Myontec produces smart garments with textile‑integrated high‑density EMG sensors that record full‑body muscle activity and transmit encrypted data via Bluetooth Low Energy to a cloud‑based analytics platform. The platform applies adaptive filtering and machine‑learning models to generate activation, timing, and fatigue metrics, which are delivered through a web dashboard, REST API, and SDKs for use in sports performance, rehabilitation, ergonomics, and research.
Funding
Funding not disclosed
Founders
Product
Problem
Athletes, clinicians, and researchers often rely on conventional surface EMG setups that are cumbersome, require extensive skin preparation, and provide limited spatial coverage, making continuous muscle monitoring impractical for training, rehabilitation, and ergonomic assessments.
Solution
Myontec delivers intelligent clothing that embeds high‑density EMG sensors directly into textile fibers, enabling unobtrusive, real‑time capture of muscle activation patterns across the full body. The garment wirelessly streams raw EMG signals to a cloud‑based analytics platform where proprietary signal‑processing algorithms extract metrics such as activation timing, intensity, and fatigue indices. Users access these insights through a web dashboard or API, allowing immediate feedback for strength‑training optimization, injury‑prevention protocols, and scientific studies. The system is designed for rapid donning, minimal calibration, and compliance with data‑privacy standards, turning raw electrophysiological data into actionable performance intelligence without the need for specialist technicians.
Target Audience
Primary customers include sports performance teams and strength‑conditioning coaches, physical therapy and rehabilitation clinics, ergonomics consultants, and academic research labs studying musculoskeletal function.
Features
- Textile‑integrated, high‑resolution EMG sensor matrix covering major muscle groups with < 10 µV noise floor
- Bluetooth Low Energy (BLE) module for low‑latency, encrypted data transmission to mobile or desktop clients
- Cloud analytics pipeline applying adaptive filtering, wavelet decomposition, and machine‑learning models to generate activation, co‑contraction, and fatigue scores
- RESTful API and SDKs (Python, C++) for seamless integration with training software, electronic health record (EHR) systems, and research data pipelines
- Auto‑calibration routine that compensates for garment fit and skin impedance, reducing setup time to under 2 minutes
- Battery pack delivering up to 12 hours of continuous monitoring, with hot‑swap capability for extended sessions
- GDPR‑compliant data storage with role‑based access controls and audit logging