# Application of the Gait Kinematics Index in Patients with Cerebral Palsy
## 1 Introduction  
Children's cerebral palsy (CP) is one of the most frequent causes of motor disability in the child population. The global prevalence of CP is estimated at around 1.5 to 3 per 1000 live births [1, 2]. This includes both cases that are diagnosed in the first year of life and those diagnosed later. The disease's severity, patterns of motor involvement and associated impairments, such as those of communication, intellectual ability and epilepsy, vary widely. Due to its clinical complexity and accompanying symptoms, cerebral palsy is divided into different types. There is a marked variability in the classification and function between individuals. For these reasons, patients with CP are taken care of by a multi-specialty team [3, 4, 5, 6, 7]. The classification of gait in patients with CP is very demanding; however, it is of great clinical importance. It enables the start of a proper treatment and makes it possible to avoid recurring problems. Depending on the CP type and its accompanying symptoms, a therapeutic method is selected, e.g., rehabilitation, pharmacological treatment (botulinum toxin, Intrathecal Baclofen Therapy--IBT), surgical treatment (Selective Dorsal Rhizothy--SDR, or Selective Peripheral Neurotomy--SPN) [8, 9, 10, 11, 12, 13, 14, 15, 16, 17]. Also, a significant role in this context is played by an objective analysis of gait based on data and not solely on observations. The different scales of functional assessment (e.g., the Gross Motor Function Classification System (GMFCS), Gross Motor Function Measure (GMFM), PediatricEvaluation of Disability Inventory (PEDI), Manual Ability Classification System (MACS), and Gillette Functional Assessment Questionnaire (FAQ)) are subjective, and results often depend directly on the testing person's experience and knowledge [18; 19; 20; 21]. More and more often, motor functions in patients with motor system dysfunctions are assessed by means of quantitative methods, which are based, among other things, on optical systems for motion analysis. Such an analysis provides many variables, whose simultaneous evaluation is more often than not difficult and time-consuming. An optimum solution supporting this quantitative analysis seems to lie in the index methods, which assess gait using one numerical value (GGI, GDI) or, additionally, with diagrams showing deviations from standard gaits (the Gait Profile Score (GPS), GKI). Moreover, the GKI is equipped with an algorithm enabling the determination of a global indicator of symmetry [22; 23; 24; 25; 26; 27]. The above-mentioned indices make use of various mathematical algorithms and are based on different kinematic parameters. The GGI is based on a selection of 16 time-space and kinematic parameters (mean values, ranges, minimum and maximum values), which, according to clinicians, accurately describe the gait of patients with CP. This index is expressed by means of a single numerical value. The value of the GGI is a measure of the difference between a set of discrete parameters of the gait of a given patient and the mean parameters of the gaits of healthy individuals [23]. The application of Principal Component Analysis makes it possible to avoid errors resulting from the codependence of some variables and the use of different units. On the basis of the GGI it is possible to evaluate how much a given patient's gait deviates from a regular gait (a healthy person's gait) [22]. Despite the fact that the GGI parameters are specifically dedicated to patients with CP, the GDI and GKI appear to be more objective due to the full image of the motion kinematics they provide throughout the whole gait cycle. The ability to assess the full range of motion is important, especially considering the number and variety of motor disorders resulting from brain injury. Using a single numerical value, the Gait Deviation Index (GDI) makes it possible to indicate the deviations between the gait of patients and healthy people.