11 resultados para FINGERS

em CentAUR: Central Archive University of Reading - UK


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The brain keeps track of the changing positions of body parts in space using a spatial body schema. When subjects localise a tactile stimulus on the skin, they might either use a somatotopic body map, or use a body schema to identify the location of the stimulation in external space. Healthy subjects were touched on the fingertips, with the hands in one of two postures: either the right hand was vertically above the left, or the fingers of both hands were interwoven. Subjects made speeded verbal responses to identify either the finger or the hand that was touched. Interweaving the fingers significantly impaired hand identification across several experiments, but had no effect on finger identification. Our results suggest that identification of fingers occurs in a somatotopic representation or finger schema. Identification of hands uses a general body schema, and is influenced by external spatial location. This dissociation implies that touches on the finger can only be identified with a particular hand after a process of assigning fingers to hands. This assignment is based on external spatial location. Our results suggest a role of the body schema in the identification of structural body parts from touch.

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We studied the effect of tactile double simultaneous stimulation (DSS) within and between hands to examine spatial coding of touch at the fingers. Participants performed a go/no-go task to detect a tactile stimulus delivered to one target finger (e.g., right index), stimulated alone or with a concurrent non-target finger, either on the same hand (e.g., right middle finger) or on the other hand (e.g., left index finger=homologous; left middle finger=non-homologous). Across blocks we also changed the unseen hands posture (both hands palm down, or one hand rotated palm-up). When both hands were palm-down DSS interference effects emerged both within and between hands, but only when the non-homologous finger served as non-target. This suggests a clear segregation between the fingers of each hand, regardless of finger side. By contrast, when one hand was palm-up interference effects emerged only within hand, whereas between hands DSS interference was considerably reduced or absent. Thus, between hands interference was clearly affected by changes in hands posture. Taken together, these findings provide behavioral evidence in humans for multiple spatial coding of touch during tactile DSS at the fingers. In particular, they confirm the existence of representational stages of touch that distinguish between body-regions more than body-sides. Moreover, they show that the availability of tactile stimulation side becomes prominent when postural update is required.

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The ten-volume edition of The Collected Works of Thomas Heywood, forthcoming from Oxford University Press from 2015 to 2022, will attempt to place Heywood’s plays, poetry, and prose back where they belong: at the centre of the study of early modern English literature, drama, and theatre history. Especially as an actor, playwright, reviser, editor, and historical chronicler, Heywood had the longest and widest-ranging career of his contemporaries and thus can reveal how sixteenth- and seventeenth-century authors and theatrical and literary audiences came to see the practice and production of drama.

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Context: Evidence is limited on the effects of different patterns of use of postmenopausal hormone therapy on fracture incidence and particularly on the effects of ceasing use. Objective: To investigate the effect of different patterns of hormone therapy use on fracture incidence. Design, Setting, and Participants: Prospective study of 138737 postmenopausal women aged 50 to 69 years recruited from the UK general population in 19961998 (the Million Women Study) and followed up for 1.9 to 3.9 years (average, 2.8 years) for fracture incidence. Main Outcome Measure: Adjusted relative risk (RR) for incident fracture (except fracture of the fingers, toes, and ribs) in hormone therapy users compared with never users at baseline. Results: A total of 5197 women (3.7%) reported 1 or more fractures, 79% resulting from falls. Current users of hormone therapy at baseline had a significantly reduced incidence of fracture (RR, 0.62; 95% confidence interval [CI], 0.58-0.66; P<.001). This protection was evident soon after hormone therapy began, and the RR decreased with increasing duration of use (P=.001). Among current users at baseline the RR of fracture did not vary significantly according to whether estrogen-only, estrogen-progestin, or other types of hormones were used (RR [95% CI], 0.64 [0.58-0.71], 0.58 [0.53-0.64], and 0.67 [0.56-0.80], respectively; P=19), nor did it vary significantly according to estrogen dose or estrogen or progestin constituents. The RR associated with current use of hormone therapy did not vary significantly according to 11 personal characteristics of study participants, including their age at menopause, body mass index, and physical activity. Past users of hormone therapy at baseline experienced no significant protection against fractures (RR, 1.07; 95% CI, 0.99-1.15); incidence rates returned to those of never-users within about a year of ceasing use. Conclusions: All types of hormone therapy studied confer substantial protection against fracture while they are used. This protection appears rapidly after use commences and wears off rapidly after use ceases. The older women are, the greater is their absolute reduction in fracture incidence while using hormone therapy.

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Most haptic environments are based on single point interactions whereas in practice, object manipulation requires multiple contact points between the object, fingers, thumb and palm. The Friction Cone Algorithm was developed specifically to work well in a multi-finger haptic environment where object manipulation would occur. However, the Friction Cone Algorithm has two shortcomings when applied to polygon meshes: there is no means of transitioning polygon boundaries or feeling non-convex edges. In order to overcome these deficiencies, Face Directed Connection Graphs have been developed as well as a robust method for applying friction to non-convex edges. Both these extensions are described herein, as well as the implementation issues associated with them.

