The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Control of Multifunctional Prosthetic Hands by Processing the Electromyographic Signal
Abstract
The human hand is a complex system, with a large number of degrees of freedom (DoFs), sensors embedded in its structure, actuators and tendons, and a complex hierarchical control. Despite this complexity, the efforts required to the user to carry out the different movements is quite small (albeit after an appropriate and lengthy training). On the contray, prosthetic hands are just a pale replication of the natural hand, with significantly reduced grasping capabilities and no sensory information delivered back to the user. Several attempts have been carried out to develop multifunctional prosthetic devices controlled by electromyographic (EMG) signals (myoelectric hands), harness (kinematic hands), dimensional changes in residual muscles, and so forth, but none ofthese methods permits the "natural" control of more than two DoFs. This article presents a review of the traditional methods used to control artificial hands by means of EMG signal, in both the clinical and research contexts, and introduces what could be the future developments in the control strategy of these devices.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“the formal scheme for the acquisition and analysis of EMG signals for the control of prosthetic devices is composed of several modules (Zecca et al., 2002) : (1) signal conditioning, pre-processing, and detection of onset movement (Micera et al., 1999) ; (2) feature extraction; (3) dimensionality reduction; (4) pattern recognition; and (5) off-line and on-line learning.”
From A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems (2005) · cites this paper as Zecca et al., 2002
In the citing paper
“Among the different approaches for restoring the link between the external world and the nervous system, the use of implantable intrafascicular PNS interfaces is of great potential, as confirmed in previous experiments in humans [6,7].”
From Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces (2011) · cites this paper as [7]
In the citing paper
“In fact, after appropriate control in experimental models to test their biocompatibility and efficacy [18], LIFEs have been recently used to control artificial devices [6,7,22-25] showing good results during short-term trials with human amputees.”
From Decoding of grasping information from neural signals recorded using peripheral intrafascicular interfaces (2011) · cites this paper as [7]
Citations
Cites
The publisher hasn’t deposited this paper’s reference list.
Cited by
Sorted by citations
Brain–machine interfaces: past, present and future
Lebedev, M. A., & Nicolelis, M. A. L. (2006) · Trends in Neurosciences · doi:10.1016/j.tins.2006.07.004 · Cited by 1,875
Feature reduction and selection for EMG signal classification
Phinyomark, A., Phukpattaranont, P., & Limsakul, C. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.01.102 · Cited by 1,605
Myoelectric control systems—A survey
Asghari Oskoei, M., & Hu, H. (2007) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2007.07.009 · Cited by 1,244
Restoring natural sensory feedback in real-time bidirectional hand prostheses
Raspopovic, S., Capogrosso, M., Petrini, F. M., Bonizzato, M., Rigosa, J., Di Pino, G., Carpaneto, J., Controzzi, M., Boretius, T., Fernandez, E., et al. (2014) · Science Translational Medicine · doi:10.1126/scitranslmed.3006820 · Cited by 1,001
Self-citationNavarro, X., Krueger, T. B., Lago, N., Micera, S., Stieglitz, T., & Dario, P. (2005) · Journal of the Peripheral Nervous System · doi:10.1111/j.1085-9489.2005.10303.x · Cited by 845
Self-citation
Metadata
- Authors
- Zecca, M., Micera, S., Carrozza, M. C., & Dario, P.
- Affiliations
- Scuola Superiore Sant'Anna (IT)
- Venue
- Critical Reviews? in Biomedical Engineering
- Publisher
- Begell House
- Published
- 2002
- Volume
- 30
- Issue
- 4-6
- Pages
- 459-485
- ISSN
- 0278-940X (ISSN-L)
- OpenAlex
- W4242470988
- Cited by
- 606
- References
- 0
- Citations by year
- 2026: 7 · 2025: 19 · 2024: 16 · 2023: 23 · 2022: 19 · 2021: 18 · 2020: 26 · 2019: 37 · 2018: 37 · 2017: 41 · 2016: 31 · 2015: 31 · 2014: 57 · 2013: 44 · 2012: 38
- FWCI
- 3.87
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Critical Reviews in Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
- Keywords
- prosthetic hand, myoelectric control, EMG signal processing, degrees of freedom, grasping, sensory feedback
- MeSH terms
- Algorithms, Artificial Limbs, Electromyography, Feedback, Hand, Hand Injuries, Humans, Pattern Recognition, Automated, Prosthesis Design, Quality Control, Signal Processing, Computer-Assisted, Neural Networks, Computer
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
