**1. Introduction**

Stroke, caused by an effusion of the blood inside the brain tissue (hemorrhage) or by an interruption of the blood supply (ischemia), leads to motor impairments and disorders of the higher functions (e.g. negligence and anosognosia), sensorial and sensitive [1–3].

On the motor plan, the lesion of the central nervous system generates a pyramidal syndrome mainly characterized by a loss of motor selectivity, alteration of motor command, and a muscle over-activity accompanied by exaggeration of the stretch reflex commonly called spasticity. Although 50–80% of the patients recover a locomotor capacity [1, 4], they reported that, due to gait alteration, they lost a lot of autonomy in daily life activities [5–7].

Human gait is a complex phenomenon that must ensure the inter-limb coordination rotation of multiple segments in order to maintain equilibrium during motion [3]. It can be described as a series of segmental rotations of the lower limbs in order to ensure the displacement of the body. These series of cyclic movements can be split into different phases grouped together in a gait cycle. Hemiplegic patients' gait differs from those of healthy people concerning different points like performance and organization. The main anomalies observed in this population are an alteration of spatiotemporal and kinematic parameters. Therapeutic management and prospective follow-up take into account these two points.

Medical care of gait disturbance in stroke patients use different treatments based on clinical evaluation and functional evaluation. Evaluation of the stroke patient's gait aims at characterizing the motor performance to provide clinicians with information on the patient's organizational or performance status and to allow them to consider the most appropriate treatment options.

In the same way, after applying these different therapeutic approaches, the evaluation allows the therapist to determine the effectiveness of the latter in relation to the fixed objective. Among the different methods for evaluating gait, the most commonly used to know the patient's organization during walking are the Functional Gait Assessment (FGA) and the 3D instrumented Gait Analysis (3D-GA).

There are different types of functional tests that can be used in varying scenarios to evaluate the locomotion of hemiparetic patients. Here, we just list some of the most used tests:


The FGAs are performed under the situations close to those of the patient's daily life but do not provide all the parameters characterizing walking. They do not allow observing the evolution of all the parameters and also limit the number of measurable parameters; their measurement is generally not precise because it is too qualitative.

The 3D-GA provides the clinician with all the quantitative information on the state of organization of the musculoskeletal system during the execution of the locomotor task by means of the kinematic, kinetic, and spatiotemporal parameters of the gait. A 3D-GA system uses the absolute three-dimensional location of the object moving relative to a system reference also fixed. It can be typically of optoelectronic type (Motion Analysis, Vicon, Optitrack, Qualisys, Saga, Codamotion, etc.). The patient, equipped with reflective markers located on anatomical points, walks in an environment equipped with optoelectronic cameras that record the displacement of the markers, of a platform of force to detect the events of the gait cycle. A complex post processing on the recorded information extracts the locomotor parameters. This test can only be performed in a hospital environment with limitations due to the size of the environment and its duration.

The walk of the patient in the hospital environment, equipped with these reflective markers, may be not representative of his/her locomotion in everyday life: the distance is too short, the ground is horizontal without asperities, and the trajectory is very often rectilinear. When using a treadmill, the start and stop phases are delicate for the patient's balance. Also, finding a device providing information on walking is a necessity.

An embedded wearable motion analysis system uses a set of sensors worn on the body of the person to measure locomotion parameters. The system must be energy

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**Figure 1.** *Spatial parameters.*

*An Embedded Gait Analysis System for CNS Injury Patients*

efficient, light, and compact and must not interfere with the patient's natural locomotion so that it can be used in patients' everyday life. Information provided by

the embedded system must be similar to those delivered by 3D-GA systems.

**2.1 Changes in spatiotemporal parameters of the gait cycle**

compare the results of different studies or different populations.

• Duration of the different sub-phases, expressed in percentage

• Gait speed, which is the product of the cadence per step length in m/s

If, for a healthy subject, the durations of the sub-phases in a cycle are symmetrical for the left and the right sides, it is not the case for a stroke patient. In that case, the duration of the stance phase and its percentage of the gait cycle decrease for the affected lower limb compared to the healthy subject [12–16]. Moreover, the duration of the single support phase of the paretic side is decreased compared to the healthy side. The spontaneous gait speed can be considered as a significant element that traduces patients' ability to walk [10]. Similarly, different studies [17, 18]

This chapter describes the wireless embedded system for acquiring the locomotor parameters of a stroke person. This system is designed to be used out of hospital environment (i.e. in the patient's daily life). This system is coupled to a gait event detection device to isolate walking cycles. The results of the experiments performed are compared to those provided by the 3D-GA in order to test the accuracy and

The gait cycle, normal or pathologic, is divided into eight sub-phases: initial contact, loading response, midstance, terminal stance, pre-swing, initial swing, mid swing, and late swing [10, 11]. If the full cycle is normalized to 100%, then the stance phase (between initial contact (IC) event and final contact (FC) event) represents 60% and the swing phase 40%. This normalization makes it possible to

The spatiotemporal parameters are often used to describe and characterize the locomotion [3, 10]. **Figure 1** illustrates the definition of the spatial parameters like

*DOI: http://dx.doi.org/10.5772/intechopen.83826*

robustness of the proposed system.

**2. Changes in hemiplegic gait**

step width, step length, and stride length.

The following are the temporal parameters:

• Cadence in number of steps per minute

• Lengths of the step and the stride

*An Embedded Gait Analysis System for CNS Injury Patients DOI: http://dx.doi.org/10.5772/intechopen.83826*

efficient, light, and compact and must not interfere with the patient's natural locomotion so that it can be used in patients' everyday life. Information provided by the embedded system must be similar to those delivered by 3D-GA systems.

This chapter describes the wireless embedded system for acquiring the locomotor parameters of a stroke person. This system is designed to be used out of hospital environment (i.e. in the patient's daily life). This system is coupled to a gait event detection device to isolate walking cycles. The results of the experiments performed are compared to those provided by the 3D-GA in order to test the accuracy and robustness of the proposed system.
