Towards The Development of a Low-Latency, Biosignal-Controlled Human-Machine Interaction System

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In this paper, we report the development of a system pipeline, and both physical and bioelectrical sensors as input modalities to demonstrate a near-natural motion synchronization between a human and a robotic arm. This effort was exemplified by the formulation of a method to reduce modular and system-level operational latency to achieve congruent human-machine interaction (HMI) through analyzing and simulating common mechanical motions. Furthermore, we explored several efficient machine learning (ML) model that reliably works with a variety of time-series-based biosignals reflective of intents, thus allowing a diversity of sensors to contribute as the system inputs. We believe our system pipeline represents a first step in unveiling otherwise hidden components within Biosignal-Controlled HMI systems and meeting the key challenges will bring us closer to the establishment of a natural, human-intent controlled, remotely operated HMI platform, with applications that extend far beyond major sectors of academia and industry.

Recommended citation: K. Bimbraw and M. Zheng (2023), “Towards The Development of a Low-Latency, Biosignal-Controlled Human-Machine Interaction System”, 2023 IEEE/SICE International Symposium on System Integration (SII), Atlanta, GA, USA, 2023, pp. 1-7, doi: 10.1109/SII55687.2023.10039467.