**1. Introduction**

Gait analysis is the analysis of various aspects of the patterns when we walk or run, which are the most common forms of human legged locomotion, as shown in **Figure 1**. Normal gait is achieved when the multiple body systems function properly and harmoniously, including visual, vestibular, proprioceptive, musculoskeletal, cardiopulmonary, nervous systems, etc. Injury or disease of any system may result in abnormal gait with symptoms and dysfunction of joints and muscles [3–5]. Therefore, gait performance is considered to be an indicator and predictor of overall health and functional status of individuals [6–8]. Gait analysis is an active research area for many medical, clinical, and healthcare applications. The validity and reliability of gait analysis depend strongly on the used measuring instruments. Generally, high-quality gait analysis requires accurate, detailed, and comprehensive spatiotemporal characterization of the actual locomotion pattern.

**Figure 1.** *Human gait. (a) Walking gait [1] and (b) Running gait [2].*

**Figure 2.**

*Commonly used gait analysis methods. (a) Visual gait analysis [9], (b) Vicon systems [10], and (c) BTS GAITLAB [1].*

At present, gait analysis in most clinics and health centers is still mainly achieved by patient self-reporting and clinician (physician, nurse, etc.) observation, as shown in **Figure 2(a)**. These subjective and qualitative methods are only suitable for preliminary gait examination. Although some severe gait abnormalities can be visually observed by human eyes, subtle differences might be overlooked without quantitative measurements [11]. With the aid of simple tools like measuring tape, stopwatch, and goniometers, as well as methods allowing leaving footprints on the ground, basic quantitative measures can be derived, such as the number of walked strides/steps, gait cadence, gait speed, stride/step length, stride time, and distance covered. The advantages of the visual observation method and foot-printing method lie in several aspects: (1) they do not require any expensive measuring instruments and complex preparation procedures; (2) they have no special requirements for the working environment; and (3) they can achieve a preliminary gait analysis in a very short time. However, the obtained measures are too limited to assess human gait, as gait is complex and multifactorial in terms of its control mechanisms governed by the neuromuscular system. Besides, the quality of measures is dependent on the observer's experience and the patient's tolerance, especially the inter- and intra-observer variability, which has been shown to significantly influence the disease-specific severity assessment and the subsequent treatment planning.

To provide high-quality quantitative information and objective measurements (some of which might not be measurable with normal clinical examinations) needed for gait analysis, gold standard gait analysis tools have been applied in some specialized centers and clinics, such as optical motion capture systems and force plates. The commonly used such systems are illustrated in **Figure 2(b)** and **(c)**, where the optoelectronic systems capture spatial gait information with infrared cameras tracking the body movement (defined by reflective markers placed on the body), while the force plates provide dynamic gait information by the measuring

**79**

**Figure 3.**

*IMU, and (d) MicroStrain IMU.*

*Applications of MEMS Gyroscope for Human Gait Analysis*

ground reaction forces (GRFs) based on inverse dynamics. When synchronized with each other, these systems can provide both kinematic and dynamic gait information during walking and running. However, although such systems can achieve high-precision gait analysis, they also have many drawbacks, such as their relatively high cost, long setup time, and complicated operation. Furthermore, they are confined to the restricted area where the systems are deployed and hence affect normal movement of the subjects, which may make the derived information fail to reflect the gait patterns in real-world settings. Generally, people only show their

Electromyography (EMG) systems are another quantitative gait analysis technology commonly used in gait-related applications. Such systems can record the electrical signals generated by skeletal muscles and hence provide insights into the patterns of muscle recruitment and neuromuscular control during walking. They are particularly suitable for investigating gait abnormalities manifested by muscle weakness and spasticity. However, EMG measuring is inconvenient in daily usage, as it requires gel, skin treatment, or smart clothes with embedded textile electrodes, especially for the traditional EMG systems that have intricate wires connecting the

For gait analysis, accuracy is not always the only or primary concern, and other relevant concerns include simplicity, accessibility, portability, etc. For example, it might be more meaningful to monitor gait patterns for patients or elders in their daily lives than just a brief examination in a clinic or a gait lab [12]. Therefore, although the optoelectronic, force platform, and EMG systems have been applied to gait analysis in the past decades, they are not pervasive enough, even in specialized centers and clinics, which makes the potential of gait analysis not been fully exploited thus far. In order to make gait analysis more accessible and usable, the use of alternative instruments has been investigated to address the limitations of the gold standard methods, such as inclinometers, goniometers, air pressure sensors, foot switches (or force-sensitive resistors), and inertial sensors. These instruments are more portable, convenient, cost-effective, and easy-to-use, among which inertial sensors are widely considered attractive alternatives. Recent advancements in microelectromechanical systems (MEMS) technology paved a way to develop wearable gait analysis systems constructed of inertial measurement units (IMUs), which have shown remarkable progress in the last two decades. MEMS inertial sensors include gyroscope, accelerometer, as well as a combination of gyroscope, accelerometer, and magnetometer [13, 14]. The commonly used MEMS IMUs in the

Notable use of inertial sensors in gait analysis is in providing rich kinematic information about the movement patterns of different body segments. However, there are issues related to the accuracy of the measurements from these low-cost

*Commonly used inertial sensors based on MEMS technology. (a) InterSense IMU, (b) ADI IMU, (c) Xsens* 

natural gait when they are accustomed to the walking environments.

*DOI: http://dx.doi.org/10.5772/intechopen.86837*

electrodes and the signal processor.

literature are shown in **Figure 3**.

