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the claim

Two-way communication between a brain and a prosthetic limb is technologically possible

the verdict
SUPPORTED
the evidence backs this
Recorded sources
8 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Extensive research into neuroprosthetics and closed-loop systems demonstrates that bidirectional communication between the nervous system and prosthetic limbs is technologically feasible.

The analysis

The retrieved literature consistently supports the claim that two-way communication (motor control signals sent to the prosthesis and sensory or myoelectric feedback returned to the user) is both technologically possible and actively being improved across various prosthetic applications.

Evidence for · 8
Recorded source metadata

Ting Zhang, Li Jiang, Hong Liu. Design and Functional Evaluation of a Dexterous Myoelectric Hand Prosthesis With Biomimetic Tactile Sensor. 2018. https://doi.org/10.1109/TNSRE.2018.2844807

Paper 0 demonstrates a dexterous prosthetic hand controlled by electromyography signals with integrated tactile sensor feedback.

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More for · 7
Recorded source metadata

Jack Tchimino, M. Marković, J. Dideriksen, S. Došen. The effect of calibration parameters on the control of a myoelectric hand prosthesis using EMG feedback. 2021. https://doi.org/10.1088/1741-2552/ac07be

Paper 1 investigates closing the control loop in myoelectric hand prostheses using EMG-based feedback.

Recorded source metadata

Patrick G. Sagastegui Alva, A. Boesendorfer, O. Aszmann, J. Ibáñez, D. Farina. Excitation of natural spinal reflex loops in the sensory-motor control of hand prostheses. 2024. https://doi.org/10.1126/scirobotics.adl0085

Paper 2 evaluates sensory feedback and spinal reflex integration in prosthesis control.

Recorded source metadata

Filip Gašparić, N. Jorgovanovic, Christian Hofer, Michael F. Russold, Mario Koppe, D. Stanisic, S. Došen. A Novel Sensory Feedback Approach to Facilitate Both Predictive and Corrective Control of Grasping Force in Myoelectric Prostheses. 2023. https://doi.org/10.1109/TNSRE.2023.3330502

Paper 4 discusses providing artificial sensory feedback via stimulation to improve grasping control in myoelectric prostheses.

Recorded source metadata

Zhuozhi Zhang, Anran Xie, Chih-hong Chou, Wenyuan Liang, Jie Zhang, Sheng Bi, Ning Lan. Closed-Loop Force Control by Biorealistic Hand Prosthesis With Visual and Tactile Sensory Feedback. 2024. https://doi.org/10.1109/TNSRE.2024.3439722

Paper 5 shows that tactile sensory feedback enhances grasp force control in biorealistic hand prostheses.

Recorded source metadata

Rudroff T. Non-Invasive Brain Stimulation and Artificial Intelligence in Communication Neuroprosthetics: A Bidirectional Approach for Speech and Hearing Impairments.. 2025. https://doi.org/10.3390/brainsci15050449

Paper 6 explores communication neuroprosthetics featuring bidirectional neural signal processing.

Recorded source metadata

Mariscal DM, Driscoll B, Huang H, Fisher LE. Somatosensory restoration and neural control strategies in lower-limb prostheses.. 2025. https://doi.org/10.1038/s44385-025-00050-w

Paper 7 reviews neuroprosthetics for somatosensory restoration and prosthetic control in bidirectional neuroprostheses.

Recorded source metadata

Zhang B, You X, Liu Y, Xu J, Xu S. Multi-Level Perception Systems in Fusion of Lifeforms: Classification, Challenges and Future Conceptions.. 2026. https://doi.org/10.3390/s26020576

Paper 10 surveys advancements in neuroprosthetics and closed-loop brain-computer interfaces achieving deep human-machine integration.

The paper trail · every fact has a biography
first checked01 Aug 2026
judged → SUPPORTED · 8601 Aug 2026
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