Hybrid Cooperative Control of Functional Electrical Stimulation and Robot Assistance for Upper Extremity Rehabilitation
Open accessAbstract
OBJECTIVE: Hybrid systems that integrate Functional Electrical Stimulation (FES) and robotic assistance have been proposed in neurorehabilitation to enhance therapeutic benefits. This study focuses on designing a cooperative controller capable of distributing the required torque for movement between robotic actuation and FES, thereby eliminating the need for time-consuming calibration procedures. METHODS: The control schema comprises three main blocks: a motion generation block that defines the desired trajectory, a motor control block including both a weight compensation feedforward and a feedback impedance controller, and an FES control block, based on trial-by-trial Iterative Learning Control (ILC), that adjusts the stimulation intensity according to a predefined stimulation waveform. The feedforward motor assistance can be dynamically regulated using an allocation factor. Experiments involving 12 healthy volunteers were conducted using a one-degree-of-freedom elbow testbed. RESULTS: The experimental results showcased the successful integration of Functional Electrical Stimulation (FES) with robotic actuation, ensuring precise trajectory tracking with a Root Mean Square Error (RMSE) below 7°. Notably, allocating more torque to FES led to a 51 % reduction in motor torque. In conditions where FES operated alone, there was poorer tracking performance with an RMSE of 24° and an early onset of muscle fatigue, as evidenced by a reduced number of achieved repetitions. Furthermore, the hybrid approach enabled 100 fatigue-free elbow flexion repetitions, underscoring the effectiveness of cooperative FES-motor control in extending the benefits of FES-induced exercises. SIGNIFICANCE: This study proposes a flexible approach which can be extended to a multi-degree-of-freedom hybrid system. Furthermore, it underscores the significance of employing a straightforward and adaptable methodology with a rapid calibration procedure, making it easily transferable to clinical applications.
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Hybrid and bioinspired methods outperform isolated approaches by balancing stiffness and flexibility.
“These methods outperform isolated approaches by balancing stiffness and flexibility [46].”
From Hybrid Fault-Tolerant Control in Cooperative Robotics: Advances in Resilience and Scalability (2025) · cites this paper as [46]
The Introduction and Discussion (pages unavailable in our copy) support a narrower advantage for hybrid FES–robot assistance: better tracking than FES alone while using less motor torque than motor-only assistance. The Discussion also reports worse tracking than motor-only assistance. The paper does not describe a bioinspired method or attribute these trade-offs to balancing stiffness and flexibility. (LLM, conf=0.86)
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- Authors
- Dalla Gasperina, S., Ferrari, F., Gandolla, M., Pedrocchi, A., & Ambrosini, E.
- Affiliations
- Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Italy
- Politecnico di Milano (IT)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2024-09
- Volume
- 71
- Issue
- 9
- Pages
- 2642-2650
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W4394627653
- Cited by
- 18
- References
- 27
- Citations by year
- 2026: 7 · 2025: 10 · 2023: 1
- FWCI
- 2.70
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
- Funders
- Istituto Nazionale per l'assicurazione contro gli Infortuni sul Lavoro (PR19-RR-P5)
- Topics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Keywords
- functional electrical stimulation, robotic assistance, upper limb rehabilitation, neurorehabilitation, hybrid control, torque distribution, impedance control, iterative learning control, muscle fatigue, elbow flexion, trajectory tracking
- MeSH terms
- Adult, Electric Stimulation Therapy, Female, Humans, Male, Robotics, Torque, Upper Extremity, Young Adult
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