#### *Applications of MEMS Gyroscope for Human Gait Analysis DOI: http://dx.doi.org/10.5772/intechopen.86837*

*Gyroscopes - Principles and Applications*

*Human gait. (a) Walking gait [1] and (b) Running gait [2].*

**Figure 1.**

**Figure 2.**

*GAITLAB [1].*

At present, gait analysis in most clinics and health centers is still mainly achieved

To provide high-quality quantitative information and objective measurements

(some of which might not be measurable with normal clinical examinations) needed for gait analysis, gold standard gait analysis tools have been applied in some specialized centers and clinics, such as optical motion capture systems and force plates. The commonly used such systems are illustrated in **Figure 2(b)** and **(c)**, where the optoelectronic systems capture spatial gait information with infrared cameras tracking the body movement (defined by reflective markers placed on the body), while the force plates provide dynamic gait information by the measuring

by patient self-reporting and clinician (physician, nurse, etc.) observation, as shown in **Figure 2(a)**. These subjective and qualitative methods are only suitable for preliminary gait examination. Although some severe gait abnormalities can be visually observed by human eyes, subtle differences might be overlooked without quantitative measurements [11]. With the aid of simple tools like measuring tape, stopwatch, and goniometers, as well as methods allowing leaving footprints on the ground, basic quantitative measures can be derived, such as the number of walked strides/steps, gait cadence, gait speed, stride/step length, stride time, and distance covered. The advantages of the visual observation method and foot-printing method lie in several aspects: (1) they do not require any expensive measuring instruments and complex preparation procedures; (2) they have no special requirements for the working environment; and (3) they can achieve a preliminary gait analysis in a very short time. However, the obtained measures are too limited to assess human gait, as gait is complex and multifactorial in terms of its control mechanisms governed by the neuromuscular system. Besides, the quality of measures is dependent on the observer's experience and the patient's tolerance, especially the inter- and intra-observer variability, which has been shown to significantly influence the disease-specific severity assessment and the subsequent

*Commonly used gait analysis methods. (a) Visual gait analysis [9], (b) Vicon systems [10], and (c) BTS* 

**78**

treatment planning.

ground reaction forces (GRFs) based on inverse dynamics. When synchronized with each other, these systems can provide both kinematic and dynamic gait information during walking and running. However, although such systems can achieve high-precision gait analysis, they also have many drawbacks, such as their relatively high cost, long setup time, and complicated operation. Furthermore, they are confined to the restricted area where the systems are deployed and hence affect normal movement of the subjects, which may make the derived information fail to reflect the gait patterns in real-world settings. Generally, people only show their natural gait when they are accustomed to the walking environments.

Electromyography (EMG) systems are another quantitative gait analysis technology commonly used in gait-related applications. Such systems can record the electrical signals generated by skeletal muscles and hence provide insights into the patterns of muscle recruitment and neuromuscular control during walking. They are particularly suitable for investigating gait abnormalities manifested by muscle weakness and spasticity. However, EMG measuring is inconvenient in daily usage, as it requires gel, skin treatment, or smart clothes with embedded textile electrodes, especially for the traditional EMG systems that have intricate wires connecting the electrodes and the signal processor.

For gait analysis, accuracy is not always the only or primary concern, and other relevant concerns include simplicity, accessibility, portability, etc. For example, it might be more meaningful to monitor gait patterns for patients or elders in their daily lives than just a brief examination in a clinic or a gait lab [12]. Therefore, although the optoelectronic, force platform, and EMG systems have been applied to gait analysis in the past decades, they are not pervasive enough, even in specialized centers and clinics, which makes the potential of gait analysis not been fully exploited thus far. In order to make gait analysis more accessible and usable, the use of alternative instruments has been investigated to address the limitations of the gold standard methods, such as inclinometers, goniometers, air pressure sensors, foot switches (or force-sensitive resistors), and inertial sensors. These instruments are more portable, convenient, cost-effective, and easy-to-use, among which inertial sensors are widely considered attractive alternatives. Recent advancements in microelectromechanical systems (MEMS) technology paved a way to develop wearable gait analysis systems constructed of inertial measurement units (IMUs), which have shown remarkable progress in the last two decades. MEMS inertial sensors include gyroscope, accelerometer, as well as a combination of gyroscope, accelerometer, and magnetometer [13, 14]. The commonly used MEMS IMUs in the literature are shown in **Figure 3**.

Notable use of inertial sensors in gait analysis is in providing rich kinematic information about the movement patterns of different body segments. However, there are issues related to the accuracy of the measurements from these low-cost

#### **Figure 3.**

*Commonly used inertial sensors based on MEMS technology. (a) InterSense IMU, (b) ADI IMU, (c) Xsens IMU, and (d) MicroStrain IMU.*

MEMS sensors. The derived angle and position estimates are usually corrupted by varying sensor noises and biases, thereby resulting in the well-known continuously increasing error called drift, i.e., angular or positional deviations away from the ground truth. Many researchers addressed these issues and presented different methods to improve the system accuracy. It should be noted that the costs of MEMS accelerometers are decreasing while the accuracy is being improved, whereas the MEMS low-cost gyroscopes could not achieve the required accuracy for precise long-term positioning applications. Generally, MEMS gyroscopes have large bias drifts that can accumulate several degrees of orientation error during even 1 min. Such large error rates make it difficult to choose reasonably priced gyroscopes for inertial navigation applications, and hence the reliability and accuracy of gyroscopes are questionable [15, 16]. However, for gait analysis applications, gyroscope is the preferred device among the inertial sensors, due to the effects of human locomotion that rotational motion is more pronounced than translational motion. The systems using solely gyroscopes can provide both temporal and spatial gait parameters, whereas most other systems using accelerometers or foot switches are limited to temporal parameters merely. Therefore, the purpose of this chapter is to demonstrate the applications of MEMS gyroscope for human gait analysis.
