Assessing the Impact of Neuromuscular Electrical Stimulation-Based Fingerboard Training versus Conventional Fingerboard Training on Finger Flexor Endurance in Intermediate to Advanced Sports Climbers: A Randomized Controlled Study.

Competitive climbers engage in highly structured training regimens to achieve peak performance levels, with efficient time management as a critical aspect. Neuromuscular electrical stimulation (NMES) training can close the gap between time-efficient conditioning training and achieving optimal prerequisites for peak climbing-specific performances. Therefore, we examined potential neuromuscular adaptations resulting from the NMFES intervention by analyzing the efficacy of twice-weekly NMES-supported fingerboard (hang board) training compared with thrice-weekly conventional fingerboard training over 7 training weeks in enhancing climbing-specific endurance among intermediate to advanced climbers.

Impact of Fatigue on Ergonomic Risk Scores and Foot Kinetics: A Field Study Employing Inertial and In-Shoe Plantar Pressure Measurement Devices.

(1) Background: Occupational fatigue is a primary factor leading to work-related musculoskeletal disorders (WRMSDs). Kinematic and kinetic experimental studies have been able to identify indicators of WRMSD, but research addressing real-world workplace scenarios is lacking. Hence, the authors of this study aimed to assess the influence of physical strain on the Borg CR-10 body map, ergonomic risk scores, and foot pressure in a real-world setting.

In Vivo Monitoring of Acute and Intermittent Fatigue in Sport Climbing Using Near-Infrared Spectroscopy Wearable Biosensors.

The objectification of acute fatigue (during isometric muscle contraction) and cumulative fatigue (due to multiple intermittent isometric muscle contractions) plays an important role in sport climbing. The data of 42 participants were used in the study. Climbing performance was operationalized using maximal climbing-specific holding time (CSHT) by performing dead hangs.

Conceptual Structure and Current Trends in Artificial Intelligence, Machine Learning, and Deep Learning Research in Sports: A Bibliometric Review.

Artificial intelligence and its subcategories of machine learning and deep learning are gaining increasing importance and attention in the context of sports research. This has also meant that the number of corresponding publications has become complex and unmanageably large in human terms. In the current state of the research field, there is a lack of bibliometric analysis, which would prove useful for obtaining insights into the large amounts of available literature.

Evaluation of Influencing Factors on the Maximum Climbing Specific Holding Time: An Inferential Statistics and Machine Learning Approach.

Handgrip strength (HGS) appears to be an indicator of climbing performance. The transferability of HGS measurements obtained using a hand dynamometer and factors that influence the maximal climbing-specific holding time (CSHT) are largely unclear. Forty-eight healthy subjects (27 female, 21 male; age: 22.

Effects of Unilateral Muscle Fatigue on Thermographic Skin Surface Temperature of Back and Abdominal Muscles-A Pilot Study.

The present study aimed to assess the effects of asymmetric muscle fatigue on the skin surface temperature of abdominal and back muscles. The study was based on a pre-post/follow-up design with one group and included a total of 41 subjects (22 male, 19 female; age, 22.63 ± 3.

Classification and Automated Interpretation of Spinal Posture Data Using a Pathology-Independent Classifier and Explainable Artificial Intelligence (XAI).

Clinical classification models are mostly pathology-dependent and, thus, are only able to detect pathologies they have been trained for. Research is needed regarding pathology-independent classifiers and their interpretation. Hence, our aim is to develop a pathology-independent classifier that provides prediction probabilities and explanations of the classification decisions.