in patient 31 shown in figure 1(b ) , the cadence slowed at 1500 , 1700 , 1900 , 2000 , 2400 , 800 , and 900 , and the acceleration decreased throughout these times . thus , simultaneous changes were confirmed at 1500 , 1700 , 1900 , 2000 , 2400 , 800 , and 900 . another type of fluctuation was observed in patients with the marked short stepping or freezing of gait . 5 ( figure 1(c ) ) walked with marked short - stepping at 1400 , 1500 , 1700 , and 600 . at 600 , the patient appeared to walk with short stepping or freezing and the acceleration simultaneously decreased in amplitude . however , the increase in cadence at 1700 was an activity - related change since acceleration increased at the same time . of the 41 patients with probable gait off , 37 patients were assessed as definite gait off based on the simultaneous changes in cadence and acceleration . no simultaneous changes were observed in the two parameters in the other four patients ( figure 1(d ) ) . thirteen patients of the 54 patients showed small cadence fluctuation that was within the interindividual mean  1sd of the normal controls ( patients with probable gait good ) . examination of these patients showed cv of acceleration below the mean + 1sd ( 0.24 ) in 7 patients . 2 ( figure 2(a ) ) with cv = 0.13 showed small fluctuation also in acceleration . the cv of the other 6 patients was more than the mean + 1sd ( 0.24 ) . figure 2(b ) shows an example of a patient with cv = 0.27 in whom the acceleration showed larger fluctuations . finally , we examined the subjective complaints of the 37 patients with definite gait off and 7 patients with definite gait good . four patients ( 17.3% ) reported no changes in the cadence and acceleration ( patients no . 14 ) . the results of patient no . 2 are shown in figure 3(a ) . however , the pgr showed a distinct fluctuation in gait rhythm in the other 19 ( 82.7% ) patients ( patients no . 15 shown in figure 3(b ) walked a with slow gait cycle and decreased acceleration at 2000 , 2100 , and 100 due to a marked bradykinesia . during the objective gait off time the time during which the patients were not aware of gait fluctuation varied , and included the morning , early afternoon , evening and night ( see patients no . no significant difference was observed in updrs - iii between the patients with synchronization and those lacking such synchronization . the other 21 ( 48% ) patients reported motor fluctuation . in 10 of these 21 patients ( 47.6% ) , there was a good synchronization between subjective off and gait off ( see patients no . 28 ( figure 4(a ) ) felt  good  between 1000 and 1200 and between 800 and 900 . these symptoms correlated well with the increase in cadence and acceleration ( activity - related changes ) , suggesting high physical activity . between 1400 and 1600 and at 1800 , and  not good  between 1700 and 21002200 . coinciding with the subjective off , the cadence and acceleration decreased simultaneously at 1500 , indicative of bradykinetic walking . 27 ( figure 4(b ) ) felt  not good  or  bad  due to the frequent occurrence of the freezing of gait between 0600 and 1200 . the pgr showed changes that coincided with the freezing of gait : an increase of cadence and decrease of acceleration , at 0800 and 900 . in the other 11 ( 52.4% ) patients , the gait parameters did not correlate with the subjective complaints . in three patients ( patients no . 3436 ) , the pgr findings of gait off were not synchronized with the subjective off findings . for example , patient no . 35 ( figure 4(c ) ) felt  bad  between 1200 and 1500 , whereas no changes were noted in cadence . in the other eight patients ( no . however , the gait cadence and acceleration were within the normal ranges at 1500 . at 1800 , no significant difference was observed in updrs - iii between patients with matched and unmatched symptoms  pgr .   taken together , desynchronization was observed between the gait fluctuation and subjective fluctuation in 30 of the 44 ( 68.2% ) patients whose 2-  hours profiles were determined by pgr . the aim of the present study was to examine the relationship between complaints of pd patients and motor fluctuation . we focused on the parkinsonian gait disorder which can be quantified easily by extracting data from the gait cadence and acceleration . previous studies showed that ( 1 ) any increase in the cadence beyond the mean + 1sd is associated with a marked short stepping or freezing and ( 2 ) any decrease in cadence below the mean  1sd is associated with a walking pattern characterized by a marked bradykinetic stepping . thus , the off period reflects the time when the cadence deviates from the range of mean  1sd of the control subjects . in contrast , it is difficult to determine the  on or off  based on the value of gait acceleration alone . this is based on the extremely wide range of the acceleration in daily life walking ( figure 3 of ) . furthermore , the absolute value of the acceleration could be variable depending on the measurement conditions . these features of the two parameters allowed the definition of criteria for identifying gait bradykinetic fluctuation . we first defined candidates of gait off and gait good based on changes in the cadence . second , we tested this validity by examining whether corresponding changes were observed in the gait acceleration . cadence fluctuations beyond the intersubject mean  1sd of the normal control ( normal range ) were presumed