Riccardo Padovan

@riccardopadovan
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6 Posts
📊 Neuromuscular & muscle science
HD-sEMG • resistance training
Visiting Researcher @ Ritsumeikan University
Research Associate @ AUT SPRINZ
PhD(c) Exercise & Sport Sciences

Honoured to present at SISMES 2025 the results of our research conducted at AUT SPRINZ (New Zealand), supervised by Dr Eric Helms.

The study explored high-density surface electromyography (HD-sEMG) applications in resistance training, contributing to a deeper understanding of neuromuscular excitation patterns.

Great discussions, valuable feedback, and a reminder of why I love doing research.

#ScienceInAction #SportsScience #EMG #PhDlife #AUTSPRINZ #SISMES2025 #ExerciseScience

Excited to announce that I’ve started a new role as Research Associate at the Sport Performance Research Institute New Zealand (SPRINZ), AUT.

My work will continue to focus on resistance training, neuromuscular adaptations, and advanced methodologies such as high-density surface EMG (HD-sEMG), in collaboration with an incredible team of researchers and practitioners.

Looking forward to sharing science and connecting here! 🌏

#SportScience #OpenScience #ExerciseScience

Thrilled to share that my abstract “Effects of Grip Variation on Muscle Excitation and Spatial Activation Patterns During the Lat Pull-Down: A Preliminary HD-sEMG Study” was accepted as an Oral Communication at SISMeS 2025 🎉
#HDsEMG #Electromyography #ResistanceTraining #LatPullDown #SportsScience #SISMeS2025

Grateful to be listed among the Top 100 most-read authors last month in Sport Sciences for Health.

As an early-career researcher, this recognition motivates me even more—still so much to learn and contribute.

#SportScience #Research #PhDlife

Just completed Improving Your Statistical Inferences 🎓

Thanks to @lakens for making such a high‑quality, free course on stats, reproducibility & #OpenScience.
Strongly recommend to all PhD, Master’s & undergrad students!

https://www.coursera.org/account/accomplishments/verify/YZKI0HDUH3TV?utm_product=course

Completion Certificate for Improving your statistical inferences

This certificate verifies my successful completion of Eindhoven University of Technology's "Improving your statistical inferences" on Coursera

Coursera

Replicability in sport & exercise science (Murphy et al., 2025):
âś… 28% replicated robustly
📉 Effect sizes ↓ sharply when replicated
⚠️ Barriers: poor data/reporting transparency

Our field might definitely benefit from embracing #OpenScience.

https://link.springer.com/article/10.1007/s40279-025-02201-w

Estimating the Replicability of Sports and Exercise Science Research - Sports Medicine

Background The replicability of sports and exercise research has not been assessed previously despite concerns about scientific practices within the field. Aim This study aims to provide an initial estimate of the replicability of applied sports and exercise science research published in quartile 1 journals (SCImago journal ranking for 2019 in the Sports Science subject category; www.scimagojr.com ) between 2016 and 2021. Methods A formalised selection protocol for this replication project was previously published. Voluntary collaborators were recruited, and studies were allocated in a stratified and randomised manner on the basis of equipment and expertise. Original authors were contacted to provide deidentified raw data, to review preregistrations and to provide methodological clarifications. A multiple inferential strategy was employed to analyse the replication data. The same analysis (i.e. F test or t test) was used to determine whether the replication effect size was statistically significant and in the same direction as the original effect size. Z-tests were used to determine whether the original and replication effect size estimates were compatible or significantly different in magnitude. Results In total, 25 replication studies were included for analysis. Of the 25, 10 replications used paired t tests, 1 used an independent t test and 14 used an analysis of variance (ANOVA) for the statistical analyses. In all, 7 (28%) studies demonstrated robust replicability, meeting all three validation criteria: achieving statistical significance (p < 0.05) in the same direction as the original study and showing compatible effect size magnitudes as per the Z test (p > 0.05). Conclusion There was a substantial decrease in the published effect size estimate magnitudes when replicated; therefore, sports and exercise science researchers should consider effect size uncertainty when conducting subsequent power analyses. Additionally, there were many barriers to conducting the replication studies, e.g., original author communication and poor data and reporting transparency.

SpringerLink