How We Walk
The human walk (gait) is a biomechanical marvel, an innovation as intricate, complex, and successful as the machinery fabricated by the very same minds it has supported for hundreds of thousands of years. For most, this locomotion is intrinsic and thoughtless, a preinstalled cerebral program that launches in the early precognitive years of life. However, there is a series of muscles, ligaments, and bones triggered to drive this forward momentum.
There are two phases of the human gait: the stance phase, in which some part of the foot is fixed to the ground, and the swing phase, in which the foot is off the ground and propelling forward. However, this is an oversimplification of the process. The human gait is explained better as five phases, the last of which being the swing phase. Gait commences with the heel strike, taking place when the heel first touches the ground, and, if locomotion is already in process, absorbing the force of the movement.
This transitions into early flatfoot, after which the heel begins to rise with late flatfoot. Following this step is toe off, which drives forward the swing. The process continues with another heel strike, and so on.
Numerous muscles are responsible for the strength behind this movement, and two joints play pivotal roles. Obviously, there’s the ankle joint, which allows the foot to move up (dorsiflexion) and down (plantarflexion), so that can raise and lower during locomotion. The transverse tarsal joint, which is actually composed of two joints, the talo-navicular and calcaneal cuboid joint, is crucial to the gait process due to its ability to be either loose or rigid. With this joint locking and unlocking, the process can flow smoothly.
However, the keystone to the human gait is the plantar calcaneonavicular ligament (or the spring ligament), which is found on the underside of the foot and connects the calcaneus to the navicular bone. After the swing phase is complete and heel strike occurs, the transverse tarsal joint locks, allowing the foot to act as a shock absorber. At this moment and as the foot rolls into the next phases, the joint locks and the spring ligament creates tension. It releases that tension once the joint locks again during toe off.
About Gait Analysis
This gait process is universal with human beings, but it varies between every single person. This is because anatomical, sociocultural, and genetic factors, as well as simply one’s habits and personality, shape the silhouette of movement by which any individual travels.
Anatomical factors influencing this are blatant: if two people vary in height, their gait will vary in speed. Similarly, disabilities or health issues often are displayed by how an individual walks. However, there are numerous opportunities for the human gait to differentiate, as it begins not with the muscles of the lower leg but the brain. Overall, human locomotion encapsulates movement with the arms, head, legs, and torso, and each can follow habitual paths that may be seemingly capricious and random but are, in fact, repeatable.
Tracking these unique movements is the focus of gait analysis. Gait analysis has its roots in medicine, where it has been used clinically throughout the past century to analyze the locomotor status of patients. By taking extensive observations of the walking habits of patients, physicians have been able to determine their health problems.
However, similar to how gait analysis can uncover a patient’s symptoms in pursuit of solving a deeper problem, the process of analyzing one’s walk also is used for identification and authentication.
Gait analysis for this purpose is founded on the premise that almost everyone has a distinctive walking style, and this behavioral (or arguably, biological) feature can be used for identification, much like the other biometric processes of fingerprint and iris recognition. However, gait analysis has two distinct advantages when compared to these two: it does not require the user’s interaction, and it can be done at a distance.
Current human gait identification is divided into two categories: model-based methods and motion-based methods.
Model-based methods describe human movement using a mathematical model. The exact variables and execution of these mathematical models may vary, but they all seek to understand and predict the motion of one’s body parts and other biomechanical behavior during locomotion. For example, one method divided the body into head, neck, waist, leg, and arm by image segmentation and then obtained the moving curve of these body parts. Another created probabilistic-based gait modeling to describe how a human was walking.
Alternatively, motion-based methods consider the human gait as a sequence of image, and they extract features from these images. One such method employed Hidden Morkov Models to analyze the relationship among the images. Another example overlapped all the images to get Gait Energy Image (GEI). GEI was used as the features to identify humans.
Biometrics and the ANSI X9.84 Standard
Regardless of how it is conducted, gait analysis can be a useful tool for identifying authenticating individuals. Much like the biological features of fingerprinting or facial or iris recognition, gait analysis is a biometric technology, meaning that it involves body measurements and calculations that serve as the “something you are” identity factor.
Biometrics is supported intrinsically by the observable characteristics of an individual, so it has a lot of value for numerous industries. For the financial services industry, for example, the capture and cross-referencing of physical or behavioral features is necessary for the secure management of data. However, the widespread use of this information across public networks can put it at danger.
An American National Standard, ANSI X9.84-2018: Biometric Information Management and Security for the Financial Services Industry, addresses this. It describes the cryptographic guidelines, techniques, protocols, and syntax for the storage and transfer of biometric information and for using biometrics as an identification and authentication mechanism for secure remote electronic access for financial services or even other industries.
You can read more about ANSI X9.84-2018 in our post on the Biometric Information Management and Security for the Financial Services Industry Standard.
