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Über dieses Buch

This book presents a new set of devices for accurate investigation of human finger stiffness and force distribution in grasping tasks. The ambitious goal of this research is twofold, the first is to advance the state of the art on human strategies in manipulation tasks and provide tools to assess rehabilitation procedure and the second is to investigate human strategies for impedance control that can be used for human robot interaction and control of myoelectric prosthesis.

Part one describes two types of systems that are able to achieve a complete set of measurements on force distribution and contact point locations. The effectiveness of these devices in grasp analysis is also experimentally demonstrated and applications to neuroscientific studies are discussed. In part two, the devices are exploited in two different studies to investigate stiffness regulation principles in humans. The first study provides evidence on the existence of coordinated stiffening patterns in the fingers of human hands and establishes initial steps towards a real-time and effective modelling of finger stiffness in tripod grasp. The second study presents experimental findings on how humans modulate their hand stiffness whilst grasping objects of varying levels of compliance.

The overall results give solid evidence on the validity and utility of the proposed devices to investigate human grasp properties. The underlying motor control principles that are exploited by humans in the achievement of a reliable and robust grasp can potentially be integrated into the control framework of robotic or prosthetic hands to achieve a similar interaction performance.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract
The investigation of the strategies of human motor control in grasping task represents a relevant topic in neuroscience with applications in robotics. Such an investigation requires the development and the exploitation of sensing tools and devices, which are able to record all the necessary information, and for this purpose, new custom devices are developed and exploited. The ambitious goal of this work is twofold: (1) to advance the state of the art on human strategies in manipulation tasks and provide tools to assess rehabilitation procedure and (2) to investigate human strategies for impedance control that can be used for human robot interaction and control of myoelectric prosthesis. Although the goal complexity requires many efforts, this book achieved tangible and original contributions that are suitable for robotic/prosthetic and human motor control studies.
Alessandro Altobelli

Chapter 2. Human Hand Motor Control Studies

Abstract
This chapter aims to give a brief overview on the complexity that is typical of hand motor control studies. Starting from biomechanical hand models to recent theories on motor control in grasping tasks, in this dissertation the important factors which affect grasp proprieties are dealt. The mechanical structure of human hand is extremely complex and difficult to model; its rigid internal framework is made by 27 bones that are moved by 18 intrinsic muscles and 18 extrinsic muscles coupled by a network of tendons. To have a simple hand model, at least 23–24 DoFs are needed: 4 DoFs for each finger, 5 for the thumb, 1 for the radioulnar joint, and 2 at the wrist. In a more detailed model, the number of DoFs increases just taking into account the hand’s capability to create a palmar arch when it closes. A complete biomechanical model includes 36 muscles coupled to the bones by a complex tendons network; moreover, several biomechanical constraints have to be included in the model. Joint limits or finger dimensions are clear examples of constraints which can affect the interaction of the hand with the world, and additional constraints arise from the coupling of tendons and muscles. Some muscles span several phalanges, making it difficult to move only one joint independently; for example, the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC) muscles are divided on each finger; therefore, a contraction of these muscles engages several hand joints. Understanding how humans exploit biomechanics and sensory feedback of hand in everyday tasks is a challenging topic that still is not completely understood. Several studies and theories, focused on kinematic and grasping tasks have been developed. In the next section, I will give an introduction on the most recent studies which focus on important aspects of manipulation: (i) hand control in pre-grasp phase, (ii) grasp force distributions, (iii) muscle activations, and (iv) impedance control.
Alessandro Altobelli

Devices for Human Grasp Studies

Frontmatter

Chapter 3. Sensorized Object Approach

Abstract
In this section, I presented two instrumented objects designed to be grasped with three-digit finger posture. Four different force/torque sensors are fixed in a profitably configuration to allow measures of contact forces exerted by each finger and the external wrench. Changing the stiffness at each contact independently is possible by two different haptic solutions. Experimental results show the validity and utility of proposed devices to investigate human grasp proprieties. As evidenced in the previous chapter, these systems constrain the hand posture throughout the grasp phase but allow to measure all: (i) the contact positions and (ii) the force/torque components at each contact. In the next subsections, the devices are described and validated in a more detailed way.
Alessandro Altobelli

Chapter 4. Wearable Approach: ThimbleSense, a Fingertip-Wearable Tactile Sensor for Grasp Analysis

