Gait is a behavioral biometric trait that enables non-invasive person recognition based on individual walking patterns. Camera-based gait acquisition is convenient, but silhouette sequences often contain substantial motion-irrelevant appearance information, such as body shape, clothing, and carried objects. To address this problem, a multi-scale time series differencer is proposed to acquire tensor difference data between adjacent frames, so as to extract dynamic feature information in motion gait image sequences. Experiments on the CASIA-B dataset show that the proposed method achieves Rank-1 accuracies of 97.7%, 94.6%, and 80.0% under NM, BG, and CL conditions, respectively. Ablation results further demonstrate that MTDU improves the mean accuracy from 84.7% to 90.8% compared with single-scale temporal differencing. The multi-scale time series differencer shows potential for fields including sports motion gait detection and recognition, surveillance security motion gait identity authentication, and medical motion gait recovery assessment for sports injuries, demonstrating practical application value.

Postural control in curling is expressed during a dynamic, sport-specific delivery on a single sliding leg, yet it is still assessed almost exclusively with static single-leg force-plate protocols that poorly reflect on-ice demands. This study developed and validated a wearable multi-sensor system that fuses trunk and pelvis inertial measurement units (IMUs), instrumented plantar-pressure insoles and core-muscle surface electromyography (sEMG) to quantify dynamic postural stability during the simulated curling delivery in 110 young adult curlers (age range 18–24 years). A four-phase segmentation of the delivery was implemented, and a compact 28-feature set was extracted and combined through a complementary Kalman fusion scheme into a single Dynamic Stability Index (DSI). Validated against a reference force plate during static single-leg standing, the IMU-derived sway path showed a small bias (~0.4 cm) with 95% limits of agreement of approximately +4.4 to −3.6 cm, and between-day reliability of the fused DSI was excellent (ICC(3,1) = 0.90, 95% CI [0.82, 0.95]). A random-forest classifier discriminated high- from low-stability deliveries with 91.8% accuracy (95% CI [87.2%, 95.1%]; AUC = 0.92, 95% CI [0.87, 0.96]), outperforming any single-sensor or static force-plate baseline. Sensor-derived dynamic metrics correlated with external-oblique strength, trunk proprioceptive error and motor self-efficacy (Spearman ρ ranging from −0.55 to 0.51, all p < 0.001 after Holm–Bonferroni correction), and dynamic instability increased monotonically across descending self-efficacy tertiles. The proposed system provides a portable, context-relevant and interpretable tool for balance profiling in young curlers, and demonstrates that multi-sensor fusion substantially improves measurement fidelity over conventional single-modality assessment.

Digital transformation is reshaping resource linkages, service organization, and consumption scenarios among culture, sports, and tourism. Based on a balanced panel dataset of 30 Chinese provincial administrative regions from 2015 to 2024, this study constructs a culture–sports–tourism industry integration coordination index (CSTI) and a digital economy index (DE), and employs two-way fixed effects, a spatial Durbin model, a panel threshold model, and a quadratic specification to examine the average association, spatial spillover, threshold conditions, and regional heterogeneity of the relationship. The results show that (1) the digital economy has a significant positive association with CSTI, mainly operating through the comprehensive development component rather than the coupling component; (2) stable cross-regional spatial spillovers are not identified, indicating that digital connectivity does not automatically translate into regional coordination; (3) a threshold exists for economic development, but the marginal association weakens beyond the threshold rather than strengthening, and the human capital threshold is only marginally significant; (4) the central and western regions exhibit stronger DE coefficients, while higher initial digital infrastructure weakens the marginal effect; and (5) a significant concave relationship between DE and CSTI is found, but a strict inverted-U shape is not supported. These findings suggest that digital economy-enabled culture–sports–tourism integration is a locally embedded, conditionally dependent transformation process rather than a uniform, self-propagating linear growth path.