Diego Torricelli

A neural-based remote eye gaze tracker under natural head motion

A novel approach to view-based eye gaze tracking for human computer interface (HCI) is presented. The proposed method combines different techniques to address the problems of head motion, illumination and usability in the framework of low cost applications. Feature detection and tracking algorithms have been designed to obtain an automatic setup and strengthen the robustness to light conditions. An extensive analysis of neural solutions has been performed to deal with the non-linearity associated with gaze mapping under free-head conditions. No specific hardware, such as infrared illumination or high-resolution cameras, is needed, rather a simple commercial webcam working in visible light spectrum suffices. The system is able to classify the gaze direction of the user over a 15-zone graphical interface, with a success rate of 95% and a global accuracy of around 2 degrees , comparable with the vast majority of existing remote gaze trackers.

Shared muscle synergies in human walking and cycling

The motor system may rely on a modular organization (muscle synergies activated in time) to execute different tasks. We investigated the common control features of walking and cycling in healthy humans from the perspective of muscle synergies. Three hypotheses were tested: 1) muscle synergies extracted from walking trials are similar to those extracted during cycling; 2) muscle synergies extracted from one of these motor tasks can be used to mathematically reconstruct the electromyographic (EMG) patterns of the other task; 3) muscle synergies of cycling can result from merging synergies of walking. A secondary objective was to identify the speed (and cadence) at which higher similarities emerged. EMG activity from eight muscles of the dominant leg was recorded in eight healthy subjects during walking and cycling at four matched cadences. A factorization technique [nonnegative matrix factorization (NNMF)] was applied to extract individual muscle synergy vectors and the respective activation coefficients behind the global muscular activity of each condition. Results corroborated hypotheses 2 and 3, showing that 1) four synergies from walking and cycling can successfully explain most of the EMG variability of cycling and walking, respectively, and 2) two of four synergies from walking appear to merge together to reconstruct one individual synergy of cycling, with best reconstruction values found for higher speeds. Direct comparison of the muscle synergy vectors of walking and the muscle synergy vectors of cycling (hypothesis 1) produced moderated values of similarity. This study provides supporting evidence for the hypothesis that cycling and walking share common neuromuscular mechanisms.

An adaptive blink detector to initialize and update a view-basedremote eye gaze tracking system in a natural scenario

A method for blink detection from video sequences gathered with a commercial camera is presented. This is used as a view-based remote eye gaze tracker (REGT) component performing two relevant functions, i.e. initialization and automatic updating in case of tracking failures. The method is based on frame differencing and eyes anthropometric properties. It has been tested on a publicly available database and results have been compared with algorithms found in literature. The obtained average true prediction rate is higher than 95%. The robustness of the automatic tracking failure detection has been tested on a set of experimental trials in different conditions, and yielded detection rates around 98%. The computational cost of the processing allows the blink detection algorithm to work in real time at 30fps. The obtained results are in favour of combining blink detection with gaze mapping for the development of a robust view-based remote eye-gaze tracker to be introduced in different HCI contexts, specifically in the assistive technology framework.

Human-like compliant locomotion: state of the art of robotic implementations

This review paper provides a synthetic yet critical overview of the key biomechanical principles of human bipedal walking and their current implementation in robotic platforms. We describe the functional role of human joints, addressing in particular the relevance of the compliant properties of the different degrees of freedom throughout the gait cycle. We focused on three basic functional units involved in locomotion, i.e. the ankle-foot complex, the knee, and the hip-pelvis complex, and their relevance to whole-body performance. We present an extensive review of the current implementations of these mechanisms into robotic platforms, discussing their potentialities and limitations from the functional and energetic perspectives. We specifically targeted humanoid robots, but also revised evidence from the field of lower-limb prosthetics, which presents innovative solutions still unexploited in the current humanoids. Finally, we identified the main critical aspects of the process of translating human principles into actual machines, providing a number of relevant challenges that should be addressed in future research.

