Guest Post – Defining “Workload”… the Engineering Way

Introduction

The competitive season in many professional sports is long, spanning many months. For example, in European elite basketball (Euroleague), the season starts in the middle of September and ends in the middle of June. Furthermore, teams play two to three high intensity games per week, competing both in the European and local (country) league. There are also practices and frequent travel that don’t allow athletes sufficient time to recover and rest.

Although athletes’ bodies are thought to be the “ultimate machines”, the increased “load” and the short recovery time allowed between competitions and practices cause frequent injuries.

Remarkably, in the English Premier League for example, in the 2016/17 season, clubs had an average of 1410 player-days out, due to injury. The financial burden to the clubs is also significant. According to recent findings, £900 million are lost per season due to injury-related under-performance (1). The picture becomes even bleaker, considering that clubs’ wage costs surpassed £3 billion and the wages/revenue ratio reached 61% in 2018/19 season.

Although there is an increased research focus on injury prevention, a high rate of injuries still plagues sports. Any intervention aimed to reduce the chance of injury must be individualized and tailored to each athlete. There are individual characteristics in tissue resilience, muscle architecture, biomechanics and physiology that render generic injury reduction strategies ineffective.

But first, lets explore soft tissue injury from a mechanics point of view.

Engineering 101

The human myoskeletal system has the remarkable ability to adapt to force. When the imposed force exceeds the tissue’s resilience, injury occurs. To understand how a healthy muscle gets injured, it is fundamental to understand its response to stress and strain. Therefore, from a mechanics point of view, understanding soft tissue injury lies in the understanding of the concept of Load.

Load can be defined either as internal or external (Picture 1). Internal load is (sometimes) subjective and refers to the physiological and psychological strain of the athlete. Its measurement is mostly based on questionnaires about an athlete’s subjective feelings, mood, sleep quality and quantity, stress and anxiety etc. This can help coaches collect valuable information regarding the athlete’s current condition and their capability to perform.

On the other hand, external load relates to the stress imposed on the body that is produced by movement. Unlike internal load, it can be measured by more objective tools and therefore contains less bias. Player Tracking Systems that can efficiently collect raw data, are the industry’s standard tool (e.g. player vest tracker). For example, GPS trackers calculate 3-dimensional acceleration (x, y, z axis), angular velocity (gyroscope), distance covered and heart rate (additional hardware required). Oftentimes, this type of data is used to estimate internal load parameters, such as metabolic work load.

Picture 1: Load types and examples of measured parameters

The standard analysis usually provided through these systems’ software produces numerous calculated parameters that have little (if any) physical meaning.

This then raises the question: do we just need data or meaningful, “usable” information?

To answer this question, we must “dig” a little deeper on semantics. There seems to be a lack of clarity in the literature regarding the use of the term “Load”. Many articles on internal and external load (Francois Gazzano, 2017) report load metrics supported by no units of measurement and with a high bias in the calculation process. For example, does everyone understand what a “workload of 1.200” stands for? Just like in the case of internal load, there were many attempts to interpret external load. But it still remains vague and difficult to calculate. Therefore, we need a “common language” and a precise interpretation of the (external) load so that we can all understand and mean the same thing.

In general, there are five different types of loading (picture 2):

  • Tensile
  • Compressive
  • Shear
  • Torsion
  • Bending
Picture 2: Schematic representation of various loading modes 2

[1] Nordin, M. and Frankel, V.H. (2012) Basic Biomechanics of the Musculoskeletal System. 4th Edition, Chapter 2: Biomechanics of Bone. Lippincott Williams & Wilkins, a Wolters Kluwer Business, Baltimore, 84-85

The analysis of each type of load is beyond the scope of this post. What is important in this discussion, is that human muscle units (fibers) DO receive all those kinds of loads. Specifically, muscles receive mostly loads according to their construction (structure) and direction and their “preferable” axis. Therefore, it is rational to examine them from the engineer’s perspective.

