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2. Adaptive R-Peak Detection on Wearable ECG Sensors for High-Intensity Exercise

Author

De Giovanni, Elisabetta, Teijeiro, Tomas, Millet, Grégoire P., and Atienza, David

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control, 68U35
Abstract

Objective: Continuous monitoring of biosignals via wearable sensors has quickly expanded in the medical and wellness fields. At rest, automatic detection of vital parameters is generally accurate. However, in conditions such as high-intensity exercise, sudden physiological changes occur to the signals, compromising the robustness of standard algorithms. Methods: Our method, called BayeSlope, is based on unsupervised learning, Bayesian filtering, and non-linear normalization to enhance and correctly detect the R peaks according to their expected positions in the ECG. Furthermore, as BayeSlope is computationally heavy and can drain the device battery quickly, we propose an online design that adapts its robustness to sudden physiological changes, and its complexity to the heterogeneous resources of modern embedded platforms. This method combines BayeSlope with a lightweight algorithm, executed in cores with different capabilities, to reduce the energy consumption while preserving the accuracy. Results: BayeSlope achieves an F1 score of 99.3% in experiments during intense cycling exercise with 20 subjects. Additionally, the online adaptive process achieves an F1 score of 99% across five different exercise intensities, with a total energy consumption of 1.55+-0.54~mJ. Conclusion: We propose a highly accurate and robust method, and a complete energy-efficient implementation in a modern ultra-low-power embedded platform to improve R peak detection in challenging conditions, such as during high-intensity exercise. Significance: The experiments show that BayeSlope outperforms a state-of-the-art algorithm up to 8.4% in F1 score, while our online adaptive method can reach energy savings up to 38.7% on modern heterogeneous wearable platforms., Comment: 12 pages, 14 figures, 2 tables

Published
2021
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17. Fair and Safe Eligibility Criteria for Women's Sport

Author

Tucker, Ross, Hilton, Emma N., McGawley, Kerry, Pollock, Noel, Millet, Gregoire P., Sandbakk, Oyvind, Howatson, Glyn, Brown, Gregory A., Carlson, Lara A., Chen, Mark A., Heron, Neil, Kirk, Christopher, Murphy, Marie H., Pringle, Jamie, Richardson, Andrew, Santos-Concejero, Jordan, Christiansen, Ask Vest, Jones, Carwyn, Alonso, Juan-Manuel, Robinson, Rebecca, Jones, Nigel, Wilson, Mathew, Parker, Michael G., Chintoh, Arabah, Hunter, Sandra, Senefeld, Jonathon W., O'Connor, Mary I., Joyner, Michael, Carneiro, Eva M., Devine, Cathy, Pike, Jon, Lundberg, Tommy R., Tucker, Ross, Hilton, Emma N., McGawley, Kerry, Pollock, Noel, Millet, Gregoire P., Sandbakk, Oyvind, Howatson, Glyn, Brown, Gregory A., Carlson, Lara A., Chen, Mark A., Heron, Neil, Kirk, Christopher, Murphy, Marie H., Pringle, Jamie, Richardson, Andrew, Santos-Concejero, Jordan, Christiansen, Ask Vest, Jones, Carwyn, Alonso, Juan-Manuel, Robinson, Rebecca, Jones, Nigel, Wilson, Mathew, Parker, Michael G., Chintoh, Arabah, Hunter, Sandra, Senefeld, Jonathon W., O'Connor, Mary I., Joyner, Michael, Carneiro, Eva M., Devine, Cathy, Pike, Jon, and Lundberg, Tommy R.

Published
2024
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21. High-Intensity Interval Training, Performance, and Oxygen Uptake Kinetics in Highly Trained Traditional Rowers.

Author

Mujika, Iñigo, Bourdillon, Nicolas, González De Txabarri, Rafa, and Millet, Gregoire P.