Impact of specific symptoms of spasticity on voluntary lower limb muscle function, gait and daily activities during subacute and chronic spinal cord injury

BACKGROUND Although the spasticity syndrome is an important sensorimotor disorder, the impact of grade of lower limb muscle hypertonia, spasm and clonus activity on voluntary muscle function, gait and daily activities has not been systematically analysed during subacute and chronic spinal cord injury (SCI). OBJECTIVE To determine the prevalence of spasticity signs and symptoms during SCI, and to assess their impact on motor function and activities. METHODS A descriptive transverse study of sixty-six subjects with SCI was performed by assessing injury characteristics, spasticity (modified Ashworth scale, Penn scale, SCATS scale) and motor function (lower limb manual muscle scores, WISCI II, spinal cord injury spasticity evaluation tool). RESULTS Most subjects with the spasticity syndrome presented lower limb hypertonia and spasms during both subacute and chronic SCI, interfering with daily life activities. Subjects with incomplete SCI and hypertonia revealed a loss of voluntary flexor muscle activity, while extensors spasms contributed strongly to loss of gait function. The Penn spasms scale no correlated with muscle function or gait. CONCLUSIONS Specific diagnosis of spasm activity during subacute SCI, and its impact on lower limb voluntary muscle activity, gait function and daily activities, is required to develop a more effective neurorehabilitation treatment strategy.

A predictive model of muscle excitations based on muscle modularity for a large repertoire of human locomotion conditions

Humans can efficiently walk across a large variety of terrains and locomotion conditions with little or no mental effort. It has been hypothesized that the nervous system simplifies neuromuscular control by using muscle synergies, thus organizing multi-muscle activity into a small number of coordinative co-activation modules. In the present study we investigated how muscle modularity is structured across a large repertoire of locomotion conditions including five different speeds and five different ground elevations. For this we have used the non-negative matrix factorization technique in order to explain EMG experimental data with a low-dimensional set of four motor components. In this context each motor components is composed of a non-negative factor and the associated muscle weightings. Furthermore, we have investigated if the proposed descriptive analysis of muscle modularity could be translated into a predictive model that could: (1) Estimate how motor components modulate across locomotion speeds and ground elevations. This implies not only estimating the non-negative factors temporal characteristics, but also the associated muscle weighting variations. (2) Estimate how the resulting muscle excitations modulate across novel locomotion conditions and subjects. The results showed three major distinctive features of muscle modularity: (1) the number of motor components was preserved across all locomotion conditions, (2) the non-negative factors were consistent in shape and timing across all locomotion conditions, and (3) the muscle weightings were modulated as distinctive functions of locomotion speed and ground elevation. Results also showed that the developed predictive model was able to reproduce well the muscle modularity of un-modeled data, i.e., novel subjects and conditions. Muscle weightings were reconstructed with a cross-correlation factor greater than 70% and a root mean square error less than 0.10. Furthermore, the generated muscle excitations matched well the experimental excitation with a cross-correlation factor greater than 85% and a root mean square error less than 0.09. The ability of synthetizing the neuromuscular mechanisms underlying human locomotion across a variety of locomotion conditions will enable solutions in the field of neurorehabilitation technologies and control of bipedal artificial systems. Open-access of the model implementation is provided for further analysis at https://simtk.org/home/p-mep/.

Benchmarking Bipedal Locomotion: A Unified Scheme for Humanoids, Wearable Robots, and Humans

In the field of robotics, there is a growing awareness of the importance of benchmarking [1], [2]. Benchmarking not only allows the assessment and comparison of the performance of different technologies but also defines and supports the standardization and regulation processes during their introduction to the market. Its importance has been recently emphasized by the adoption of the technology readiness levels (TRLs) in the Horizon 2020 information and communication technologies by the European Union as an important guideline to assess when a technology can shift from one TRL to the other. The objective of this article is to define the basis of a benchmarking scheme for the assessment of bipedal locomotion that could be applied and shared across different research communities.

