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  1. 1

    Validity and reliability of an on-bike sensor system for the determination of aerodynamic drag in cycling

    Hopker, J. G., Barnes, C., Fennell, C. R. J., Gibson, S.
    Published in European Journal of Sport Science (2025)
    Subjects: “…Sensor…”
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  2. 2

    Study of the local oxygen saturation in cycling and differences between sexes

    Sendra-Pérez, C.
    Published 2025
    “…The most relevant conclusions of this thesis document were that portable muscle oxygenation sensors demonstrated moderate to good reliability in determining the second threshold. …”
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  3. 3

    Asymmetric spread analysis of heart rate variability in XC mountain biking during a 20-minute autonomic profile test

    Tafur-Tascón, L. J., Martínez-Patiño, M. J., Mina-Paz, Y.
    Published in Sensors (2025)
    “…Sensors…”
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  4. 4

    Validity of the Quarq cycling power meter

    Oteo-Gorostidi, J., Camara, J., Ojanguren-Rodríguez, D., Iriberri, J., Vadillo-Ventura, I., Montalvo-Pérez, A.
    Published in Sensors (2025)
    “…Sensors…”
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  5. 5

    Breath-by-breath measurement of respiratory frequency and tidal volume with a multiple-camera motion capture system during cycling incremental exercise

    Massaroni, C., Nicolò, A., Lopes, A.L.d.C., Romano, C., Pinnelli, M., Sarro, K., Schena, E., Cerveri, P., Sacchetti, M., Silvestri, S., Silvatti, A. P.
    Published in Sensors (2025)
    “…Sensors…”
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  6. 6

    The type of sport, but not sex, impacts body composition and metabolic response to a complete weight loss-weight regain episode in weight cycling athletes: results from the WAVE st...

    Bagot S., Ramos I., Miles-Chan J., Dulloo A., Hackney A. C., Boirie Y., Duclos M., Thivel D., Isacco L. “…Body composition (dual-energy X-ray absorptiometry), core body temperature (telemetric temperature sensor), energy expenditure and substrate oxidation at rest and during moderate exercise (indirect calorimetry), and energy intake (48 h food record) were assessed. …”
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  7. 7

    Validity and Reliability of an on-bike sensor system for the determination of aerodynamic drag in cycling

    Hopker, J., Barnes, C., Fennell, C., Gibson, S.
    Published in SportRxiv Preprints (2024)
    Subjects: “…Sensor…”
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  8. 8

    Assessing ambient temperature measurements in road cycling races

    Pinedo-Jauregi, A., Romarate, A. Subjects: “…Sensor…”
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  9. 9

    Continuous glucose monitoring in para cyclists: An observational study

    Weijer, V., van der Werf, R., van der Haijden, M., Jeukendrup, A., van Loon, L. J. C., van Dijk, J. W.
    Published in European Journal of Sport Science (2024)
    “…Furthermore, CGM accuracy is compromised during exercise, especially if the sensor is in proximity to highly active muscles.…”
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  10. 10

    Assessing energy availability and glucose dynamics in adolescent cyclists: Implications for nutritional interventions during the competitive season

    Tarocchi, M., Pellegrino, A., Skroce, K., Zignoli, A., Cavadini, L. C., Bodini, C., Pagliai, G., Toncelli, L., Stefani, L., Vanni, S., Boddi, M., Modesti, A., Modesti, P. A.
    Published in Nutrients (2024)
    “…Their real-time power output, interstitial glucose, and temperature were recorded via sensors and a bike computer. Their energy intake (EI) was estimated from daily, self-reported food diaries. …”
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  11. 11

    Validity and reliability of movesense hr+ ecg measurements for high-intensity running and cycling

    Martín Gómez, R., Allevard, E., Kamstra, H., Cotter, J., Lamb, P.
    Published in Sensors (2024)
    “…Sensors…”
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  12. 12

    Validity of current smartwatches for triathlon training: How accurate are heart rate, distance, and swimming readings?

    Jacko, T., Bartsch, J., von Diecken, C., Ueberschär, O.
    Published in Sensors (2024)
    Subjects: “…Sensor…”
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  13. 13

    Sensitivity analysis of bicycle characteristics for pavement roughness monitoring by vibration data

    Ghaderi, O., Cafiso, S., Caponnetto, R., Pappalardo, G.
    Published in Journal of Science and Cycling (2024)
    “…The focus of this paper is to investigate how the physical characteristics of bicycles affect the vibration response under different pavement conditions, and to explore the potential of crowdsourced collection with sensor-equipped bicycles to collect data for road condition and comfort assessment of micro-mobility users. …”
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  14. 14

    The effect of low-intensity exercise duration on acute skeletal muscle signalling responses

    Harrison, P., Dugdale, H., Hulston, C., Martin, N., Bailey, S., Bishop, D., Ferguson, R.
    Published in Journal of Science and Cycling (2024)
    “…Mitochondrial biogenesis is initiated by homeostatic perturbations within skeletal muscle which activate sensor proteins, including AMPK, CaMKII, and p38 MAPK. …”
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  15. 15

    Artificial intelligence in cycling - Live positional tracking using on-bike aerodynamic sensors

    Barnes, C., Hopker, J., Gibson, S.
    Published in Journal of Science and Cycling (2024)
    Subjects: “…Sensor…”
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  16. 16

    Validity of a commercial wearable sensor measuring respiratory frequency in cycling

    Greco, G., Innocenti, L., Massaroni, C., Nicolò, A.
    Published in Journal of Science and Cycling (2024)
    Subjects: “…Sensor…”
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  17. 17

    Estimation of LT with dynamic transfer function models with commercial HR and power sensor data

    Stessens, L., Gouwy, R., Gielen, J., Aerts, J.-M.
    Published in Journal of Science and Cycling (2024)
    Subjects: “…Sensor…”
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  18. 18

    Multi-sensor based analysis of the changeovers in team pursuit

    Decorte, R., Verstockt, S., Slembrouck, M.
    Published in Journal of Science and Cycling (2024)
    Subjects: “…Sensor…”
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  19. 19

    Estimation of heart rate recovery from field rides

    Published in Journal of Science and Cycling (2024)
    “…In this work, we propose ways to estimate HRR from data collected with power meters and heart rate sensors during field rides. This allows for continuous and automatic tracking of HRR without the burden of regular lab tests. …”
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  20. 20

    Physical performance estimation in practice: A systematic review of advancements in performance prediction and modeling in cycling

    Stessens, L., Gielen, J., Meeusen, R., Aerts, J.-M. “…Wearable technology, such as physiological and biomechanical sensors, can be integrated with mathematical models to enhance the practicality of performance monitoring and enable real-time feedback and personalized training recommendations. …”
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