Simple model of human arm reachable workspace

Lenarčič, Jadran; Umek, A.

doi:10.1109/21.299704

Cited by 95 publications

(41 citation statements)

References 8 publications

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“…For this reason, we selected a set of movements driven by the study of grasping taxonomies (Cutkosky, 1989;Feix et al, 2016), and the analysis of human upper limb movement workspace (Lenarcic and Umek, 1994;Abdel-Malek et al, 2004;Perry et al, 2007). The output of this selection resulted in a set of 30 different actions, divided into intransitive, transitive, and tool-mediated actions to avoid bias due to the affordances of the objects used for the grasp investigation.…”

Section: A Set Of Daily Living Tasksmentioning

confidence: 99%

“…Using this tool, we carried out a series of experiments with human considering a comprehensive dataset of daily living activities (ADLs) and grasping/manipulation actions. These actions were selected relying on the study of grasping taxonomies (Cutkosky, 1989;Feix et al, 2016), and considerations on human upper limb movement workspace (Lenarcic and Umek, 1994;Abdel-Malek et al, 2004;Perry et al, 2007). Our analysis has led to the reduction of complexity of upper limb trajectories by describing these as linear combinations of few principal functions (or modes).…”

Section: Introductionmentioning

confidence: 99%

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Unvealing the Principal Modes of Human Upper Limb Movements through Functional Analysis

et al. 2017

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The rich variety of human upper limb movements requires an extraordinary coordination of different joints according to specific spatio-temporal patterns. However, unvealing these motor schemes is a challenging task. Principal components have been often used for analogous purposes, but such an approach relies on hypothesis of temporal uncorrelation of upper limb poses in time. To overcome these limitations, in this work, we leverage on functional principal component analysis (fPCA). We carried out experiments with 7 subjects performing a set of most significant human actions, selected considering state-of-the-art grasp taxonomies and human kinematic workspace. fPCA results show that human upper limb trajectories can be reconstructed by a linear combination of few principal time-dependent functions, with a first component alone explaining around 60/70% of the observed behaviors. This allows to infer that in daily living activities humans reduce the complexity of movement by modulating their motions through a reduced set of few principal patterns. Finally, we discuss how this approach could be profitably applied in robotics and bioengineering, opening fascinating perspectives to advance the state of the art of artificial systems, as it was the case of hand synergies.

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Section: A Set Of Daily Living Tasksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Unvealing the Principal Modes of Human Upper Limb Movements through Functional Analysis

et al. 2017

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“…The shoulder complex radically increases the arms mobility and reachability by the use of sternoclavicular and scapulothoracic degree of freedom. This role of the sternoclavicular and the scapulothoracic joint in the human arm movement has been demonstrated in previous work of J. Lenarcic [2,3]. In recent investigations they also enlarge the self-motion ability and the amount of positioning redundancy of the arm [4].…”

Section: Introductionmentioning

confidence: 89%

Kinematic Design of 3-Limb Spatial Parallel Mechanism with Two Identical Limbs for a Humanoid Robotic Shoulder Complex

Rao¹

2017

IOSR JMCE

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“…Analysing the workspace of the human arm, is possible to obtain information for the design and control of the mechanism, and also, gives an understanding of the movement properties. In the case of the human arm, this study allows the planning and programming of rehabilitation process comparing the workspace of a normal patient, with a person with pathology deficient, this differences could be used for the diagnosis study (Lenarčič & Umek, 1994).…”

Section: Fig 3 Description Of Arm Transformationsmentioning

confidence: 99%