nikhil-garg/EMG_exp

The project is a 5-year-old research artifact accompanying a specific academic paper. With only 13 stars and 3 forks over half a decade, it lacks any meaningful community adoption or development velocity. While the combination of EMG signal processing and neuromorphic 'regulated reservoir computing' was novel in a research context, the code serves as a static reference rather than a living tool. From a competitive standpoint, this is highly vulnerable to displacement by modern spiking neural network (SNN) frameworks like SpikingJelly or Tonic, and the hardware landscape has shifted significantly since its release. In the commercial sector, companies like Meta (via CTRL-Labs) have moved far beyond these basic reservoir implementations for EMG-based gesture control. The defensibility is near zero as it is a pure algorithmic implementation with no data moat or ecosystem lock-in. Frontier labs are unlikely to target this specific niche (EMG + SNN), but larger platforms focusing on AR/VR/Wearables (Apple, Meta) represent a categorical threat to the relevance of this specific approach.