Many current neurophysiological, psychophysical, and psychological approaches to vision rest on the idea that when we see, the brain produces an internal representation of the world. The activation of this internal representation is assumed to give rise to the experience of seeing. The problem with this kind of approach is that it leaves unexplained how the existence of such a detailed internal representation might produce visual consciousness. An alternative proposal is made here. We propose that seeing is a way of acting. It is a particular way of exploring the environment. Activity in internal representations does not generate the experience of seeing. The outside world serves as its own, external, representation. The experience of seeing occurs when the organism masters what we call the governing laws of sensorimotor contingency. The advantage of this approach is that it provides a natural and principled way of accounting for visual consciousness, and for the differences in the perceived quality of sensory experience in the different sensory modalities. Several lines of empirical evidence are brought forward in support of the theory, in particular: evidence from experiments in sensorimotor adaptation, visual \"filling in,\" visual stability despite eye movements, change blindness, sensory substitution, and color perception.

A sensorimotor account of vision and visual consciousness-Authors' Response-Acting out our sensory experience

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Biomechanics And Motor Control Of Human Movement

The complete title of this book runs ‘Analyzing Linguistic Data: A Practical Introduction to Statistics using R’ and as such it very well reflects the purpose and spirit of the book. The author guides the reader in about 350 pages from descriptive and basic statistical methods over classification and clustering to (generalised) linear and mixed models. Each of the methods is introduced in the context of concrete linguistic problems and demonstrated on exciting datasets from current research in the language sciences. In line with its practical orientation, the book focuses primarily on using the methods and interpreting the results. This implies that the mathematical treatment of the techniques is held at a minimum if not absent from the book. In return, the reader is provided with very detailed explanations on how to conduct the analyses using R [1]. The first chapter sets the tone being a 20-page introduction to R. For this and all subsequent chapters, the R code is intertwined with the chapter text and the datasets and functions used are conveniently packaged in the languageR package that is available on the Comprehensive R Archive Network (CRAN). With this approach, the author has done an excellent job in enabling researchers and students alike to reproduce the analyses and learn by doing. Another quality as a textbook is the fact that every chapter ends with Workbook sections where the user is invited to exercise his or her analysis skills on supplemental datasets. Full solutions including code, results and comments are given in Appendix A (30 pages). Instructors are therefore very well served by this text, although they might want to balance the book with some more mathematical treatment depending on the target audience. After the introductory chapter on R, the book opens on graphical data exploration. Chapter 3 treats probability distributions and common sampling distributions. Under basic statistical methods (Chapter 4), distribution tests and tests on means and variances are covered. Chapter 5 deals with clustering and classification. Strangely enough, the clustering section has material on PCA, factor analysis, correspondence analysis and includes only one subsection on clustering, devoted notably to hierarchical partitioning methods. The classification part deals with decision trees, discriminant analysis and support vector machines. The regression chapter (Chapter 6) treats linear models, generalised linear models, piecewise linear models and a substantial section on models for lexical richness. The final chapter on mixed models is particularly interesting as it is one of the few text book accounts that introduce the reader to using the (innovative) lme4 package of Douglas Bates which implements linear mixed-effects models. Moreover, the case studies included in this

Analyzing linguistic data: a practical introduction to statistics using R

Evidence-based guidelines on the therapeutic use of transcranial direct current stimulation (tDCS)

The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic.

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Diverse Applications of Nanomedicine

Aim of this work is to design and develop an instrumented cylindrical object equipped with force sensors, which is able to assess grasping performance of both human and robotic hands. The object is made of two concentric shells between which sixteen piezoresistive sensors have been located in order to measure the forces applied by the hand fingers during grasping. Furthermore, a magneto-inertial unit has been positioned inside the object for acquiring information about object orientation during manipulation. A wireless communication between the electronic boards, responsible for acquiring the data from the sensors, and a remote laptop has been guaranteed. The object has been conceived in such a way to be adopted for evaluating both power and precision grasps and for measuring the forces applied by each finger of the hand. In order to evaluate object performance, a finite element analysis for estimating the deformation of the external shell for different force values has been carried out. Moreover, to evaluate object sensitivity, a static analysis of the force transmitted by the external shell to the underlying sensors has been performed by varying the thickness of the shells. The obtained preliminary results have validated the feasibility of using the developed object for assessing grasping performed by human and robotic hands.

