**2. Gait analysis: relevance and impact in an e-Health scenario**

Gait analysis research was given a pilot role in the nineteenth century, when the study of gait parameters started to be relevant in sports and medicine [7]. Regarding the medical point of view, from gait pattern analysis, a change in its normal parameters can reveal key information on patient's quality of life and/or in the evolution of different diseases. Gait disorders affect a large number of world population, since they are direct consequence of neurodegenerative diseases, such as spinal amyotrophic, multiple sclerosis, amyotrophic lateral sclerosis, neuromuscular diseases, cerebrovascular and cardiovascular pathologies, or even the physiological aging process [8–12]. Neurodegenerative diseases can be reflected in gait by showing a poor balance, a slower pace, shorter steps, lower free speed, and higher cadence [8–11].

The study of dynamic characteristics of human gait for clinical purposes has been widely reported lately. It aims to enhance the life's quality of patients suffering from gait disorders, and also, for their early detection, to enable early diagnosis and an adaptable treatment according to the evolution of the diseases or disorders [7, 13–16].

### **2.1 Gait analysis: gait cycle pattern**

Gait analysis can be seen as the comprehensive study of the human locomotion, which as previously mentioned, has a major role in physical rehabilitation assessment, disorder diagnosis, surgical decision, and recovering follow up. Such study comprises the kinematic analysis (joint angles, angular velocities, and accelerations) and the kinetic analysis (ground reaction and joint forces) during the gait cycles [17, 18].

One gait cycle is the period of time between two consecutive contacts of the heel of the same foot with the floor. Generally, a cycle can be divided in two major phases: the stance phase, corresponding to the period in contact with the ground, which lasts for ~60% of the cycle; and the swing phase, corresponding to the period when there is no contact with the floor, and has a duration of ~40% of the total gait cycle [12, 19]. In **Figure 2**, the different phases are illustrated, along with events and periods that characterize a gait cycle.

The gait cycle can be further subdivided into six periods and eight functional events, five during the stance phase and three in the swing phase. Considering only one limb, the stance phase encompasses three different support periods. The first consists in a period of a double support, which is followed by single

*Applications of Optical Fibers for Sensing*

mechanism is shown.

nium, given a new insight on the FBGs production [2, 3].

(n*eff*) and the grating period (Λ) by the relation [4]:

dependence on strain and temperature can be translated by:

in the doped silica core. Such findings lead to the later confirmation that the refractive index changes could be induced by doping the optical fibers core with germa-

One decade has passed since new breakthroughs emerged regarding the FBGs production methodology. In 1989, Meltz et al*.* reported an FBG external inscription technique. The authors used a split 244 nm beam, which was later recombined in order to produce an interference pattern in the optical fiber core [4, 5]. With this technique, the authors were able to create a periodic and permanent change in the optical fiber core refractive index [5]. The reflected Bragg wavelength can be adjusted by changing the angle between the two split beams. In that way, the period

of the interference pattern and the refractive index will change accordingly. Alternatively, FBGs can be inscribed using phase masks, which are periodic patterns usually etched onto fused silica. In this technique, when the radiation from a UV laser is incident in the phase mask, the diffracted orders +1 and −1 are maximized, while the remaining ones are suppressed, creating an interferometric reflective pattern along the optical fiber core [6]. In **Figure 1**, the FBG inscription based on the phase mask technique as well as a representation of the FBG sensing

The FBG operational principle consists in monitoring the Bragg wavelength (λBragg) shift reflected by the grating, as a function of the monitored parameter. The Bragg wavelength is dependent on the effective refractive index of the fiber core

λBragg = 2n*eff*Λ (1)

Therefore, the Bragg wavelength can be actuated by variations in the grating period or in optical fiber core effective refractive index. So, the Bragg wavelength

ΔλBragg = λBragg(1 − ρα)Δɛ + λBragg(α + ξ)ΔT, (2)

*(a) Schematic representation of the setup typically used to inscribe FBG sensors in photosensitive optical fiber* 

*using the phase mask methodology; and (b) working principle of an FBG sensor.*

where the first term refers to the strain influence on the λBragg and the second describes the temperature effect. Hence, in Eq. (2), ∆λBragg represents the shift of the Bragg wavelength, while ρ, α, and ξ are the photoelastic, thermal expansion,