to represent motor fluctuation ( probably gait off ) . physical activity was associated with increased cadence and acceleration , due to fast stepping during walking and augmentation of floor reaction force . in the second stage of the study , we matched the changes in cadence to those in acceleration . during the off period , the amplitude of the acceleration should decrease , since the ability to disturbances in force production . in the present study , the cut - off level was defined as the mean  2sd of the control subjects . we demonstrated in our previous studies that acceleration below the mean  2sd was associated with severe disturbances in the production of floor reaction forces ( figure 3 of ) , indicating that this range reflects the off - related changes . based on the above criteria , we examined whether deviations of the cadence beyond the normal range were associated with a simultaneous decrease in the acceleration less than the cut - off level . no such relationship was identified in 4 of 41 patients . in the other 37 ( 90.2% ) patients , however , a total harmony was observed between the cadence and the acceleration changes . cadence within the normal range throughout the day suggested the absence of motor fluctuation during the recording . in patients with probable gait for this purpose , we calculated the coefficient variance ( cv ) of acceleration in control subjects . we defined the cut - off level as 0.24 , corresponding to the intersubject mean + 1sd of the control subjects . any change in acceleration beyond this cut - off level should mean unlikely fluctuation in the control subjects . based on these definitions , 6 of the 13 patients with probable constant showed fluctuation that hardly occurred in the control subjects . the other 7 patients ( 53.8% ) with cv values below the cut - off level were assessed as definite gait good . based on the changes in cadence and acceleration ( gait fluctuation ) interestingly , no such agreement was observed in 30 of the 44 patients ( 68.2% ) . definite gait fluctuation occurred in 19/23 ( 82.7% ) patients who subjectively felt no fluctuation . on the other hand , gait fluctuation was not recorded or did not synchronize with the subjective symptoms in 11/21 ( 52.4% ) patients . one reason for the discrepancy could be that the patient concerns or priorities varied from one patient to another . in some patients , the target of attention might be other types of movement disorders . for example , some patients might feel good when they could easily manipulate their hands . other patients might feel subjectively good upon the improvement of hypokinesia ( difficulty in initiation of movements ) . in such patients , they would estimate to be on time when they easily initiated their movements without hesitation . moreover , other patients might weigh mood disorders such as apathy , rather than movement disorders . thus , the present finding of desynchronization between subjective off and gait off could represent the inherent features of pd itself . another alternative explanation is that some pd patients did not notice motor fluctuation due to deficits in attention to motor deficits . in such a condition , fluctuation in the gait parameters would have occurred even though the patients felt good throughout the day . further studies are needed to perform an advanced statistica analysis , for example , a logistic regression analysis to adjust for these confounding factors . the limitation of the present methodology also should be noticed since our device will only be useful in individuals who have specific gait disorders . the present results showed that subjective assessment does not necessarily match the findings of quantitative objective assessment in pd patients with gait disorders . the results highlight the importance of true assessment of the patients ' complaints to identify the wearing off . for this purpose , an objective long - term monitoring system , including pgr , would be helpful .
in advanced - stage parkinson 's disease ( pd ) , motor fluctuation is a frequent and disabling problem . 
 assessment of motor fluctuation depends on patient 's subjective self - statement . 
 we examined whether the subjective fluctuation matched the objective motor fluctuation defined by gait disorders . using a new device , the portable gait rhythmogram , we recorded gait cadence and acceleration continuously over the 24-hour period in 54 patients with pd and 17 normal controls , for the quantitative evaluation of motor fluctuation . 
 the patients were asked to estimate motor fluctuation every hour . in 44 of 54 patients , changes in the cadence were associated with simultaneous changes in acceleration . 
 we examined the subjective fluctuation in these 44 patients who were confirmed to have motor fluctuation . 
 nineteen ( 82.7% ) of 23 patients who felt no fluctuation showed distinct gait disorders . during off time 
 , they walked with marked short or bradykinetic stepping . 
 no matching changes were observed in either the cadence or acceleration in 11 ( 52.4% ) of 21 patients who perceived motor fluctuation . 
 no synchronization was noted in 30 ( 68.2% ) of the 44 patients , between the times of subjectively assessed motor fluctuation and those of quantitative analysis of gait disorder . 
 this discrepancy suggests that the objective continuous recording of the cadence and acceleration is necessary to understand motor fluctuation .