Background: Evidence exists for the effectiveness of functional electrical stimulation (FES) and robots in stroke rehabilitation. This study examined i) the feasibility of using Stimulation Assistance through Iterative Learning (SAIL), a novel system combining FES and robots for chronic stroke upper limb rehabilitation and ii) participants’ perspectives of the system. Method: Five chronic stroke participants, three men and two women aged between 33 and 67 years, with reduced upper limb function were recruited to this study via stroke clubs and a volunteer database. Participants undertook 18, 1 hour training sessions involving 3D tracking tasks in which they moved their impaired arm, supported by a robot, to follow a slowly moving sphere along a specified trajectory. FES precisely controlled by advanced iterative learning control (ILC) algorithms, was applied to the triceps and anterior deltoid muscles. Participants also completed unassisted tracking tasks in each session, and the Action Research Arm Test (ARAT) and Fugl-Meyer Assessment (F-M) pre- and post-intervention. Participant perspectives were explored during a semi-structured interview post-intervention. Analysis of data was conducted using: linear regression for changes in assisted and unassisted tracking; a signed Wilcoxon sum-rank test for F-M and ARAT; and content analysis for the semi-structured interviews. Results: From pre- to post-intervention a significant improvement in the F-M (mean 23.5 (SD 12.95) to 32.8 (SD 12.28), z(5) = -2.02, p = .04), an improvement in unassisted tracking performance, and a reduction in the amount of ES required for accurate assisted tracking were demonstrated. No changes were found for the ARAT. Participants responded positively to the system and identified ways to achieve more effective, functional improvements. Conclusion: The feasibility of SAIL in reducing upper limb impairments following stroke was demonstrated. Participants’ perspectives highlighted key issues to be considered by researchers developing new rehabilitation technologies, indicating the value of user involvement.