Design and development of a sensorized cylindrical object for grasping assessment

Wearable devices are extensively used for monitoring physiological parameters both in clinical settings and in sports science. Among others, respiratory rate is mostly neglected but is a valid index to assess athletes' performance. The purpose of this work was to test a wearable device composed of two elastic bands embedding conductive textiles during a running session of approximately 9.5 km. The test has been carried out by a young healthy volunteer who worn two bands on the rib cage (one on the upper thorax and one on the umbilicus). The frequency-domain analysis allowed estimating both respiratory parameters (i.e., the average respiratory rate, $\overline{f_{R}})$ and running related parameters (i.e., estimated running distance and average running pace). The wearable system was able to perform a good estimation of both respiratory and gait parameters allowing a better understanding of the relationship between the fatigue and the respiratory activity, enabling a more accurate running performance evaluation.

A wearable system for respiratory and pace monitoring in running activities: a feasibility study

Fiber Bragg Grating (FBG) technology is very attractive to develop sensors for the measurement of thermal and mechanical parameters in biological applications, particularly in presence of electromagnetic interferences. This work presents the design, working principle and experimental characterization of a force sensor based on two FBGs, with the feature of being compatible with Magnetic Resonance. Two prototypes based on different designs are considered and characterized: 1) the fiber with the FBGs is encapsulated in a polydimethylsiloxane (PDMS) sheet; 2) the fiber with the FBGs is free without the employment of any polymeric layer. Results show that the prototype which adopts the polymeric sheet has a wider range of measurement (4200 mN vs 250 mN) and good linearity; although it has lower sensitivity (≈0.1 nm-N(1) vs 7 nm-N(1)). The sensor without polymeric layer is also characterized by employing a differential configuration which allows neglecting the influence of temperature. This solution improves the linearity of the sensor, on the other hand the sensitivity decreases. The resulting good metrological properties of the prototypes here tested make them attractive for the intended application and in general for force measurement during biomedical applications in presence of electromagnetic interferences.

An MR-compatible force sensor based on FBG technology for biomedical application

Neuro-Developmental Engineering (NDE) is a new and emerging interdisciplinary research area at the intersection of developmental neuroscience and bioengineering aiming at providing new methods and tools for: i) understanding neuro-biological mechanisms of human brain development; ii) quantitative analysis and modeling of human behavior during neurodevelopment; iii) assessment of neuro-developmental milestones achieved by humans from birth onwards. Main application fields of NDE are:

/pdf/neuro-developmental-engineering-towards-early-diagnosis-of-5e9469s10v.pdf

Neuro-Developmental Engineering: towards Early Diagnosis of Neuro-Developmental Disorders

This work proposes a mechatronic solution to increase the backdrivability of a rehabilitation robot in order to cope with intrinsic kinematic constraints which are adopted by the human brain to solve redundancy in motor tasks. In order to reduce the interaction force between the user and the robot and ensure the robot to follow subjects movements a pure force control algorithm has been adopted. The Control law has been validated on the MIT-Manus robotic system: first simulation tests have been performed, and then experimental trials on the real machine have been realized in several operative conditions. A net decrease of human force required to execute a motor task in interaction with the robot has been verified both in simulation tests and experimental validation; this confirms that force control effectively reduce the robot perturbation to subjects intrinsic motor strategies. From these observations it would be possible to define useful indications for the design of a new generation of rehabilitative robots, which comply with constraints of neural origin.

Domenico Formica

Papers

Design and development of a sensorized cylindrical object for grasping assessment

A wearable system for respiratory and pace monitoring in running activities: a feasibility study

An MR-compatible force sensor based on FBG technology for biomedical application

Neuro-Developmental Engineering: towards Early Diagnosis of Neuro-Developmental Disorders

Coping with intrinsic constraints of neural origin in the design of rehabilitation robots: A preliminary study