Subjects
AEROBIC capacity, ENDURANCE sports training, OXYGEN consumption, DYNAMICS, AQUATIC sports, PRE-tests & post-tests, DESCRIPTIVE statistics, ATHLETIC ability, HIGH-intensity interval training
Abstract

Purpose: Oxygen uptake kinetics (VO2kinetics) is a measure of an athlete's capacity to respond to variations in energy demands. Faster VO2kinetics is associated with better performance in endurance sports, but optimal training methods to improve VO2kinetics remain unclear. This study compared the effects of 2 high-intensity interval-training (HIIT) programs on traditional rowing performance and VO2kinetics. Methods: Twelve highly trained rowers performed one of two 6-week HIIT protocols: either 3-minute repetitions at 90% (HIIT90; n = 5) of peak aerobic power (PAP) or 90-second repetitions at 100% (HIIT100; n = 7) of PAP. Before (PRE) and after (POST) the training intervention, they performed an incremental test to exhaustion to determine the individual lactate threshold, onset of blood lactate accumulation and PAP, and two 6-minute rest-to-exercise transitions to determine VO2kinetics. Results: No significant changes (P >.05) were observed for rowing ergometer power output at individual lactate threshold (HIIT90 PRE 255 [12], POST 264 [13]; HIIT100 247 [24], 266 [28] W), onset of blood lactate accumulation (279 [12], 291 [16]; 269 [23], 284 [32] W), or PAP (359 [13], 381 [15]; 351 [21], 363 [29] W) or for any parameters of VO2kinetics. No differences were observed between HIIT interventions. Conclusion: The HIIT interventions did not induce significant performance or VO2kinetics improvements, although mean power output at individual lactate threshold, onset of blood lactate accumulation, and PAP increased by 5.7%, 5.0%, and 4.5%, respectively. This suggests that the exact intensity and duration of HIIT sessions performed in the same intensity domain may be of lesser importance than other well-established influential factors (eg, training volume progression, training intensity distribution, altitude training) to develop aerobic qualities in endurance athletes. [ABSTRACT FROM AUTHOR]

Published
2023
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27. Adaptive R-Peak Detection on Wearable ECG Sensors for High-Intensity Exercise

Author

De Giovanni, Elisabetta, Teijeiro, Tomas, Millet, Gregoire P., and Atienza, David

Subjects
Signal Processing (eess.SP), FOS: Computer and information sciences, Computer Science - Machine Learning, FOS: Electrical engineering, electronic engineering, information engineering, Biomedical Engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Signal Processing, Electrical Engineering and Systems Science - Systems and Control, 68U35, Machine Learning (cs.LG)
Abstract

Objective: Continuous monitoring of biosignals via wearable sensors has quickly expanded in the medical and wellness fields. At rest, automatic detection of vital parameters is generally accurate. However, in conditions such as high-intensity exercise, sudden physiological changes occur to the signals, compromising the robustness of standard algorithms. Methods: Our method, called BayeSlope, is based on unsupervised learning, Bayesian filtering, and non-linear normalization to enhance and correctly detect the R peaks according to their expected positions in the ECG. Furthermore, as BayeSlope is computationally heavy and can drain the device battery quickly, we propose an online design that adapts its robustness to sudden physiological changes, and its complexity to the heterogeneous resources of modern embedded platforms. This method combines BayeSlope with a lightweight algorithm, executed in cores with different capabilities, to reduce the energy consumption while preserving the accuracy. Results: BayeSlope achieves an F1 score of 99.3% in experiments during intense cycling exercise with 20 subjects. Additionally, the online adaptive process achieves an F1 score of 99% across five different exercise intensities, with a total energy consumption of 1.55+-0.54~mJ. Conclusion: We propose a highly accurate and robust method, and a complete energy-efficient implementation in a modern ultra-low-power embedded platform to improve R peak detection in challenging conditions, such as during high-intensity exercise. Significance: The experiments show that BayeSlope outperforms a state-of-the-art algorithm up to 8.4% in F1 score, while our online adaptive method can reach energy savings up to 38.7% on modern heterogeneous wearable platforms., Comment: 12 pages, 14 figures, 2 tables

