Open access

Introductory Chapter: Understanding Human Gait

Written By

Manuel Domínguez-Morales and Francisco Luna-Perejón

Published: 05 June 2024

DOI: 10.5772/intechopen.114971

From the Edited Volume

Human Gait - Recent Findings and Research

Edited by Manuel Domínguez-Morales and Francisco Luna-Perejón

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1. Introduction

Human gait, the intricate biomechanical process by which humans move from one place to another, has been a subject of fascination and study for centuries. From the earliest observations of walking patterns to modern-day biomechanical analysis, understanding human gait has profound implications for fields ranging from sports science to rehabilitation medicine. In this introductory chapter, we delve into recent findings and research surrounding human gait, exploring its complexities and the advancements in our understanding of this fundamental aspect of human locomotion.

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2. The basics of human gait

At its core, human gait involves a rhythmic sequence of movements that facilitates locomotion. This sequence typically includes the alternating movements of the lower limbs, coordinated with movements of the upper body to maintain balance and stability. While walking is the most common form of human gait, variations such as running, jogging, and sprinting highlight the adaptability and versatility of this fundamental human function.

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3. Biomechanical factors

The study of human gait encompasses a broad range of biomechanical factors, including the mechanics of joints, muscles, and bones involved in locomotion (see Figure 1). Several research has elucidated the intricate interplay between these components, revealing the complex mechanisms that govern efficient and effective movement [1]. From the role of muscle activation patterns in propulsion to the biomechanics of foot-ground interaction, advancements in technology and methodology have provided new insights into the biomechanical underpinnings of human gait.

Figure 1.

Illustration showing the biomechanical aspects of human gait.

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4. Neural control and coordination

Central to the execution of human gait is the intricate neural control and coordination of movement patterns (see Figure 2). Recent research in neuroscience has shed light on the neural pathways and mechanisms responsible for initiating, coordinating, and modulating gait patterns [2]. Understanding the neural basis of gait not only informs our knowledge of normal locomotion but also provides insights into neurological disorders that affect gait, such as Parkinson’s disease and cerebral palsy.

Figure 2.

Brain imaging illustrating neural control of gait.

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5. Clinical applications

The study of human gait extends beyond fundamental research to clinical applications in rehabilitation and healthcare. Recent advancements in gait analysis technology, such as motion capture systems and wearable sensors, have revolutionized the assessment and treatment of gait disorders [3]. These tools enable clinicians and researchers to quantify gait parameters (see Figure 3), identify abnormalities [4, 5], and develop targeted interventions to improve gait function and mobility in patients with neurological and musculoskeletal conditions [6].

Figure 3.

Motion capture system in a clinical setting.

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6. Future directions

As our understanding of human gait continues to evolve, future research directions hold promise for further advancements in this field. Integrating insights from biomechanics, neuroscience, and clinical practice, researchers are poised to unravel the complexities of human gait and develop innovative approaches to enhance mobility and quality of life for individuals across the lifespan [7].

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7. Emerging technologies and methodologies

The exploration of human gait has been greatly enhanced by emerging technologies and methodologies. High-speed motion capture systems, force plates, and computational modeling techniques have provided researchers with unprecedented levels of detail and precision in analyzing gait patterns [8]. Additionally, advances in neuroimaging technologies, such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), have enabled researchers to investigate the neural correlates of gait control and coordination in real-time [9].

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8. Interdisciplinary collaborations

Collaborative efforts between researchers from diverse disciplines have enriched our understanding of human gait. Interdisciplinary collaborations between biomechanists, neuroscientists, clinicians, and engineers have facilitated the integration of multiple perspectives and methodologies in studying gait [10]. These collaborations have led to innovative research approaches and have accelerated progress in addressing complex questions related to human locomotion.

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9. Environmental influences on gait

Environmental factors play a crucial role in shaping human gait patterns. Recent studies have examined how terrain, footwear, and external conditions influence gait dynamics [11]. Understanding the interaction between individuals and their environment can provide valuable insights into designing accessible urban spaces, ergonomic footwear, and assistive devices for individuals with mobility impairments.

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10. Conclusion

In this introductory chapter, we have explored the multifaceted nature of human gait, from its biomechanical foundations to its clinical applications and future directions in research. As we delve deeper into the intricacies of human locomotion, we gain a greater appreciation for the remarkable capabilities of the human body and the potential to improve outcomes for individuals with gait impairments. In the chapters that follow, we will delve into specific aspects of human gait research, examining recent findings, methodologies, and implications for theory and practice.

References

  1. 1. Winter DA. The Biomechanics and Motor Control of Human Gait: Normal, Elderly and Pathological. Vol. 3. Waterloo: Waterloo Biomechanics; 1991
  2. 2. Neptune RR, Kautz SA, Zajac FE. Contributions of the individual ankle plantar flexors to support, forward progression and swing initiation during walking. Journal of Biomechanics. 2009;42(6):843-850
  3. 3. Whittle MW. Gait Analysis: An Introduction. London, England: Butterworth-Heinemann Ltd; 1991
  4. 4. Domínguez-Morales M et al. Smart footwear insole for recognition of foot pronation and supination using neural networks. Applied Sciences. 2019;9(19):3970
  5. 5. Luna-Perejón F et al. Low-power embedded system for gait classification using neural networks. Journal of Low Power Electronics and Applications. 2020;10(2):14
  6. 6. Perry J, Burnfield JM. Gait analysis. Normal and pathological function. 2nd ed. California: Slack; 2010
  7. 7. Zatsiorsky VM, Prilutsky BI. Biomechanics of Skeletal Muscles. Pennsylvania State University Press, Human Kinetics; 2012
  8. 8. Fregly BJ, Besier TF, Lloyd DG, Delp SL, Banks SA, Pandy MG, et al. Grand challenge competition to predict in vivo knee loads. Journal of Orthopaedic Research. 2012;30(4):503-513
  9. 9. Clark DJ, Christou EA, Ring SA, Williamson JB. Enhanced somatosensory feedback reduces prefrontal cortical activity during walking in older adults. Journal of Gerontology: Series A. 2014;69(11):1422-1428
  10. 10. Graziano MS, Aflalo TN. Mapping behavioral repertoire onto the cortex. Neuron. 2007;56(2):239-251
  11. 11. Mickle KJ, Munro BJ, Lord SR, Menz HB, Steele JR. ISB clinical biomechanics award 2009: Toe weakness and deformity increase the risk of falls in older people. Clinical Biomechanics. 2016;25(9):767-772

Written By

Manuel Domínguez-Morales and Francisco Luna-Perejón

Published: 05 June 2024