Excerpt:
Combining EMG input and multi-sensor fusion to achieve stable, low-latency prosthetic motion.
Content:
The Challenge of Natural Motion
Human movement is dynamic and context-dependent.
Muscle signals vary with fatigue, electrode placement, and environmental conditions.
To achieve intuitive prosthetic control, systems must adapt continuously.
EMG as the Primary Interface
EMG provides a direct interface between muscle intention and mechanical execution.
However, raw EMG signals require:
- Noise reduction
- Signal normalization
- Pattern classification
- Continuous recalibration
Without adaptation, performance degrades over time.
Sensor Fusion for Stability
To improve reliability, we integrate additional inputs such as:
- Position sensors
- Force feedback modules
- Motion tracking data
Sensor fusion allows the system to cross-validate signals and maintain consistent behavior.
Real-Time Adaptation
Our adaptive algorithms update internal parameters dynamically based on signal behavior.
This ensures:
- Reduced latency
- Smoother motion transitions
- Improved user confidence
- Long-term performance stability
Toward Intuitive Control
Adaptive prosthetic systems must evolve with the user.
By combining EMG interpretation with sensor fusion and embedded intelligence, we create responsive and scalable control platforms.