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Previous work has presented the friction cone algorithm, a generalised method to resolve forces on a simulated haptic object when two or more fingers are in contact. Two extensions to the friction cone algorithm are presented: force shading and bump mapping. Force shading removes the discontinuities that are present when transitioning from one face to the next, whilst bump mapping provides a mechanism for rendering haptic textures on polygonal surfaces. Both these extensions can be combined whilst still maintaining the friction cone algorithm's intrinsic ability to simulate arbitrarily complex friction models.

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The problem of the appropriate distribution of forces among the fingers of a four-fingered robot hand is addressed. The finger-object interactions are modelled as point frictional contacts, hence the system is indeterminate and an optimal solution is required for controlling forces acting on an object. A fast and efficient method for computing the grasping and manipulation forces is presented, where computation has been based on using the true model of the nonlinear frictional cone of contact. Results are compared with previously employed methods of linearizing the cone constraints and minimizing the internal forces.

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Although the somatosensory homunculus is a classically used description of the way somatosensory inputs are processed in the brain, the actual contributions of primary (SI) and secondary (SII) somatosensory cortices to the spatial coding of touch remain poorly understood. We studied adaptation of the fMRI BOLD response in the somatosensory cortex by delivering pairs of vibrotactile stimuli to the finger tips of the index and middle fingers. The first stimulus (adaptor) was delivered either to the index or to the middle finger of the right or left hand, whereas the second stimulus (test) was always administered to the left index finger. The overall BOLD response evoked by the stimulation was primarily contralateral in SI and was more bilateral in SII. However, our fMRI adaptation approach also revealed that both somatosensory cortices were sensitive to ipsilateral as well as to contralateral inputs. SI and SII adapted more after subsequent stimulation of homologous as compared with nonhomologous fingers, showing a distinction between different fingers. Most importantly, for both somatosensory cortices, this finger-specific adaptation occurred irrespective of whether the tactile stimulus was delivered to the same or to different hands. This result implies integration of contralateral and ipsilateral somatosensory inputs in SI as well as in SII. Our findings suggest that SI is more than a simple relay for sensory information and that both SI and SII contribute to the spatial coding of touch by discriminating between body parts (fingers) and by integrating the somatosensory input from the two sides of the body (hands).

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Detection of a tactile stimulus on one finger is impaired when a concurrent stimulus (masker) is presented on an additional finger of the same or the opposite hand. This phenomenon is known to be finger-specific at the within-hand level. However, whether this specificity is also maintained at the between-hand level is not known. In four experiments, we addressed this issue by combining a Bayesian adaptive staircase procedure (QUEST) with a two-interval forced choice (2IFC) design in order to establish threshold for detecting 200ms, 100Hz sinusoidal vibrations applied to the index or little fingertip of either hand (targets). We systematically varied the masker finger (index, middle, ring, or little finger of either hand), while controlling the spatial location of the target and masker stimuli. Detection thresholds varied consistently as a function of the masker finger when the latter was on the same hand (Experiments 1 and 2), but not when on different hands (Experiments 3 and 4). Within the hand, detection thresholds increased for masker fingers closest to the target finger (i.e., middle>ring when the target was index). Between the hands, detection thresholds were higher only when the masker was present on any finger as compared to when the target was presented in isolation. The within hand effect of masker finger is consistent with the segregation of different fingers at the early stages of somatosensory processing, from the periphery to the primary somatosensory cortex (SI). We propose that detection is finger-specific and reflects the organisation of somatosensory receptive fields in SI within, but not between the hands.

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Most current state-of-the-art haptic devices render only a single force, however almost all human grasps are characterised by multiple forces and torques applied by the fingers and palms of the hand to the object. In this chapter we will begin by considering the different types of grasp and then consider the physics of rigid objects that will be needed for correct haptic rendering. We then describe an algorithm to represent the forces associated with grasp in a natural manner. The power of the algorithm is that it considers only the capabilities of the haptic device and requires no model of the hand, thus applies to most practical grasp types. The technique is sufficiently general that it would also apply to multi-hand interactions, and hence to collaborative interactions where several people interact with the same rigid object. Key concepts in friction and rigid body dynamics are discussed and applied to the problem of rendering multiple forces to allow the person to choose their grasp on a virtual object and perceive the resulting movement via the forces in a natural way. The algorithm also generalises well to support computation of multi-body physics

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We assess the corticomuscular coherence (CMC) of the contralateral primary motor cortex and the hand muscles during a finger force-tracking task and explore whether the pattern of finger coordination has an impact on the CMC level. Six healthy subjects (three men and three women) were recruited to conduct the force-tracking tasks comprising two finger patterns, i.e., natural combination of index and middle fingers and unnatural combination of index and middle fingers (i.e., simultaneously producing equal force strength in index and middle finger). During the conducting of the tasks with right index and middle finger, MEG and sEMG signals were recorded from left primary motor cortex (M1) and right flexor digitorum superficialis (FDS), respectively; the contralateral CMC was calculated to assess the neuromuscular interaction. Finger force-tracking tasks of Common-IM only induce beta-band CMC, whereas Uncommon-IM tasks produce CMC in both beta and low-gamma band. Compared to the force-tracking tasks of Common-IM, the Uncommon-IM task is associated with the most intensive contralateral CMC. Our study demonstrated that the pattern of finger coordination had significant impact on the CMC between the contralateral M1 and hand muscles, and more corticomuscular interaction was necessary for unnaturally coordinated finger activities to regulate the fixed neural drive of hand muscles.