Date of Award

Fall 2019

Degree Type

Open Access Dissertation

Degree Name

Engineering and Industrial Applied Mathematics Joint PhD with California State University Long Beach, PhD

Program

Institute of Mathematical Sciences

Advisor/Supervisor/Committee Chair

Shadnaz Asgari

Dissertation or Thesis Committee Member

Vennila Krishnan

Dissertation or Thesis Committee Member

Marina Chugunova

Dissertation or Thesis Committee Member

Ali Nadim

Terms of Use & License Information

Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2019 Aisha J Chen

Abstract

Postural analysis is the study of how the position of the body in any mode interacts with internal and external forces. This type of analysis is typically used to assess potential abnormalities in the balance control system and to understand how the balance control system changes with time. However, compared to other medical fields of study, postural analysis is relatively new [1]. In fact, although widely used in clinical and research studies, postural assessment methods are scientifically inaccurate, and some data collection methods are relatively expensive. A better understanding of the human balance control system could lead to more accurate and less expensive postural assessment techniques. The human balance control system must continuously act because the human body is an inherently unstable system. In fact, gait and balance impairments lead to loss of mobility, falls, and a diminished quality of life. Advanced age, orthopedic and neurological conditions affect overall balance control, which leads to gait and balance impairment [1, 2]. In fact, disability, falls and increased mortality are all associated with insufficient balance control during gait and postural support [2].The ability to maintain stability is dependent on executing postural movements to control the temporal and spatial change in the center of mass of the body [3]. The inability to maintain this stability, results in falls and fall related injuries. Although the risk of falling increases with age and neurological condition, there is some risk of falling for adults of all ages and circumstance [4]. In fact, falling is one of the leading causes of accidental death in the United States [5]. In 2015, the total medical cost of falls older adults was $31.9 billion, and of that total $637 million of that cost was due to death [5]. One of the main causes of falls is a trip, which accounts for 35-53% of all falls and is responsible for 12-22% of hip fractures [6]. Therefore, an understanding of the postural instability that leads to a trip could lead to prevention of a significant portion of falls, which would ultimately lead to a decrease in the cost associated with falls. Nonetheless, there are many other factors that can contribute to an individual falling, and a better understanding of the postural control system can lead to an understanding of how to prevent recurring falls. Traditionally, gait initiation and reaction to postural perturbation can be observed in order to evaluate the potential an individual has to fall [7, 8, 9]. In addition, analysis of standing upright posture allows for a better understanding of the overall balance control system and the ability to identify strategies the human body uses to maintain upright posture [10, 11, 12]. Kinematic, kinetic, and electromyographic signals have all previously been used to identify strategies the body can use to main posture, initiate movement, or recover from a perturbation. Each signal offers information about the balance control system, which could ultimately lead to a better understanding of postural stability. While several studies have focused on kinetic and electromyographic (EMG) signals in order to analyze posture during perturbation, there a very few studies that have added kinematic information as a factor [8, 13]. In contrast, there have been several studies that have used kinetic and kinematic signals or kinematic and electromyographic signals in order to analyze gait initiation but there have been only a few studies that have used all three signals [14, 15]. Lastly, most studies focus on kinetic information in order to analyze standing posture, but few studies use both kinetic and electromyographic information[7, 11]. The main purpose of this study is to analysis an appropriate basis for stereotypical gait and posture. A secondary purpose is to analyze how that basis can be applied to gait and postural analysis of people with Parkinson’s disorder.

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