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. 2019 May 28;16(1):63.
doi: 10.1186/s12984-019-0536-6.

Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset

Néstor J Jarque-Bou  1 , Alessandro Scano  2   3 , Manfredo Atzori  4 , Henning Müller  5   6
Affiliations

Kinematic synergies of hand grasps: a comprehensive study on a large publicly available dataset

Néstor J Jarque-Bou et al. J Neuroeng Rehabil. .

Abstract

Background: Hand grasp patterns require complex coordination. The reduction of the kinematic dimensionality is a key process to study the patterns underlying hand usage and grasping. It allows to define metrics for motor assessment and rehabilitation, to develop assistive devices and prosthesis control methods. Several studies were presented in this field but most of them targeted a limited number of subjects, they focused on postures rather than entire grasping movements and they did not perform separate analysis for the tasks and subjects, which can limit the impact on rehabilitation and assistive applications. This paper provides a comprehensive mapping of synergies from hand grasps targeting activities of daily living. It clarifies several current limits of the field and fosters the development of applications in rehabilitation and assistive robotics.

Methods: In this work, hand kinematic data of 77 subjects, performing up to 20 hand grasps, were acquired with a data glove (a 22-sensor CyberGlove II data glove) and analyzed. Principal Component Analysis (PCA) and hierarchical cluster analysis were used to extract and group kinematic synergies that summarize the coordination patterns available for hand grasps.

Results: Twelve synergies were found to account for > 80% of the overall variation. The first three synergies accounted for more than 50% of the total amount of variance and consisted of: the flexion and adduction of the Metacarpophalangeal joint (MCP) of fingers 3 to 5 (synergy #1), palmar arching and flexion of the wrist (synergy #2) and opposition of the thumb (synergy #3). Further synergies refine movements and have higher variability among subjects.

Conclusion: Kinematic synergies are extracted from a large number of subjects (77) and grasps related to activities of daily living (20). The number of motor modules required to perform the motor tasks is higher than what previously described. Twelve synergies are responsible for most of the variation in hand grasping. The first three are used as primary synergies, while the remaining ones target finer movements (e.g. independence of thumb and index finger). The results generalize the description of hand kinematics, better clarifying several limits of the field and fostering the development of applications in rehabilitation and assistive robotics.

Keywords: Cluster analysis; Cyberglove; Hand synergies; Kinematics; Myoelectric prostheses; Principal component analysis; Rehabilitation.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
a Cyberglove II device. b The number and corresponding position of each Cyberglove sensor
Fig. 2
Fig. 2
The 20 grasps considered in the study. They provide a comprehensive mapping of the repertoire of hand grasps available to human subjects, and are stored in the publicly available NinaPro Database
Fig. 3
Fig. 3
List of recorded anatomical angles. Nomenclature: _F for flexion (circles), _A for abduction (triangles); 1 to 5, digits
Fig. 4
Fig. 4
Sign criteria for the CMC joint of the thumb
Fig. 5
Fig. 5
Histograms of % variance explained (a) and number of PCs (b) versus number of subjects
Fig. 6
Fig. 6
Dendrogram for cluster composition. Using angles between data as pairwise-distance and Complete linkage algorithms for cluster composition in the Dendrogram. The horizontal axis represents all the PCs with 418 numbers of clustered nodes; vertical axis represents the distance between the observed subjects in a logarithmic scale
Fig. 7
Fig. 7
Percentage of the variance explained (calculated as the number of PCs in each group divided by the total amount of PCs) for each group of the 23 synergies found when cutting the dendrogram tree at a distance of 80
Fig. 8
Fig. 8
Bar and error plots representing mean and standard deviation of the loadings of different joints for the 12 synergies considered. The picture highlights the joint correlations represented by each synergy. Positive values represent flexion for PIP (2–5)_F, IP1_F, MCP (1–5)_F, WRIST_F, CMC5_F and CMC1_F; abduction for CMC1_A; radial deviation for WRIST_A; and fingers separated for MCP (3–4, 4–5)_A
Fig. 9
Fig. 9
Number of PCs grouped in each of the 12 synergies selected (e.g. the first synergy was found in 70 subjects)
See this image and copyright information in PMC

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