In (Bio)Engineering science, a material’s load refers to the entire collection of forces and moments which act on it. Therefore, we can calculate cumulative force to a surface or an element, measured either in Newton or (Newton * meters). These forces will cause stress and strain on a material.

Stress is defined as force per area unit, which causes the material to change shape. Principal stresses are responsible for volume changes. Shear stresses are responsible for angular changes. Stress refers to the internal (between particles) forces in the object, as a reaction to the external forces (see above), which are applied on it.

Strain is the measure of the material’s deformation, because of the received stress. It is expressed as the extension ratio of the body, surface or element, respectively.

“Bio-Engineering Reflection”

A human muscle unit constitutes a specific “material”, which is loaded during exercise. The accumulated applied forces, produce the respective stress, which in turn causes muscle (material) deformation (strain). It is at this point that muscle injury may occur. Therefore, it’s imperative to calculate and express the applied forces and momentums on the tissues: In other words, we must calculate the Workload and express it in a meaningful way.

EVO Human Performance

As a native Bio-Engineering company, we strongly believe that now – more than ever – lies a tremendous opportunity to establish and embrace a common language for what Workload is (means) in the Sports Industry.

A thorough review of the existent literature resulted in poor bibliography. Only a couple of studies characterize the muscular system as a “material” and consider the ability of muscles to afford engineering loads. Also, very few studies include an applicable laboratory model 3,4 based on inverse kinematics/inverse dynamics5,6,7. None of of the above studies were applicable on the field.

At EVO4HP, we precisely calculate the athlete’s workload by using a tailor-made (personalized) method. Despite the high cost of handling large raw data parameters, we do manage to generate useful information. Artificial Intelligence plays a vital role here, helping us analyze medical and performance data.

Conclusion

The Sports Industry dictates the establishment of an avant-garde language, on top of which crucial concepts, like Workload, will be explicitly defined and leveraged. The accumulated experience of the Engineering domain can prove to be invaluable. Through the lens of Bio-Engineering, it suggests that force/momentum calculations lead to a realistic measurement of the athlete’s workload. By using and understanding a common language, the industry may exchange data more effectively, generate high quality information and draw valid conclusions.

Since every answer brings up a new question, the next one might be… “Where do these loads apply?”

Stay tuned for another engineering solution….


EVO Human Performance

EVO Human Performance is a tech company which delivers AI-powered BioEngineering solutions to the Sports Industry’s main issues: Performance & Injury.

Its growing team of experts assess the human body from the Engineer’s perspective and develop cutting-edge solutions based on the expertise of Computational Fluid Mechanics, Finite Element Analysis and Deep Learning, all wrapped in one application – artemYs.

Whether you represent a Team, an individual athlete, coach or a manager, you may contact us for tailor-made, engineered solutions.

Website: https://evo4hp.com

LinkedIn: evo-human-performance

Twitter: @evo4hp

References:

1 Eyal Eliakim, 2020 [https://bmjopensem.bmj.com/content/6/1/e000675]

2 Nordin, M. and Frankel, V.H. (2012) Basic Biomechanics of the Musculoskeletal System. 4th Edition, Chapter 2: Biomechanics of Bone. Lippincott Williams & Wilkins, a Wolters Kluwer Business, Baltimore, 84-85

3 Anurag J. Vaidya, 2019 [https://pubmed.ncbi.nlm.nih.gov/31877528/]

4 Eijden, 2001 [https://journals.sagepub.com/doi/10.1177/00220345010800101001]

5 Gaddi Blumrosen, 2013 [https://pubmed.ncbi.nlm.nih.gov/23979481/]

6 Jacob Rosen 1, 2010 [https://www.hindawi.com/journals/abb/2010/605978/]

7 Angelos Karatsidis, 2016 [https://pubmed.ncbi.nlm.nih.gov/28042857/]

Top photo by: Photo by Alexander Hipp on Unsplash

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