Tibialis Anterior muscle coherence during controlled voluntary activation in patients with spinal cord injury: diagnostic potential for muscle strength, gait and spasticity

BackgroundCoherence estimation has been used as an indirect measure of voluntary neurocontrol of residual motor activity following spinal cord injury (SCI). Here intramuscular Tibialis Anterior (TA) coherence estimation was performed within specific frequency bands for the 10-60 Hz bandwidth during controlled ankle dorsiflexion in subjects with incomplete SCI with and without spasticity.MethodsIn the first cohort study 15 non-injured and 14 motor incomplete SCI subjects were recruited to evaluate TA coherence during controlled movement. Specifically 15-30 Hz EMG was recorded during dorsiflexion with: i) isometric activation at 50, 75 and 100% of maximal voluntary torque (MVT), ii) isokinetic activation at 60 and 120°/s and iii) isotonic dorsiflexion at 50% MVT. Following identification of the motor tasks necessary for measurement of optimal TA coherence a second cohort was analyzed within the 10-16 Hz, 15-30 Hz, 24-40 Hz and 40-60 Hz bandwidths from 22 incomplete SCI subjects, with and without spasticity.ResultsIntramuscular 40-60 Hz, but not 15-30 Hz TA, coherence calculated in SCI subjects during isometric activation at 100% of MVT was lower than the control group. In contrast only isometric activation at 100% of MVT 15-30 Hz TA coherence was higher in subjects with less severe SCI (AIS D vs. AIS C), and correlated functionally with dorsiflexion MVT. Higher TA coherence was observed for the SCI group during 120°/s isokinetic movement. In addition 15-30 Hz TA coherence calculated during isometric activation at 100% MVT or 120°/s isokinetic movement correlated moderately with walking function and time from SCI, respectively. Spasticity symptoms correlated negatively with coherence during isometric activation at 100% of MVT in all tested frequency bands, except for 15-30 Hz. Specifically, 10-16 Hz coherence correlated inversely with passive resistive torque to ankle dorsiflexion, while clinical measures of muscle hypertonia and spasm severity correlated inversely with 40-60 Hz.ConclusionAnalysis of intramuscular 15-30 Hz TA coherence during isometric activation at 100% of MVT is related to muscle strength and gait function following incomplete SCI. In contrast several spasticity symptoms correlated negatively with 10-16 Hz and 40-60 Hz TA coherence during isometric activation at 100% MVT. Validation of the diagnostic potential of TA coherence estimation as a reliable and comprehensive measure of muscle strength, gait and spasticity should facilitate SCI neurorehabilation.

Teorías y modelos de control y aprendizaje motor. Aplicaciones clínicas en neurorrehabilitación

INTRODUCTION In recent decades there has been a special interest in theories that could explain the regulation of motor control, and their applications. These theories are often based on models of brain function, philosophically reflecting different criteria on how movement is controlled by the brain, each being emphasised in different neural components of the movement. The concept of motor learning, regarded as the set of internal processes associated with practice and experience that produce relatively permanent changes in the ability to produce motor activities through a specific skill, is also relevant in the context of neuroscience. Thus, both motor control and learning are seen as key fields of study for health professionals in the field of neuro-rehabilitation. DEVELOPMENT The major theories of motor control are described, which include, motor programming theory, systems theory, the theory of dynamic action, and the theory of parallel distributed processing, as well as the factors that influence motor learning and its applications in neuro-rehabilitation. CONCLUSIONS At present there is no consensus on which theory or model defines the regulations to explain motor control. Theories of motor learning should be the basis for motor rehabilitation. The new research should apply the knowledge generated in the fields of control and motor learning in neuro-rehabilitation.

Hybrid robotic systems for upper limb rehabilitation after stroke: A review

In recent years the combined use of functional electrical stimulation (FES) and robotic devices, called hybrid robotic rehabilitation systems, has emerged as a promising approach for rehabilitation of lower and upper limb motor functions. This paper presents a review of the state of the art of current hybrid robotic solutions for upper limb rehabilitation after stroke. For this aim, studies have been selected through a search using web databases: IEEE-Xplore, Scopus and PubMed. A total of 10 different hybrid robotic systems were identified, and they are presented in this paper. Selected systems are critically compared considering their technological components and aspects that form part of the hybrid robotic solution, the proposed control strategies that have been implemented, as well as the current technological challenges in this topic. Additionally, we will present and discuss the corresponding evidences on the effectiveness of these hybrid robotic therapies. The review also discusses the future trends in this field.