Sense of Agency in Brain-Computer Interface-Controlled Lower-Limb Rehabilitation Exoskeletons: Factors and Design Implications

Open Access
Article
Conference Proceedings
Authors: Qingyu ZhaoHaoyu liPei-Luen Patrick Rau
Abstract

Brain-computer interface (BCI)-enhanced lower-limb rehabilitation exoskeletons can translate movement-related brain signals into assisted walking, thereby linking motor intention, robotic assistance, and sensory feedback. Existing evaluations of these systems mainly focus on decoding accuracy, gait control, safety, and clinical rehabilitation outcomes, but these indicators do not fully explain whether patients experience assisted walking as self-initiated and related to their own effort. This paper approaches this issue through the concept of sense of agency and proposes a loop-based analytical framework for BCI-controlled exoskeleton rehabilitation. It suggests that sense of agency depends not only on whether motor intention is accurately decoded, but also on whether the decoded command is triggered within a plausible temporal window, whether system responses remain stable across repeated training, whether robotic assistance preserves the patient’s perceived contribution, and whether sensory and contextual feedback can be meaningfully interpreted. On this basis, the paper argues that assisted walking may feel machine-driven when patients cannot integrate their intention, device response, limb movement, and feedback into a coherent process of self-attribution. Conversely, agency may be better supported when the system makes intention perceptible, assistance attributable, and shared control understandable. This perspective reframes the design significance of low-latency decoding, assist-as-needed control, and multimodal feedback: these features are not only technical or clinical indicators, but also important design conditions for supporting patients’ sense of agency during assisted movement.

Keywords: Brain-computer Interface, Lower-limb Rehabilitation Exoskeleton, Sense Of Agency, Patient Engagement, Assist-as-needed Control, Human Factors

DOI: 10.54941/ahfe1007543

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