Feng Ran

Dr. Feng Ran


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 September 2024 in Journal of Intelligence
Verified
Journal Article
Open access
PDF file
DADongZhen An
DongZhen An
JPJianhua Pan
Jianhua Pan
FRFeng Ran
Feng Ran
DBDonghuan Bai
Donghuan Bai
JZJIA ZHANG
JIA ZHANG
Objective: The aims of this study were to investigate the effects and mechanisms of physical exercise input, sports emotional intelligence, and sports self-efficacy on exercise adherence, and to examine the chain-mediating role of sports emotional intelligence→sports self-efficacy. Methods: The Physical Exercise Input Scale, Exercise Adherence Scale, Sports Emotional Intelligence Scale, and Sports Self-Efficacy Scale were used to investigate 1390 college students in three universities in the Henan Province. Results: (1) Physical exercise input was a significant positive predictor of exercise adherence (β = 0.29, t = 5.78, p < 0.001); (2) sports emotional intelligence and sports self-efficacy mediated the relationship between physical exercise input and exercise adherence; (3) physical exercise input influenced exercise adherence through the separate mediating role of sports emotional intelligence (β = 0.10, t = 5.98, p < 0.001), the separate mediating role of sports self-efficacy (β = 0.13, t = 2.64, p < 0.01), and the chain mediating role of sports emotional intelligence→sports self-efficacy (β = 0.09, t = 2.80, p < 0.01). Conclusions: (1) Physical exercise input can positively predict the level of sports emotional intelligence and sports self-efficacy of college students; (2) Physical exercise input can not only directly influence college students’ exercise adherence but can also indirectly influence it through sports emotional intelligence or sports self-efficacy levels alone, as well as through the chain mediation of the two.

27 February 2025 in Sensors
Verified
Journal Article
Open access
PDF file
YSYao Sun
Yao Sun
YSYingjie Sun
Yingjie Sun
JZJIA ZHANG
JIA ZHANG
FRFeng Ran
Feng Ran
Objective: Mental fatigue (MF) induced by prolonged cognitive tasks poses significant risks to postural stability, yet its effects on multi-sensory integration remain poorly understood. Method: This study investigated how MF alters sensory reweighting and postural control in 27 healthy young males. A 45 min incongruent Stroop task was employed to induce MF, validated via subjective Visual Analog Scale (VAS) scores and psychomotor vigilance tests. Postural stability was assessed under four sensory perturbation conditions (O-H: no interference; C-H: visual occlusion; O-S: proprioceptive perturbation; C-S: combined perturbations) using a Kistler force platform. Center of pressure (COP) signals were analyzed through time-domain metrics, sample entropy (SampEn), and Discrete Wavelet Transform (DWT) to quantify energy distributions across sensory-related frequency bands (visual: 0–0.1 Hz; vestibular: 0.1–0.39 Hz; cerebellar: 0.39–1.56 Hz; proprioceptive: 1.56–6.25 Hz). Results: MF significantly reduced proprioceptive energy contributions (p < 0.05) while increasing vestibular reliance under O-S conditions (p < 0.05). Time-domain metrics showed no significant changes in COP velocity or displacement, but SampEn decreased under closed-eye conditions (p < 0.001), indicating reduced postural adaptability. DWT analysis highlighted MF’s interaction with visual occlusion, altering cerebellar and proprioceptive energy dynamics (p < 0.01). Conclusion: These findings demonstrate that MF disrupts proprioceptive integration, prompting compensatory shifts toward vestibular and cerebellar inputs. The integration of nonlinear entropy and frequency-domain analyses advances methodological frameworks for fatigue research, offering insights into real-time sensor-based fatigue monitoring and balance rehabilitation strategies. This study underscores the hierarchical interplay of sensory systems under cognitive load and provides empirical evidence for optimizing interventions in high-risk occupational and clinical settings.