An EMG-Centric Approach to Understanding the Differences Between Adaptive Athletes

Key Takeaways

The current classification system for paralympic swimming is based on qualitative assessments and has been branded as inconsistent, unfair and unscientific. 

By using insights from EMG data, researchers are aiming to produce an improved classification system.

Initial results suggest that EMG data can improve the competitive integrity of Paralympic sports by addressing widespread classification issues.

What is Classification?

The term “classification in Paralympic sports refers to the process of evaluating athletes to determine their level of impairment and performance potential, with the goal of designing an equitable competitive environment. There are different classification systems for each sport and for different types of impairments, including physical impairments, intellectual impairments, and visual impairments. The classification process aims to ensure that no athlete is advantaged or disadvantaged by their impairment when competing.

Classification Today

Classification is a complex and often contentious topic. In Para swimming, athletes with physical impairments are classified on a scale from S1-S10, where S1 is the highest degree of impairment and S10 is the lowest. In this system, components of coordination and strength are measured and then aggregated to produce a single “S-class”.

As an example of this process, and athlete performing a coordination assessment is asked to go through a series of limb movements. The movements get progressively faster, and a classifier with clinical experience evaluates each movement on a scale of 0-5. As scoring is based on the classifier’s individual interpretation of the athlete’s movements, the process is subjective and susceptible to inconsistency. The current system for classifying Para swimmers has seen little change in 30 years and relies heavily on expert judgement rather than scientific research.

Another challenge to the integrity of the classification process is intentional misrepresentation, which occurs when an athlete deliberately underperforms during the classification process with the aim of being assigned to a lower S-class. Within the current system, it is virtually impossible to detect intentional misrepresentation.

As a result, the classification process is considered by some to be inconsistent, unfair, and unscientific.

Using EMG to Assess Physical Impairments

In response to these critiques, researchers led by Prof. Carl Payton at Manchester Metropolitan University and Dr. Emma Beckman at Queensland University are using electromyography (EMG) to contribute to the development of a more scientific, evidence-based classification system. This research uses Trigno EMG equipment, which the researchers received as a result of winning the Rethink EMG Challenge by the De Luca Foundation.

One of the big elements of this research – and this is where the EMG added a really nice element – is trying to develop tests of strength and coordination that are specific to the classification process that are far more objective, reliable, valid, and reliable. So, wherever the athlete goes in the world to be classified, it will be done the same and they’re likely to get the same outcome.

The focus of this research is on physical impairments in para swimmers, and the main aim is to develop tests of strength and coordination that are more valid, appropriate, and objective for classification.  This can be split further into two phases: first, to develop assessments for classification and second, to understand what is happening at the muscular level during these assessments. Electromyography unlocks the ability to examine muscular activity, providing the key to the second phase of this research.  

With the inclusion of EMG, the researchers have three main goals for the second phase of this research: 
  • Compare EMG activity between athletes with and without motor impairment during these assessments. 

  • Examine the impact of fatigue on EMG activity in athletes with and without motor impairment. 

  • Determine if EMG can be used to detect intentional misrepresentation.  

A Look at the Muscular Level

Sensor Locations:

  1. Biceps Brachii
  2. Triceps Brachii
  3. Anterior Deltoid
  4. Posterior Deltoid
  5. Wrist IMU
  6. Rectus Femoris
  7. Vastus Lateralis
  8. Gastrocnemius Medialis
  9. Tibialis Anterior
  10. Ankle IMU

Coordination was measured through a tapping task, where athletes were instructed to tap their hand or foot between two tablets as quickly and accurately as possible. Muscle activity was recorded from four EMG sensors, placed on the key muscle sites outlined above. An additional inertial measurement unit was used to measure the smoothness of the movement, and video was captured to provide a qualitative assessment of movement patterns.

Data were collected from three groups of participants: elite para swimmers with central motor and neuromuscular impairment (CMNI), elite para swimmers without CMNI, and a control group of non-impaired elite swimmers.

Member of the Japan Para swimming team performing motor coordination tests at Manchester Metropolitan’s Institute of Sport during the 2023 Para Swimming World Championships in Manchester. 

Figure 1: Box & Whisker plot of tapping characteristics for the control (AB) and CMNI groups.

Initial results from the coordination tapping task show that tapping duration and variance were much greater in CMNI participants as compared to the non-impaired control group (Figure 1)

When taking a qualitative look at the EMG activity, results indicate that there was less repeatability for an athlete with CMNI compared to a non-impaired control (Figure 2).

Figure 2: EMG RMS for each tapping cycle (overlaid) for a CMNI participant vs. non-impaired control

Figure 3: Duty Cycle and on/off sequence in the biceps brachii for a CMNI participant vs. non-impaired control

A more quantitative analysis is demonstrated through the duty cycle and on/off sequences (Figure 3). According to EMG data, the biceps brachii in the CMNI participant was more active and less consistent than in the non-impaired control. Additionally, the CMNI participant showed more distinct bursts of EMG activity on average as compared to the control, indicating that the muscle went on and off more frequently during the assessment.

Interpreting Data to Revamp the Classification Process for Para Swimmers

Findings from this analysis help inform how EMG activity can change across different levels of impairment and how this corresponds to performance on the tapping task. By understanding this relationship, the researchers can provide evidence-based recommendations to World Para swimming and facilitate the development of a revised classification system.

Prof. Carl Payton

This novel research will contribute to more evidence-based classification in Para swimming. The use of EMG is providing new and valuable insights into strength and motor coordination testing that are essential elements of the classification process.

These results are for the coordination of para swimmers, but Dr. Emma Beckman and the team from the University of Queensland are taking a similar look at strength assessment. With both coordination and strength components, the researchers will be able to design a holistic approach to evaluating the performance potential of para swimmers.

Expanding Beyond Swimming

Through further data analysis, the researchers hope to detect intentional misrepresentation, which is a widespread concern that impacts the validity of classification in every sport. This research lays the groundwork for redefining classification, and it may be used to improve classification in other Paralympic sports in the future.

In this current application, EMG is being used to validate the tests of coordination and strength. However, in the future, it may be possible to include EMG recording within the athlete classification process itself, providing classifiers with additional evidence on which to base their important decisions.

For more information on the use of EMG as a quantitative assessment technique for movement classification, please reach out to contact@delsys.com.

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