**24**

**Figure 1.**

### **Figure 2.**

*Representation of the stance and swing phases of a gait cycle.*

support and ends with the second double support period [18–20]. The double support period corresponds to the percentage of the cycle when both feet are simultaneously in contact with the floor and it describes the smooth transition between the left and the right single limbs support [18]. During the first double support, the heel strikes the floor (heel strike), marking the beginning of the gait cycle. The cycle evolves then toward the single period support, with the foot moving down toward the floor into a foot-flat position, where a stable support base is created for the rest of the body. Within the single support phase, the body is propelled over the foot, with the hip joint vertically aligned with ankle joint in the event characterized as the mid stance. From that point onward, the second double support phase starts, with the lower limb moving the body center of mass forward during the heel rise event, where the heel loses contact with the floor. The last contact of the foot with the floor is made by the big toe (hallux), at the toe off event, which also marks the end of the stance phase and the beginning of the swing phase [20].

During the swing phase, there is no contact between the plantar foot and the floor, and the limb continues its movement forward, which can be divided into three different periods: initial swing, mid swing, and terminal swing. In the initial swing, the lower limb vertical length should be reduced, for the foot to clear the floor and to accelerate forward by flexing the hip and knee, together with ankle dorsiflexion. The mid swing is characterized by the alignment of the accelerating limb with the stance limb. In this phase, the ankle and the hip joints are aligned. During the terminal swing, the limb undergoes a deceleration while it prepares for the contact with the floor, in the heel strike of the start of a new cycle [19–21]. As described, the swing phase is characterized by accelerations and decelerations of the lower limb, which require a more demanding muscular effort at the hip level [18].

### **2.2 Gait parameters**

Gait analysis is a systematic procedure that allows the detection of negative deviations from normal gait pattern, as well as their causes. Based on such analysis, it is possible to quantify the parameters involved in the movement of the lower limbs and retrieve the mechanisms that rule the human body movement [22]. Based on the gait cycle pattern described earlier, there are several parameters that can be physically monitored in order to assess the patient's health: anthropometric,

**27**

**Table 1.**

*Fiber Bragg Gratings as e-Health Enablers: An Overview for Gait Analysis Applications*

• the stance and the swing phases duration for each foot;

and angles (direction of the foot during gait);

spatio-temporal, kinematic, kinetic, and dynamic electromyography (EMG), as shown in **Table 1** [22]. From such parameters, the ones that require a more specialized technology to be monitored outside the clinical environment, and therefore passible of being monitored in a gait e-Health architecture, are [7, 23, 24]:

• the walking velocity and gait cadence (number of steps per unit of time);

• the body posture (bending and symmetry) and the existence of tremors;

• the shear and the foot plantar pressure during the stance phase; and

• The step length, width (distance between two equivalent points of both feet),

• the direction and alignment of the limb segments with the ankle, knee, and hip

The act of walking implies the movement of the whole body, and specifically, it requires a synchronized movement of each lower limb apart. Therefore, the gait pattern of an individual can be affected by a disorder in any segment of the body, like for instance, problems in the spinal cord or from a reduced knee flexion in patients with an anterior cruciate ligament reconstruction [25]. For that reason, the analysis of the gait cycle is a vital tool for the biomechanical mobility monitoring, as it can give crucial information not only about the lower limbs health condition, but also allows to infer details about other possible pathologies related to the dynamic movement of the body [26]. So, by monitoring the parameters previously listed, it is possible to assess the health conditions for the body parts involved in walking, namely the lower limbs and its joint. These parameters can be analyzed using objec-

The subjective analysis is based on the observation of the patient while walking, and is generally performed in clinical environment under the supervision

> Age, gender, height, weight, limb length, and body mass index.

Step and stride length, step width, cadence, velocity, stance and swing phases, and gait cycle events (for

Joint and segments angles, angular motion, acceleration, and segment

Ground reaction forces, torque, and

Motor unit action parameters.

instance, heel strike).

trajectory.

momentum.

**Parameters Definition Evaluation of:**

a simple objective gait evaluation, considering the time-distance

geometric description of the lower limbs motion, without reference to

activity, generally performed by using

EMG surface electrodes.

Anthropometric Related to the corporal dimensions of the human body.

characteristics.

Kinetic Evaluation of the forces involved in the body locomotion.

Spatio-temporal General gait parameters used for

Kinematic Quantification of movements and

forces.

EMG Refers to the analysis of muscular

*Parameters generally used for gait analysis (adapted from [22]).*

*DOI: http://dx.doi.org/10.5772/intechopen.81136*

tive and subjective techniques [7, 27, 28].

joints.
