ArticleDigital health
Advanced biomechanical analytics: Wearable technologies for precision health monitoring in sports performance.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
23 citing papers in PubMed.
- Virtual reality-assisted neuromuscular training effects on agility performance and injury prevention in basketball athletes: a controlled laboratory experiment.Scientific reports · 2026Trial
- The effects of an 8-week functional training program on functional movement and physical fitness in male university students: a randomized controlled trial.Frontiers in public health · 2025Trial
- Artificial Intelligence and Psychophysiological Monitoring for Integrated Performance Modeling in Elite Soccer: A Scoping Review of Applications, Evidence Gaps, and Translational Challenges.Sports (Basel, Switzerland) · 2026Review
- Biomechanical Analysis of the Field Hockey Sweep Skill Using Inertial Measurement Units.Sensors (Basel, Switzerland) · 2026Article
- Intelligence-driven Mechanomedicine for Weight Rebound in Obesity.Current obesity reports · 2026Review
- Emergency Clinical Decision for Sports Injury Management: A Wearable Sensor-Driven Framework from Training to Rehabilitation.Biosensors · 2026Review
- Time-Course of Knee Muscle Strength Recovery at 3, 6, and 12 Months Postoperatively After Open Wedge High Tibial Osteotomy: Differential Recovery Patterns of Maximal Power and Muscle Endurance.Journal of clinical medicine · 2026Article
- Wearable Biosensing and Machine Learning for Data-Driven Training and Coaching Support.Biosensors · 2026Review
- Bioinformatics-Inspired IMU Stride Sequence Modeling for Fatigue Detection Using Spectral-Entropy Features and Hybrid AI in Performance Sports.Sensors (Basel, Switzerland) · 2026Article
- A Protocol for the Biomechanical Evaluation of the Types of Setting Motions in Volleyball Based on Kinematics and Muscle Synergies.Methods and protocols · 2026Article
- Aristotle's arm-swing hypothesis: biomechanical evidence from forward and inverse dynamics in an Olympic sprinter.Frontiers in sports and active living · 2026Article
- Generative artificial intelligence and large language models in sports medicine: a scoping review of applications, accuracy, and ethical implications.Frontiers in public health · 2026Article
- Artificial Intelligence in Sports Biomechanics: A Scoping Review on Wearable Technology, Motion Analysis, and Injury Prevention.Bioengineering (Basel, Switzerland) · 2025Review
- Advancements in Wearable and Implantable BioMEMS Devices: Transforming Healthcare Through Technology.Micromachines · 2025Review
- Challenges in Combining EMG, Joint Moments, and GRF from Marker-Less Video-Based Motion Capture Systems.Bioengineering (Basel, Switzerland) · 2025Review
- Artificial Intelligence for Objective Assessment of Acrobatic Movements: Applying Machine Learning for Identifying Tumbling Elements in Cheer Sports.Sensors (Basel, Switzerland) · 2025Article
- Neurosciences and Sports Rehabilitation in ACLR: A Narrative Review on Winning Alliance Strategies and Connecting the Dots.Journal of functional morphology and kinesiology · 2025Review
- Special Issue "Biomechanical Analysis in Physical Activity and Sports".Journal of functional morphology and kinesiology · 2025Article
- RETRACTED: Optimizing the impact of time domain segmentation techniques on upper limb EMG decoding using multimodal features.PloS one · 2025Article
- Precision nutrition in sports science: an opinion on omics-based personalization and athletic outcomes.Frontiers in nutrition · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study investigated the impact of wearable technologies, particularly advanced biomechanical analytics and machine learning, on sports performance monitoring and intervention strategies within the realm of physiotherapy. The primary aims were to evaluate key performance metrics, individual athlete variations and the efficacy of machine learning-driven adaptive interventions. Methods: The research employed an observational cross-sectional design, focusing on the collection and analysis of real-world biomechanical data from athletes engaged in sports physiotherapy. A representative sample of athletes from Bahawalpur participated, utilizing Dring Stadium as the primary data collection venue. Wearable devices, including inertial sensors (MPU6050, MPU9250), electromyography (EMG) sensors (MyoWare Muscle Sensor), pressure sensors (FlexiForce sensor) and haptic feedback sensors, were strategically chosen for their ability to capture diverse biomechanical parameters. Results: Key performance metrics, such as heart rate (mean: 76.5 bpm, SD: 3.2, min: 72, max: 80), joint angles (mean: 112.3 degrees, SD: 6.8, min: 105, max: 120), muscle activation (mean: 43.2%, SD: 4.5, min: 38, max: 48) and stress and strain features (mean: [112.3 ], SD: [6.5 ]), were analyzed and presented in summary tables. Individual athlete analyses highlighted variations in performance metrics, emphasizing the need for personalized monitoring and intervention strategies. The impact of wearable technologies on athletic performance was quantified through a comparison of metrics recorded with and without sensors. Results consistently demonstrated improvements in monitored parameters, affirming the significance of wearable technologies. Conclusions: The study suggests that wearable technologies, when combined with advanced biomechanical analytics and machine learning, can enhance athletic performance in sports physiotherapy. Real-time monitoring allows for precise intervention adjustments, demonstrating the potential of machine learning-driven adaptive interventions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.