Design, prototyping and testing of a bioinspired prosthetic hand finger based on six-bar linkage
This study presents the design, prototyping, and testing of a bioinspired 1-degree-of-freedom prosthetic hand finger based on a six-bar linkage. The objective is to replicate natural finger motion patterns and subject-specific anthropometric features to prospectively overcome the problem of devices abandonment and enhance usability in everyday life. The design leverages additive manufacturing techniques and 3D scanning, which play a crucial role to enable affordable customization. The proposed methodology integrates kinematic synthesis, performance evaluation, and sensitivity analysis to identify an optimal mechanism robust to fabrication inaccuracies. The selected solution exhibits bioinspired linear couplings among joints flexion/extension closely resembling the reference human average ones, with strong linear trends ( R 2 ≥ 0.97 ) and low deviations from desired proximal and distal couplings (≤0.07, ≤0.05). A unitary load was applied under the worst-case configuration of the mechanism: the static analysis identified maximum joint reaction forces of 14 - 18 N and actuation torques of 80 - 110 N mm, while the FEM-based evaluation revealed a safety factor of 3.8. The final design was prototyped and tested to verify the expected motion, showing fingertip RMSE of 2.27 mm compared to human motion, closely replicating human finger trajectories. • Linear intra-finger couplings allow for underactuation of 1-DoF prosthetic fingers. • General Performance Index combines kinematic and static metrics for mechanism optimal selection. • Sensitivity analysis filters mechanisms, favoring robustness to fabrication inaccuracies. • Six-bar linkages for prosthetic fingers can closely replicate human fingertip motion.
Authors
- Loredana Zollo (ORCID: https://orcid.org/0000-0002-8015-010X)
- Nevio Luigi Tagliamonte (ORCID: https://orcid.org/0000-0001-5595-7481)
- Salvatore Maria Li Gioi (ORCID: https://orcid.org/0009-0009-8599-3032)
- Fabrizio Taffoni (ORCID: https://orcid.org/0000-0003-3215-1375)
- Francesca Cordella (ORCID: https://orcid.org/0000-0002-6946-0377)
- Alessandro Ceccarelli (ORCID: https://orcid.org/0009-0009-9252-7849)
- Ludovica Nini
Institutions
- Università Campus Bio-Medico (IT)
Publication Details
- Journal
- Results in Engineering
- Published
- 2025-11-06
- DOI
- https://doi.org/10.1016/j.rineng.2025.107989
- Primary Topic
- Robot Manipulation and Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00