Abstract
BackgroundA proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative analyses of the movements and thus they are usually not quantitatively justified.MethodsThis paper presents to the best of our knowledge the first quantitative taxonomy of hand grasps based on biomedical data measurements. The taxonomy is based on electromyography and kinematic data recorded from 40 healthy subjects performing 20 unique hand grasps. For each subject, a set of hierarchical trees are computed for several signal features. Afterwards, the trees are combined, first into modality-specific (i.e. muscular and kinematic) taxonomies of hand grasps and then into a general quantitative taxonomy of hand movements. The modality-specific taxonomies provide similar results despite describing different parameters of hand movements, one being muscular and the other kinematic.ResultsThe general taxonomy merges the kinematic and muscular description into a comprehensive hierarchical structure. The obtained results clarify what has been proposed in the literature so far and they partially confirm the qualitative parameters used to create previous taxonomies of hand grasps. According to the results, hand movements can be divided into five movement categories defined based on the overall grasp shape, finger positioning and muscular activation. Part of the results appears qualitatively in accordance with previous results describing kinematic hand grasping synergies.ConclusionsThe taxonomy of hand grasps proposed in this paper clarifies with quantitative measurements what has been proposed in the field on a qualitative basis, thus having a potential impact on several scientific fields.
Highlights
A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation
The data analysis procedure can be summarized as data acquisition (“Data acquisition” subsection), signal feature extraction (“Surface Electromyography (sEMG) and data glove signal processing” subsections), creation of the hierarchical trees (“Hierarchical trees” subsection) and fusion of the trees into super-trees (“Computation of the muscular, kinematic and general quantitative taxonomies: hierarchical super-trees” subsection), a procedure coming from genetics studies and leading to the general quantitative taxonomy of hand movements
This work presents a quantitative taxonomy of hand grasps based on muscular and kinematic data, described in detail in “General quantitative taxonomy of hand grasps based on muscular and kinematic data” subsection
Summary
A proper modeling of human grasping and of hand movements is fundamental for robotics, prosthetics, physiology and rehabilitation. The taxonomies of hand grasps that have been proposed in scientific literature so far are based on qualitative analyses of the movements and they are usually not quantitatively justified. A taxonomy of hand movements is important for several scientific fields, including robotics, prosthetics, physiology and rehabilitation. It can be useful to compare the functionality of robotic hands with real human hands. Very advanced myoelectric hands have been developed from a mechanical point of view but they are usually not well accepted by amputees [2,3,4]. A taxonomy of hand grasps can foster the development of prosthetic hands that perform movements corresponding to the taxonomic groups that are mostly useful in real life situations. A comprehensive quantitative comparison of hand grasps may create a link between
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