# The Relationship between Gait Velocity and Walking Pattern in Hemiplegic Patients
## 4 Discussion  
The assessment of specific compensatory gait strategies as it relates to gait speed in hemiparetic post-stroke patients is a relatively new feature in the literature. Several features of stroke gait were assessed to understand their relationship to gait speed, with particular interest in the presence of global, multi-joint, multi-planar abnormal patterns which would strongly influence the impaired locomotor patterns post-stroke [16]. Gait speed reported in the current study is within the range of mean comfortable gait speed reported for chronic stroke patients in literature, which reports a range between 0.23 m/s and 0.96 m/s [34]. The vaulting and hip hiking combination strategy showed an impact on gait speed in the Wald Chi-Square test. If we look at speed in the single groups, this pattern, however, does not have the highest speed value, but when associated to circumduction the speed value increases. Circumduction alone, present in only two patients, had in fact the highest speed value, but did not feature in the Wald Chi-Square model, probably due to the small number of patients. The lack of a precise gait pattern means a gait more similar to normal gait, since both from gait analysis data and videorecording it was not possible to individuate major specific compensations in any plane. Actually, this group of patients has a large variance of gait speed ranging from 0.22 m/s to 1.07 m/s. Probably, other factors such as the severity of paralysis in terms of spasticity/flacidity, sensory problems or others should have been considered. According to [PERSON] et al., [PERSON] et al. and [PERSON] et al. [34; 35; 36], gender and age did not have any effect on walking speed in hemiparesi or the genetic side. The correlation we found between walking speed and severity of motor paralysis as measured by the Motricity Index, confirms the literature findings, even if this is not the only factor to affect speed, and biomechanical and neurological factors need to be considered [37]. Among neurological factors that affect walking speed, sensory disorder, muscular co-contractions and spasticity, coordination and muscular weakness [37; 38; 39; 40; 41; 42] are all involved. In particular, in terms of the influence of selective muscle strength on the genetic side on walking speed, we found a correlation between quadriceps strength as a knee extensor and a slight correlation with the liigsoas strength as a hip flexor. The implication of these muscles for gait speed agrees with previous findings for hip flexors and quadriceps [42]. Among other muscles of the lower limbs affecting gait speed, the literature also reports ankle dorsiflexor, hip extensor, ankle plantar flexor and knee flexor strength [16; 38; 43; 44; 42], not found in the current study. Unfortunately, the correlation of single muscle strength with each gait pattern was not possible due to the small number of patients in each group. Considering the muscles resulted related to gait speed in the present work (quadriceps and ileopasoas), none are involved in the gait patterns highly related to speed, i.e., hip hiking and vaulting. Furthermore, measuring selective muscle strength in stroke patients is not an easy task due to the presence of spasticity, co-contraction or synergies. This implies that, notwithstanding the use of a dynamometer, the measure may not have been taken appropriately. In addition to the hand-held dynamometer, other authors reported MMT (Manual Muscle Test) and MST (Modified Sphygmomanometer Test) as measuring muscle strength systems. They demonstrated proper strength assessment with optimal reliability, but reported the