Article

Lightweight Reinforcement Algorithms for autonomous, scalable intra-cortical Brain Machine Interfaces

2020-12-09

Abstract excerpt

Intra-cortical Brain Machine Interfaces (iBMIs) with wireless capability could scale the number of recording channels by integrating an intention decoder to reduce data rates. However, the need for frequent retraining due to neural signal non-stationarity is a big impediment. This paper presents an alternate paradigm of online reinforcement learning (RL) with a binary evaluative feedback in iBMIs to tackle this is...

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Literature Corpus work: e6a47428-7cba-534d-bd7e-c60a066156df
DOI: 10.1101/2020.12.08.416131

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