Tactile sensory control of the human hand

2021 ◽  
pp. 239-242
Author(s):  
Roland S. Johansson ◽  
Per F. Nordmark
Keyword(s):  
Motor System ◽  
Sensory Input ◽  
Human Hand ◽  
Nerve Fibres ◽  
Dexterous Manipulation ◽  
Anatomical Distribution ◽  
Sensory Control ◽  
Continuous Feedback

This chapter details the sensory input from the hand that is mediated by a system of fast-adapting and slowly adapting nerve fibres with a specific anatomical distribution and associations with particular sensory end organs that allow multimodal sensory input and processing. This highly refined system interacts with the motor system to provide continuous feedback that allows the dexterous manipulation of the environment that distinguishes the human hand.

The pathways for perception

2017 ◽  
Author(s):  
Ray Guillery
Keyword(s):  
Action Potentials ◽  
Sensory Input ◽  
Sensory Receptors ◽  
Nerve Fibres ◽  
Standard View ◽  
Nerve Roots ◽  
Functional Roles ◽  
The World ◽  
Sensory Pathway ◽  
Dorsal Nerve

Chapter 2 outlines some of the evidence on which the seemingly strong standard view has been based. The early discovery that ventral nerve roots of the spinal cord provide a motor output and dorsal nerve roots provide a sensory input supported the dichotomy of the standard view. Then as each sensory pathway was traced to the thalamus for relay to the cortex, the separate inputs from the sensory receptors—visual, auditory, gustatory, and so on—could be seen as providing the cortex with a ‘view’ of the world. The nature of this view became strikingly clear once investigators could understand (read) the messages that pass along the nerve fibres on the basis of very brief changes in membrane potentials, the action potentials. However, many branches given off by sensory fibres on their way to the thalamus remain unexplained on the standard view. These are important for the integrative sensorimotor view and their precise functional roles need to be defined.

scholarly journals Tactile Sensor Analysis during Early Stages of Manipulation for Single Grasp Identification of Daily Objects

2021 ◽  
Vol 6 (1) ◽  
pp. 56
Author(s):  
Vinicius Prado da Fonseca
Keyword(s):  
Wrist Joint ◽  
Somatosensory System ◽  
Tactile Sensor ◽  
Object Identification ◽  
Robotic Manipulation ◽  
Human Hand ◽  
Sample Collection ◽  
Dexterous Manipulation ◽  
Unstructured Environments ◽  
Early Phases

Dexterous robotic manipulation in unstructured environments is still challenging, despite the increasing number of robots entering human settings each day. Even though robotic manipulation provides complete solutions in factories and industries, it still lacks essential techniques, displaying clumsy or limited operation in unstructured environments. Daily objects typically aim at the human hand, and the human somatosensory system is responsible for solving all the complex calculations required for dexterous manipulations in unstructured settings. Borrowing concepts of the human visuotactile system can improve dexterous manipulation and increase robotics usage in unstructured environments. In humans, required finger and wrist joint adjustments occur after fast identification of the object in the initial stages of manipulation. Fast object identification during those phases may increase robotic dexterous manipulation performance. The present paper explores human-inspired concepts such as haptic glance to develop robotic single-grasp object identification. This concept can assist early phases of robotic manipulation, helping automated decision-making, such as type of grasp and joint position, during manipulation tasks. The main stages developed here are detecting sensor activation and sample collection using signal-to-noise and z-score filtering on tactile data. This procedure automates touch detection and reduces the sensor space for classification. Experiments on a daily objects dataset presented compelling results that will assist in the later stages of the early phases of robotic grasping.

scholarly journals Towards domain-general predictive coding: Expected TMS excites the motor system less effectively than unexpected stimulation

2020 ◽  
Author(s):  
Dominic M. D. Tran ◽  
Nicolas A. McNair ◽  
Justin A. Harris ◽  
Evan J. Livesey
Keyword(s):  
Motor System ◽  
Sensory Input ◽  
Primary Motor Cortex ◽  
Motor Evoked Potentials ◽  
Predictive Coding ◽  
Auditory Evoked Potential ◽  
Environmental Cues ◽  
Direct Stimulation ◽  
Predictive Learning ◽  
The Brain

AbstractThe brain’s response to sensory input is modulated by prediction. For example, sounds that are produced by one’s own actions, or those that are strongly predicted by environmental cues, are perceived as less salient and elicit an attenuated N1 component in the auditory evoked potential. Here we examined whether the neural response to direct stimulation of the brain is attenuated by prediction in a similar manner. Transcranial magnetic stimulation (TMS) applied over primary motor cortex can be used to gauge the excitability of the motor system. Motor-evoked potentials (MEPs), elicited by TMS and measured in peripheral muscles, are larger when actions are being prepared and smaller when actions are voluntarily suppressed. We tested whether the amplitude of MEPs was attenuated under circumstances where the TMS pulse can be reliably predicted, even though control of the relevant motor effector was never required. Self-initiation of the TMS pulse and reliable cuing of the TMS pulse both attenuated MEP amplitudes, compared to MEPs generated programmatically in an unpredictable manner. These results suggest that predictive coding may be governed by domain-general mechanisms responsible for all forms predictive learning.

