## 1 Introduction  
The walking style of Parkinson's disease (PD) patients, the Parkinsonian gait (PG), is characterized by small shuffling steps and hypokinesia in comparison with normal subjects, whose gait is rhythmic when walking on an even surface [1]. There is significant deterioration of the gait of PD patients with the progression of the disease [2; 3; 4], and this is a major cause of their falls and injuries [2; 5; 6].  
In comparison with control subjects, PD patients have reduced stride length [7; 8] and walking speed [7; 9] with increased double-support duration [10; 11; 12; 13] during free ambulation on an even surface. Neurologists monitor their patients by observing their gait, to determine the progression of the disease and the efficacy of treatments [14; 15; 16]. This requires a significant amount of time on the part of experienced neurologists, and there is a need for quantifiable gait analysis that can be performed without the extensive infrastructure used to monitor the severity of PD.  
Many studies have quantified the difference in the gait of PD and control subjects by using devices such as insole sensors to record the gait parameters [17; 18; 19; 20]. It has been found that there is higher variability [18; 21; 22] and changed fractal properties [17; 18; 23; 24] of the inter-stride intervals in PDpatients. [PERSON] et al. [25] studied the spectral properties of stride variability and found that the range of power spectrum was four times larger for PD than control. [PERSON] et al. [26] have developed a statistical model to describe the higher gait variability in PD patients. This increase has been proposed for diagnostics and monitoring the progression of the disease.  
A number of factors can influence the change in the gait of a person, and the inter-stride interval is very gross and unspecific. Besides neurological disorders such as PD, a skeletal disease such as arthritis can also reduce the speed of walking and increase the variability in the inter-stride interval. Further analysis of the gait is required to identify the changes due to this disorder.  
Gait has four major subcomponents that can be estimated from the heel-strike data: stride, swing, stance, and double-support intervals. The swing phase resembles the motion of a free-swinging pendulum [27; 28], requiring minimum neuromuscular control, and is thus expected to be least disturbed by a neurological disorder. This is confirmed by the observation that in PD patients, swing-time variability is not affected by changes in gait speed [29]. The stance phase, on the other hand, requires the simultaneous control of multiple muscles and is most likely to be affected by neurological disorders [23]. This explains the significant increase in the percentage of the stance phase in PD patients when compared to that of the control group [30], and the increased double-support duration [30; 31]. This paper reports a statistical analysis of the four phases of the gait of PD and control subjects to identify which of these are most affected by disease and could thus be considered for diagnosing or monitoring PD.  
The other important factor of gait that can be obtained from the heel-strike data is lateral asymmetry. There is a natural asymmetrical gait pattern in humans due to limb dominance [32]. During walking, the nondominant lower limb contributes more towards support, and the dominant limb contributes more to propulsion [33]. However, loss of limb coordination in producing rhythmic motion may cause pathological asymmetric gait [34]. This project has also investigated the lateral difference in the gait parameters for PD patients.