Countermovement jump and pull-up performance before and after a swimming race in preparatory and competitive phases of a swimming season

Purpose: Monitoring performance athletes’ training responses can be efficiently completed at competitive events. This study aimed to explore the changes in swimming, countermovement jump (CMJ) and pull-up (PU) performance following training across a competitive phase, as well as immediately before (PRE) and after (POST) each race. Methods: Fourteen well-trained male sprint/middle-distance swimmers (height 179 ± 7 cm; mass 70 ± 8 kg; age: 18 ± 2 years), from 3 regional training groups, completed CMJ and PU tests PRE and POST national competitions in October (PREP phase) and May (COMP), when race performance was also assessed. Results: Swimming race performance was significantly improved from PREP to COMP (1.8 ± 3.2 %, p = 0.044, d = 0.60, moderate effect). Although there were no significant changes in PU velocity, CMJ performance significantly improved from PREP to COMP (Mean difference 2.29 cm, p = 0.004, d = 3.52) and showed PRE to POST race decreases (Mean difference -1.64 cm, p = 0.04, d = 2.28). Conclusion: Swimming performance and CMJ performance improved as the season progressed, although these improvements were not directly correlated. PU performance did not appear to be sensitive to training or race-induced fatigue, in contrast to CMJ, in this group of male swimmers

Efficiency in Kinesiology: Innovative Approaches in Enhancing Motor Skills for Athletic Performance

The inaugural edition of the Special Issue titled “Efficiency in Kinesiology: Innovative approaches in enhancing motor skills for Athletic Performance” has been effectively concluded [...

Crosstalk between Gross and Fine Motor Domains during Late Childhood: The Influence of Gross Motor Training on Fine Motor Performances in Primary School Children

Gross and fine motor competence have a close relationship during development and are shown to correlate to some extent. However, the study of the interaction between these domains still requires further insights. In this study, we investigated the developmental changes in overall motor skills as well as the effects of gross motor training programs on fine motor skills in children (aged 6–11, n = 240). Fine motor skills were assessed before and after gross motor intervention using the Box and Block Test. The gross motor intervention was based on the Test of Gross Motor Development—3rd Edition. Results showed that gross and fine motor skills correlate across all years of primary school, both significantly improving with age. Finally, the gross motor intervention appeared to not influence fine motor skills. Our findings show that during primary school age, overall motor development is continuous, but non-linear. From age nine onward, there seems to be a major step-up in overall motor competence, of which teachers/educators should be aware of in order to design motor educational programs accordingly. While gross and fine motor domains might be functionally integrated to enhance children’s motor performances, further research is needed to clarify the effect of gross motor practice on fine motor performances

Markerless Pose Estimation of DeepLabCut for Shoulder Motion Assessment in Patients with Cervical Spinal Cord Injury

Purpose: Residual motion of upper limbs in individuals with cervical spinal cord injury (CSCI) is a key-element in achieving functional independence and performing activities of daily living. Objective assessment of shoulder joint range of motion (ROM) is crucial to monitor CSCI patients’ progress. Advancements in technological devices allowed to validate wearable Inertial Measurement Unit sensors (IMU) to evaluate shoulder movement. In addition, markerless human motion capture could also be a potential tool for studying body biomechanics. Recently, it was developed a new computer vision technology for markerless pose estimation, named DeepLabCut (DLC), based on transfer learning with deep neural networks. This study evaluated the validity of DeepLabCut contactless method in measuring active shoulder movements in CSCI patients, while seated in a wheelchair, in a clinical setting. To achieve this, we compared the accuracy of the DeepLabCut contactless method to a customized, wireless wearable IMU-based sensors system. Methods: Eight CSCI patients and 8 healthy controls performed four shoulder movements (forward flexion, abduction, external and internal rotation at 90 of shoulder abduction) with dominant upper limb. Every movement was recorded by IMU system and 2 cameras (GoPro Hero 5) placed frontally and laterally to the subject at the same time. Two IMU sensors of the MbientLab (MetaMotion R), characterized by small dimensions and low cost, were positioned on the arm, just above the elbow, and on the wrist, respectively. For each trial, joints center locations were manually applied to 10 images from each video, and were used as training data for the neural network (ResNet-101), which is in line with recommendations when using DLC. After training, all the videos were analyzed by the DLC and the predicted joints center locations during shoulder movements were extracted. Finally, angle measurements of the extracted coordinates of the joints were calculated with Matlab R2019b. Results: DLC reliably tracked and predicted joint center pixel locations from video recordings. Shoulder ROM measurements of DLC correlated well by comparing with IMU sensors system. Conclusion: DeepLabCut, a new technology for markerless pose estimation, can quantify shoulder ROM measurements in CSCI patients and healthy subjects. From a conventional video recording, DLC allows for objective contactless measurements and this open up possibilities to build tele-rehabilitation