Abstract
In this chapter, I tested and validated the “ThimbleSense” system, a new wearable individual-digit force/torque sensor developed and presented by Battaglia et al (Thimblesense: an individual-digit wearable tactile sensor for experimental grasp studies, 2014 IEEE International Conference on Robotics and Automation (ICRA), 2728–2735 (2014) [1]). This system aims to integrate the grasp analysis achievable with sensorized objects presented in the Chap. 2 where the position of the contact surfaces is fixed. ThimbleSense allows to obtain measurement of contact forces between hand and grasped objects without constrains on the hand postures. The main advantage of this approach with respect to more conventional solutions is the possibility of being versatile without losing accuracy: instead of building many sensorized objects for different experiments, it is possible to employ ThimbleSense to study grasps of a variety of objects, while still retaining the complete force/torque measurements. Unfortunately, ThimbleSense rigid shells are interposed between the fingertip and grasped object. This inevitably modifies the physiological mechanical deformation that would otherwise occur at the bare fingerpad in direct contact with objects. An experiment shows that excessive grip forces are attenuated with training as the subjects familiarize him/herself with the ThimbleSense. This effect evidences that sensorized object and wearable object are both necessary to investigate different aspects of human grasp. In this work, I briefly introduce the concept and the implementation of individual-digit wearable force/torque sensors; later, I present some experiments to validate the device (Battaglia et al, Thimblesense: A fingertip wearable tactile sensor for grasp analysis (2015) [2]). In particular, my contributions in this work are: (i) to define a procedure to handle F/T sensor offsets and to estimate the inertial parameters of the device in static conditions and (ii) to validate the measures of the device with some experiments. Results evidenced that internal forces estimated with the ThimbleSense are inside the null space of the grasp matrix.
Alessandro Altobelli

Studies and Experiments on Three Digit Grasp

Frontmatter

Chapter 5. Electromyographic Mapping of Finger Stiffness in Tripod Grasp

Abstract
In the first part, I described and validated a sensorized object with easy to change contact surfaces of customizable stiffness; in this chapter, this device is profitably integrated in a new setup to identify the stiffness of hand finger tips in a tripod grasp pose. Understanding the policy used by human to modulate the stiffness in grasping task is important to develop suitable control in robotics, rehabilitation, and teleoperation. As previously said in Chap. 1, few studies investigate about finger stiffness control performed by human in grasping tasks. Toward the twofold purpose of investigating the presence of coordinated regulations of the finger stiffness in human hand and the establishment of a real-time technique in modeling and identification of the finger stiffness while grasping, this study (Rossi et al, Electromyographic mapping of finger stiffness in tripod grasp: A proof of concept, (2015) [1]) explores the relation between the fingertip stiffness and the EMG activity of the antagonist muscles contributing to this profile. To achieve this, the experiments are performed with a custom version of tripod grasp device presented in Chap. 2. While constrained in a tripod posture, subjects held a stable level of stiffness and experienced a series of perturbations provided by the KUKA lightweight robot arm. EMG was recorded alongside force/torque measurements. Consequently, the map between the fingertip stiffness profiles is calculated from the force/torque measurements and the EMG data.
Alessandro Altobelli

Chapter 6. Effect of Homogenous Object Stiffness on Tri-Digit Proprieties

Abstract
In the previous chapter, I evidenced a relation between finger stiffness and EMG signals of principal finger muscles; in this study, I monitored the same muscle activity throughout the grasp of a instrumented manipulandum with different stiffnesses at contact points. To investigate the effect of the stiffness at contact point on the grasping force distribution, I profitably used the tools and method presented in the previous chapters. In effect, grasping of compliant objects presents additional uncertainties and Winges et al. (Winges et al, J Neurophysiol, 101(5), 2447–2458, 2009 [1]) showed that during a grasp, when one or two contact points are compliant, the activation patterns of finger muscles are different with respect to the case where the contact points are rigid. Besides analyzing the grip forces, to fully understand the control of hand grasping by the CNS, it is important to study how the hand stiffness is regulated during a grasp: stiffening behavior is commonly realized to stabilize movement or to fix posture in isometric tasks (Humphrey and Reed, Adv Neurol, 39, 347–372, 1983, [2]) and recent findings suggest that to some extent, grip stiffness is independent from grip force (Hoppner et al, Plos one 8(12), e80889, 2013, [3]). This study (Godfrey et al, Effect of homogenous object stiffness on tri-digit grasp properties, EMBC, 2015, [4]) aims to investigate the relation between object compliance and grasping stiffness of the hand. To achieve this goal, 11 subjects perform a grasp experiment exploiting a modified version of the manipulandum (see Sect. 2.​2) with three different contact modules. Each module is characterized by a certain level of stiffness: rigid, high, medium, or low stiffness. The experiment consisted of four blocks of trials, corresponding to the four different levels of stiffness; in each trial, the subject grasped and lifted the manipulandum 25 times, while the EMG was recorded from the flexor digitorum superficialis (FDS) and extensor digitorum communis (EDC). These two muscles are the main finger antagonist pair and thus can be used to monitor the EMG activity resulting in the production of grasp force as well as overall hand stiffness; this assumption is in agreement with the capability of the human control system to increase hand stiffness exploiting the co-contraction of antagonist muscles (Smith, Can J Physiol Pharmacol, 59(7), 733–747, 1981, [5]).
Alessandro Altobelli

Backmatter

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