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SKM, V.

Publications and source records attributed to SKM, V..

2 recordsLinked to original sources

Effort distribution changes effector choice, behaviour and performance: A visuomotor tracking study using finger forces

Human movement and its associated performance are bounded by a hierarchy of constraints operating over certain control variables. One such variable of both physiological and behavioural importance is the mechanical effort exerted by the participating elements. Here, we explored how motor performance is affected by the distribution of work, and consequently the effort.\n\nUsing human hand as a model, we employed a visuomotor tracking task to study the associated motor performance when mechanical effort exerted by the fingers are modulated. The subject has to trace a set of ideal paths provided on visual feedback screen to reach a target through a cursor controlled by index and little finger forces. Modulation of these forces allows us to see how the perceived effort requirement affects the tracking performance. In this task demanding two-element coordination, we represent index finger as the independent/dominant element against little finger as the dependent/subjugate counterpart. We study how increasing mechanical effort contribution from the independent element leads to changes in both behaviour and performance.\n\nWe found that despite higher mechanical requirements of employing index finger to produce larger absolute force, the movement control system continues to prefer it as against little finger which could have produced smaller absolute force. Moreover, the observation of better tracking performance under larger contributions from the independent component reflects to a plausible hierarchy of constraints employed in the motor control system that operates with more than one objective, energy minimisation per se. At least for the behaviour in study, the improved motor performance suggests that the control system prefers higher independence of the participating elements.

neuroscience

Sensor location optimization and joint angle prediction in hand postures

1. Sensor selection problem 1. Sensor selection problem Grasping of objects (Mason et al. 2001; Santello et al. 2002) or hand shaping during grasping is of interest in robotics, neuroscience, and biomechanics. In animation industry and biomechanics, tracking body and hand movements are essential. For tracking body movements and hand movements, a sizable number of markers are required. As number of marker increase complexity and cost also increase. Researchers have tried various approaches for selecting a set of minimum no. of markers for accurate reproduction of movements. Data-driven approaches have been proposed for classification of various grasps. Some studies have focussed on prediction of joint angles (Kang et al. 2012; Hoyet et al. 2012; Wheatland et al. 2013). Our objective is to predict joint angles from a reduced set of sensors. For preliminary sorting purpose, we used PCA based sensor ranking which is disc ...

bioengineering