As the Olympic games continue, the competitions are intense. Athletes went through extensive preparation and training to reach this stage.
Biosignals are crucial in pre-competition training for performance improvement and preventing injuries, as well as in post-competition training for rehabilitation and preparing for future events.
This article presents several real-world research examples using biosignals in athlete training sessions.
Electromyography-Driven Football Performance
A recent study by Ahmedreza Firouzi et al. explored the reliability of the Voluntary Response Index and breakpoint angles during the Nordic Hamstring Test using surface Electromyography (sEMG) in professional football players. The goal was to improve motor control and training effectiveness. Breakpoint angles were measured via slow-motion video in addition to the EMG sensor data.
The study involved a total of 24 healthy professional football players, using surface electromyography to assess the index’s magnitude and similarity index. Reliability was measured using the intra-class correlation coefficient, which indicates the consistency of test results under the same conditions.
The findings showed excellent reliability for the index components. The magnitude had an intra-class correlation coefficient of 0.9, indicating almost perfect reliability, while the similarity index had an intra-class correlation coefficient of 0.81, also highly reliable with a low standard error of measurement (0.07). Breakpoint angles showed moderate reliability with an intra-class correlation coefficient of 0.65 and a standard error of measurement of 17.8.
Understanding muscle activation patterns and breakpoint angles helps in designing training programs to prevent injuries, especially hamstring strains. Reliable motor control measures help fine-tune athletic performance by identifying optimal muscle activation levels and angles.
Find out more about this use case in the researchers publication here.
What do biosignals say about your motivation level?
Understanding what drives and sustains motivation during exercise is crucial, especially for endurance activities like jogging. A study from the University of Bremen (Germany) explored the relationship between self-reported motivation drops and changes in physiological signals such as heart rate, muscle activity, and respiration.
The researchers conducted a 20-minute jogging experiment with 11 participants, capturing data through Electrocardiography (ECG), surface Electromyograms (sEMG), and Respiration sensors. Participants self-reported motivation drops by squeezing a small rubber duck, allowing researchers to compare these reports with physiological data.
The findings showed no consistent link between self-reported motivation drops and significant changes in physiological signals For example, while participants often reported shortness of breath and rapid heartbeat, these symptoms did not consistently align with measurable changes in Heart Rate Variability (HRV), muscle activity, or respiration rate. HRV metrics, such as RR-Interval and the LF/HF ratio remained within normal ranges even during reported motivation drops.
The study used advanced methods to analyze the data. The Self-Similarity Matrix (SSM) identified repetitive patterns within the physiological signals, providing a visual representation of sequence similarities. Additionally, Long Short-Term Memory (LSTM) models, a type of neural network designed to recognize and predict temporal dependencies in sequential data, captured trends over time.
This research highlights that while physiological discomfort is commonly reported during decreased motivation, it is not reliably reflected in measurable physiological changes. Therefore, more personalized approaches might be needed to understand and manage motivation during exercise effectively.
Learn more about the research in the researcher’s publications here.
Improving Swimmers Performance with EMG & Dry Exercies
Scapular punches are a common exercise in swimmer’s shoulder preventive programs. Scapular punches involve extending the arms forward while keeping them straight, causing the shoulder blades to move away from the spine. This exercise targets the muscles around the shoulder blade, particularly the serratus anterior, to improve shoulder stability and prevent injuries.
Previous research using Electromyography (EMG) analyses in non-swimmers showed higher mean EMG activity in the serratus anterior (SA), a muscle located on the side of the chest, extending from the upper ribs to the shoulder blade, compared to other shoulder muscles during this exercise.
A study led by the University of Porto (Portugal) aimed to analyze the EMG activity of shoulder muscles during scapular punches in swimmers and compare the results with those of previous studies.
Eight swimmers performed scapular punches with elastic bands and weights in a random order. The mean EMG activity of the back muscles, middle trapezius (MT), lower trapezius (LT), infraspinatus (IS), serratus anterior, and pectoralis major (PM) was measured.
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Results showed that scapular punches with weights produced higher EMG activity in all five muscles tested compared to elastic bands. Specifically, the exercise with an elastic band resulted in higher EMG activity in the MT and SA, while using weights led to higher EMG activity in the IS and SA. Consistent with previous studies, scapular punches significantly activated the SA. However, in swimmers, this activation was not as pronounced or distinct compared to other shoulder muscles.
