FAQ

Kineura’s wearable EMG (electromyography) device is a compact and comfortable sensor system designed to monitor and analyze muscle activity in real time. It helps athletes, trainers, and sports professionals better understand muscle engagement, effort, and fatigue during training or competition.

Our technology is suitable for athletes across all levels, fitness enthusiasts, physical therapists, sports coaches, and researchers interested in movement science and muscle performance optimization.

Kineura’s EMG sensors detect and record the electrical signals generated by muscle fibers during contraction. Data is transmitted wirelessly to our companion app or platform, where users can view real-time muscle activity, performance metrics, and personalized insights.

Kineura focuses on delivering actionable, easy-to-understand insights with a user-friendly interface. Our technology emphasizes sports performance, reliability, and ease of integration into existing training routines.

At Kineura, we use advanced dry-electromyography (D-EMG) sensors seamlessly integrated with comfortable and durable compression sleeves. D-EMG has been proven to be 99.5% accurate relative to needle EMG, the medical diagnostic standard. In the same study, surface-EMG, the standard for physiological muscular analysis, was only 98.7% as accurate. Combined with proprietary data processing and machine learning algorithms, Kineura is able to put medical-grade analysis and insights into the hands of every athlete-- no doctors or PT's required.

**Kineura EMG wearables are designed solely for sports performance monitoring and athletic training purposes. They are not intended for medical diagnostics, treatment, or any clinical use. The data provided by Kineura devices should not be used to diagnose, treat, or prevent any medical condition. Always consult a qualified healthcare professional for any medical concerns or health-related decisions.**

As an early access user, you’ll receive priority support, onboarding assistance, and regular software updates. Our team welcomes feedback and offers personalized help for setup, troubleshooting, and feature requests.

Kineura technology is all supported by peer-reviewed literature. We always encourage users to take control! Find a list of relevant papers below: 1. Application of Surface Electromyography in Exercise Fatigue Sun J, Liu G, Sun Y, Lin K, Zhou Z, Cai J. Front Syst Neurosci. 2022;16:893275. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC9406287/ PMCID: PMC9406287

2. The Use of Electromyography (EMG) in Sports Applications Cometa Systems. (2024). Available at: https://www.cometasystems.com/the-use-of-electromyography-emg-in-sports-applications/ [Industry summary, useful for practical insights]

3. The Practical Use of Surface Electromyography During Running: Does the Evidence Support the Hype? Subbu R, Weiler R, Whyte G. BMJ Open Sport Exerc Med. 2015;1:e000026. Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC5117013/ PMCID: PMC5117013

4. Sport Biomechanics Applications Using Inertial, Force, and EMG Wearable Sensors: A Literature Overview Taborri J, Keogh J, Kos A, Santuz A, Umek A, Urbanczyk C, van der Kruk E, Rossi S. Sensors (Basel). 2020 Jun 23;20(12):3607. Available at: https://pubmed.ncbi.nlm.nih.gov/32676126/ PMID: 32676126

5. Electromyography and the Study of Sports Movements: A Review De Luca CJ. Med Sci Sports Exerc. 1994;26(5):652-660. Available at: https://pubmed.ncbi.nlm.nih.gov/8301704/ PMID: 8301704

6. Advanced Biomechanical Analytics: Wearable Technologies for Sports Performance Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC11151756/ [2024, explores integration of EMG and AI in athletic monitoring]

7. Sensor-Enhanced Wearables and Automated Analytics for Injury Prediction in Athletics Available at: https://www.sciencedirect.com/science/article/pii/S2665917424000308 [2024, demonstrates AI-based injury prediction from wearable sensor datasets]

8. Wearable Sensors for Monitoring the Internal and External Workload of Athletes Peake JM, Kerr G, Sullivan JP. NPJ Digital Medicine. 2019 Jul 29;2:13. Available at: https://www.nature.com/articles/s41746-019-0149-2