Control of a Biomimetic Robot Hand Finger

2015 ◽  
pp. 475-499
Author(s):  
Yunus Ziya Arslan ◽  
Yuksel Hacioglu ◽  
Yener Taskin ◽  
Nurkan Yagiz
Keyword(s):  
Sliding Mode ◽  
Control Strategies ◽  
Metabolic Energy ◽  
Human Hand ◽  
Robot Hand ◽  
Robotic Hands ◽  
Dexterous Manipulation ◽  
Model And Simulation ◽  
Robot Hands ◽  
Biomimetic Robot

Due to the dexterous manipulation capability and low metabolic energy consumption property of the human hand, many robotic hands were designed and manufactured that are inspired from the human hand. One of the technical challenges in designing biomimetic robot hands is the control scheme. The control algorithm used in a robot hand is expected to ensure the tracking of reference trajectories of fingertips and joint angles with high accuracy, reliability, and smoothness. In this chapter, trajectory-tracking performances of different types of widely used control strategies (i.e. classical, robust, and intelligent controllers) are comparatively evaluated. To accomplish this evaluation, PID, sliding mode, and fuzzy logic controllers are implemented on a biomimetic robot hand finger model and simulation results are quantitatively analyzed. Pros and cons of the corresponding control algorithms are also discussed.

Mechanism Design of Anthropomorphic Robot Hand: Gifu Hand I

1999 ◽  
Vol 11 (4) ◽  
pp. 269-273 ◽  
Author(s):  
Haruhisa Kawasaki ◽  
◽  
Tsuneo Komatsu
Keyword(s):  
Mechanism Design ◽  
Design Concept ◽  
Human Hand ◽  
Robot Hand ◽  
Dexterous Manipulation ◽  
Grasping And Manipulation

This paper presents an anthropomorphic robot hand Gifu Hand I, to be used as a platform of robot hand for the study of dexterous manipulation. To perform grasping and manipulation like a human, the Gifu Hand I includes five fingers whose actuators are servomotors built in the palm and fingers. A thumb has four degreeof-freedom (DOF) and four joints, and fingers have three DOF and four joints. Two axes of joints near the palm cross orthogonally at one point like the human hand. The design concept of the anthropomorphic robot hand is presented and mechanisms and specifications of the developed robot hand are shown.

Function of sensory input in Insect motor systems

1981 ◽  
Vol 59 (7) ◽  
pp. 660-666 ◽  
Author(s):  
K. G. Pearson
Keyword(s):  
Motor Activity ◽  
Motor System ◽  
Sensory Input ◽  
External Environment ◽  
Motor Systems ◽  
Environmental Disturbances ◽  
Reflex Pathways ◽  
Locust Flight ◽  
And Function

The organization and function of sensory input has been examined in three insect motor systems: locust jumping, cockroach walking, and locust flight. In these three systems sensory input is primarily involved in the production of the normal patterns of motor activity rather than in the compensation for sudden changes in the external environment. At least two general functions for sensory input in the normal patterning of motor activity can be identified: (1) compensation for changes in the peripheral elements of the motor system which occur as a result of use and maturation and (2) regulation of switching from one phase of a movement to another following the attainment of a specific state by peripheral structures. Reflex pathways may exist for compensating for sudden environmental disturbances but these have not yet been clearly demonstrated.

scholarly journals Adaptability and Flexibility of the Human Motor System: Implications for Neurological Rehabilitation

2001 ◽  
Vol 8 (1-2) ◽  
pp. 131-140 ◽  
Author(s):  
Theo Mulder ◽  
Jacqueline Hochstenbach
Keyword(s):  
Transfer Of Learning ◽  
Motor System ◽  
Sensory Input ◽  
Environmental Changes ◽  
Dominant Role ◽  
Neurological Rehabilitation ◽  
Learning Context ◽  
Human Motor ◽  
Learning And Change

This article stresses the plasticity of the adult sensorimotor cortex in response to various injuries or environmental changes. The dominant role of sensory input is discussed. A number of studies are presented that show how input may lead to learning and change. Learning is discussed in relation to recovery. It is shown how concepts from the field of motor control and learning may be used for improving neurological rehabilitation. Specific attention is given to the variability of input, the meaningfulness of input, and the role of the learning context. The learning context and the application context should have essential characteristics in common, otherwise transfer of learning will be non-optimal. It is argued that learning landscapes are necessary in order to treat patients in such a way that he learned skills are transferable to situations outside the hospital.

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