Published
2023
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34. The Evolution of World-Class Endurance Training : The Scientist's View on Current and Future Trends

Author

Sandbakk, Øyvind, Pyne, David B., McGawley, Kerry, Foster, Carl, Talsnes, Rune Kjosen, Solli, Guro Strom, Millet, Gregoire P., Seiler, Stephen, Laursen, Paul B., Haugen, Thomas, Tonnessen, Espen, Wilber, Randy, van Erp, Teun, Stellingwerff, Trent, Holmberg, Hans-Christer, Sandbakk, Silvana Bucher, Sandbakk, Øyvind, Pyne, David B., McGawley, Kerry, Foster, Carl, Talsnes, Rune Kjosen, Solli, Guro Strom, Millet, Gregoire P., Seiler, Stephen, Laursen, Paul B., Haugen, Thomas, Tonnessen, Espen, Wilber, Randy, van Erp, Teun, Stellingwerff, Trent, Holmberg, Hans-Christer, and Sandbakk, Silvana Bucher

Abstract

Background: Elite sport is continuously evolving. World records keep falling and athletes from a longer list of countries are involved. Purpose: This commentary was designed to provide insights into present and future trends associated with world-class endurance training based on the perspectives, experience, and knowledge of an expert panel of 25 applied sport scientists. Results: The key drivers of development observed in the past 10-15 years were related to (1) more accessible scientific knowledge for coaches and athletes combined with (2) better integration of practical and scientific exchange across multidisciplinary perspectives within professionalized elite athlete support structures, as well as (3) utilization of new technological advances. Based on these perspectives, we discerned and exemplified the main trends in the practice of endurance sports into the following categories: better understanding of sport-specific demands; improved competition execution; larger, more specific, and more precise training loads; improved training quality; and a more professional and healthier lifestyle. The main areas expected to drive future improvements were associated with more extensive use of advanced technology for monitoring and prescribing training and recovery, more precise use of environmental and nutritional interventions, better understanding of athlete- equipment interactions, and greater emphasis on preventing injuries and illnesses. Conclusions: These expert insights can serve as a platform and inspiration to develop new hypotheses and ideas, encourage future collaboration between researchers and sport practitioners, and, perhaps most important, stimulate curiosity and further collaborative studies about the training, physiology, and performance of endurance athletes.

Published
2023
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35. Editorial: Prevention, assessment and treatment of clinical issues related to endurance exercise and sports

Author

Rojas-Valverde, Daniel; https://orcid.org/0000-0002-0717-8827, Burtscher, Martin; https://orcid.org/0000-0002-5232-3632, Millet, Gregoire P, Scheer, Volker; https://orcid.org/0000-0003-0074-3624, Nokolaidis, Pantelis T, Knechtle, Beat; https://orcid.org/0000-0002-2412-9103, Rojas-Valverde, Daniel; https://orcid.org/0000-0002-0717-8827, Burtscher, Martin; https://orcid.org/0000-0002-5232-3632, Millet, Gregoire P, Scheer, Volker; https://orcid.org/0000-0003-0074-3624, Nokolaidis, Pantelis T, and Knechtle, Beat; https://orcid.org/0000-0002-2412-9103

Published
2023

40. Editorial: Prevention, assessment and treatment of clinical issues related to endurance exercise and sports

Author

Rojas-Valverde, Daniel, Burtscher, Martin, Millet, Gregoire P, Scheer, Volker, Nokolaidis, Pantelis T, Knechtle, Beat, University of Zurich, and Rojas-Valverde, Daniel

Subjects
11035 Institute of General Practice, cycling, 2737 Physiology (medical), Physiology, cardiovascular, Physiology (medical), running, 610 Medicine & health, health, renal, 1314 Physiology, issues. illness
Published
2023
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