Gait Analysis Example

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Gait Analysis

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Gait Analysis

Gait analysis in biometrics

Gait analysis has been a subject of discussion for many years as to its use. The recognition f gait by computers requires profound knowledge to instill in them the ability to recognize human traits or gait.

Gait analysis is a new form of technology that has attracted the attention of computer enthusiasts and the medical fraternity alike, due to the profound abilities of the gait (Li, Miaou, Hung, & Sese, 2003). The use of gait falls in two core categories, which are the gait recognition as a biometric and gait use as a means of rehabilitation and sports activity. Gait has attracted a lot of attention in many areas of its abilities. The area, which has attracted most interest, is the visual aspect of recognition by an individual’s gait.

Gait analysis in biometrics works in ways that were never thought as possible in earlier periods (Whittle, 1996).

. However, this has been enabled by the technological advancements in all aspects aiding research in the topic of gait use. Its use in the field of biometrics has enabled identification of suspicious individuals and restricting entry into various premises such as offices and residences of people. This is done is such a way that the biometric system is set in a way that it has the ability to recognize the bodily features of the people it is allowed to give entry or access into various premises.

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Biometrics, which involves identification of people by their features, is a new way of doing things, which can be attributed to the presence technological advancements (Razali & Manaf, 2007)

The common field of biometric is the use of fingerprints in the identification of individuals and facial recognition. These forms of gait analysis are used in numerous countries around the world. This is in areas of ensuring security especially within sensitive areas that are susceptible to criminal acts. Despite the advantages accrued to this forms of gait analysis, they are becoming obsolete in the sense that they are cumbersome in their use. For instance, fingerprint and facial recognition require a lot of effort to identify people. In addition, the gait systems cannot identify all individuals in busy areas such as airports and banks, which are susceptible to criminal, and terror activities.

Hence, these vulnerabilities necessitate the creation of new forms of gait, which are able to recognize individuals even in crowded places with ease and adequate speed simultaneously.

Gait recognition systems work in identical ways (Li et al., 2003). They rely on information fed to them about the specific individual. This enables the system to have background data and be able to recognize individuals at any vantage points. The individual should provide his features portrayed in background viewpoint. The gait detector is placed on a vantage point in order to allow it to recognize individuals from various positions. The gait detector takes up the features identified and compares them with the existing data in relation to the individual. This is with the hope of attaining positive recognition of the individual.

The identification process can be classified into two distinct approaches the motion based approach model based approach. The model based approach focuses on the individual’s bodily features such as posture, walking styles, the height, neck length, feet length and the distance between the pelvis and the feet. Such details are vital in exact body recognition by the gait detector. The motion-based approach is whereby the gait detector recognizes the motion patterns of an individual such as the movement of the hands while walking (Post, 2006). Such movements are put as data and are fed into the gait for future recognition of the individual.

Despite the numerous advantages accrued from the use of gait systems as biometric identifiers. The gait data can be manipulated by use of identical height and items such as clothing and shoes to gain identical height or body size. In addition, body movements can be mastered to gain access of individual residences or other premises. Moreover, the use of gait systems can be used with other forms of identifiers, which enhance their ability to recognize individuals with utmost accuracy.

Gait analysis in rehabilitation and sport activities

Gait analysis systems in the art of rehabilitation treatment and the enhancement of performance of individuals is different is some aspects in relation to gait systems used in biometrics. The gait capture systems are different because they are not invasive in terms of individual privacy, and more so, they do not operate without the consent of the subject.

Gait systems because of consent from the subjects are elaborate in study of the gait. They are efficient because of their incorporation of various systems in the evaluation of the subject’s gait. Methods vary in terms of their application and methodology and more so the treatment of various conditions. Several equipments are used in the evaluation of the gait of an individual, they include, electromyography data, magnetic fields, cameras and force plates (Post, 2006). However, notion capture systems are disadvantageous in that they do not allow outdoor movement and mobile motion capture. This inhibits the medical practitioners from getting a clarified answer in relation to the movements of an individual on real terrain in comparison to the evenly shaped and sized floors in the medical institutions.

Some gait systems use sensors placed on the subject’s body; these sensors are connected to a transmitter, which generates low electromagnetic forces. The electromagnetic enables the connection to the computer, which is programmed with tracking software for monitoring the different positions and movements of the body locations. Despite the efficiency provided by such methods, the method cannot be used effectively in the presence of other electromagnetic fields provided by other electronic equipment within an area. In addition, the presence of metal, which is attracted to any magnetic force, poses a challenge in the use of this method. Other methods use cameras with infrared capabilities. Cameras are used to monitor the markers placed on the subject’s body and they resonate with each movement of the individual. The primary focus of this system is on the central points and joints of the body in the evaluation of the subject.

Artificial neural networks are another form of gait systems in that they use layer feed forward networks to examine the bodily activity of individuals. People with sports injuries, bodily injuries unrelated to sporting activities and those who have ever suffered from stroke require this form of treatment because it focuses on the movement of muscles and other vital body movements (Li et al., 2003). The methods usually use physical assistance from physiotherapists and medical practitioners to assist in the movement and therapy, which might eventually enable movement of the muscles.

Gait analysis is extensive in terms of its study and its use. Gait analysis has been a successful subject of study because it has given people hope of achieving treatments in extensive study of body movements. In addition, it has enabled improvements in the methods used to achieve security in people’s areas of residences, premises and other sensitive pubic and private areas such as military barracks, airports, seaports and banks (Lee, 2003). There is adequate room for more inventions in terms of new gait systems. This can only be facilitated by the presence of new technological advancements, which have aided in the formation of new systems. Such systems will eventually transform the way medical practitioners with specific reference to the physiotherapists involved in the treatment of bodily-related ailments and injuries.

References

Lee, L. (2003). Gait Analysis for Classification. Boston, MA: Massachusetts Institute of Technology

Li, Y., Miaou, S., Hung, K. C., & Sese, J. T. (2003). A Gait Analysis System Using Two Cameras with Orthogonal View. Chung-Li: Chung Yuan Christian University

Post, D. C. (2006). Gait Analysis Review. Washington, DC: Mendeley University

Razali, N. S., & Manaf, A. A. (2003). Gait Analysis for Criminal Identification Based on Motion Capture. Advanced Informatics School, Universiti Teknologi Malaysia

Whittle, M. W. (1996). Clinical gait analysis: A review. Human Movement Science, 15(3), 369–387