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. 2024 Jan 30;24(3):909.
doi: 10.3390/s24030909.

Sensor-Based Assessment of Time-of-Day-Dependent Physiological Responses and Physical Performances during a Walking Football Match in Higher-Weight Men

Sami Hidouri  1   2 , Tarak Driss  2 , Sémah Tagougui  3 , Noureddine Kammoun  4 , Hamdi Chtourou  4 , Omar Hammouda  1   2
Affiliations

Sensor-Based Assessment of Time-of-Day-Dependent Physiological Responses and Physical Performances during a Walking Football Match in Higher-Weight Men

Sami Hidouri et al. Sensors (Basel). .

Abstract

Monitoring key physiological metrics, including heart rate and heart rate variability, has been shown to be of value in exercise science, disease management, and overall health. The purpose of this study was to investigate the diurnal variation of physiological responses and physical performances using digital biomarkers as a precise measurement tool during a walking football match (WFM) in higher-weight men. Nineteen males (mean age: 42.53 ± 12.18 years; BMI: 33.31 ± 4.31 kg·m-2) were engaged in a WFM at two different times of the day. Comprehensive evaluations of physiological parameters (e.g., cardiac autonomic function, lactate, glycemia, and oxygen saturation), along with physical performance, were assessed before, during, and after the match. Overall, there was a significant interaction (time of day x WFM) for mean blood pressure (MBP) (p = 0.007) and glycemia (p = 0.039). Glycemia decreased exclusively in the evening after WFM (p = 0.001), while mean blood pressure did not significantly change. Rating of perceived exertion was significantly higher in the evening than in the morning (p = 0.04), while the heart rate recovery after 1 min (HRR60s) of the match was lower in the evening than in the morning (p = 0.048). Overall, walking football practice seems to be safe, whatever the time of day. Furthermore, HRR60, glycemia, and (MBP) values were lower in the evening compared to the morning, suggesting that evening exercise practice could be safer for individuals with higher weight. The utilization of digital biomarkers for monitoring health status during WFM has been shown to be efficient.

Keywords: HRV; circadian rhythms; metabolic health; recreational soccer.

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Conflict of interest statement

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
Flow chart of participants’ recruitment.
Figure 2
Figure 2
Experimental protocol. HRV: heart rate variability; MBP: mean blood pressure; SpO2: oxygen saturation; La: blood lactate; Gl: glycemia; MAT: modified agility T-Test; VJ: vertical jump height; LS: lumbar strength; nbS: number of steps; HR: heart rate; MET: metabolic equivalent of task; HRR60s: heart rate of recovery after 60 s; RPE: rating of perceived exertion; and ↓: measurement.
Figure 3
Figure 3
Group means and standard deviation of physiological parameters. (A): mean HR: mean heart rate; (B): HR max: maximal heart rate; (C): HRR60s: heart rate of recovery after 60 s; (D): MBP: mean blood pressure; (E): lactate; (F): glycemia; (G): MET: metabolic equivalent of task; (H): SpO2: oxygen saturation; *: significantly different at p < 0.05; a: significantly different from before at p < 0.05; black plot: morning and gray plot: evening.
Figure 4
Figure 4
Group means and standard deviation of physical parameters. (A): nbS: number of steps; (B): RPE: rating of perceived exertion; (C): LS: lumber strength; (D): VJ: vertical jump; (E): MAT: modified agility test; a: significantly different from before; *: significantly different at p < 0.05; black plot: morning and gray plot: evening.
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