Alejandro Melendez-Calderon

On the analysis of movement smoothness

Quantitative measures of smoothness play an important role in the assessment of sensorimotor impairment and motor learning. Traditionally, movement smoothness has been computed mainly for discrete movements, in particular arm, reaching and circle drawing, using kinematic data. There are currently very few studies investigating smoothness of rhythmic movements, and there is no systematic way of analysing the smoothness of such movements. There is also very little work on the smoothness of other movement related variables such as force, impedance etc. In this context, this paper presents the first step towards a unified framework for the analysis of smoothness of arbitrary movements and using various data. It starts with a systematic definition of movement smoothness and the different factors that influence smoothness, followed by a review of existing methods for quantifying the smoothness of discrete movements. A method is then introduced to analyse the smoothness of rhythmic movements by generalising the techniques developed for discrete movements. We finally propose recommendations for analysing smoothness of any general sensorimotor behaviour.

Sensory Agreement Guides Kinetic Energy Optimization of Arm Movements during Object Manipulation

The laws of physics establish the energetic efficiency of our movements. In some cases, like locomotion, the mechanics of the body dominate in determining the energetically optimal course of action. In other tasks, such as manipulation, energetic costs depend critically upon the variable properties of objects in the environment. Can the brain identify and follow energy-optimal motions when these motions require moving along unfamiliar trajectories? What feedback information is required for such optimal behavior to occur? To answer these questions, we asked participants to move their dominant hand between different positions while holding a virtual mechanical system with complex dynamics (a planar double pendulum). In this task, trajectories of minimum kinetic energy were along curvilinear paths. Our findings demonstrate that participants were capable of finding the energy-optimal paths, but only when provided with veridical visual and haptic information pertaining to the object, lacking which the trajectories were executed along rectilinear paths.

Robot-aided assessment of lower extremity functions: a review

The assessment of sensorimotor functions is extremely important to understand the health status of a patient and its change over time. Assessments are necessary to plan and adjust the therapy in order to maximize the chances of individual recovery. Nowadays, however, assessments are seldom used in clinical practice due to administrative constraints or to inadequate validity, reliability and responsiveness. In clinical trials, more sensitive and reliable measurement scales could unmask changes in physiological variables that would not be visible with existing clinical scores.In the last decades robotic devices have become available for neurorehabilitation training in clinical centers. Besides training, robotic devices can overcome some of the limitations in traditional clinical assessments by providing more objective, sensitive, reliable and time-efficient measurements. However, it is necessary to understand the clinical needs to be able to develop novel robot-aided assessment methods that can be integrated in clinical practice.This paper aims at providing researchers and developers in the field of robotic neurorehabilitation with a comprehensive review of assessment methods for the lower extremities. Among the ICF domains, we included those related to lower extremities sensorimotor functions and walking; for each chapter we present and discuss existing assessments used in routine clinical practice and contrast those to state-of-the-art instrumented and robot-aided technologies. Based on the shortcomings of current assessments, on the identified clinical needs and on the opportunities offered by robotic devices, we propose future directions for research in rehabilitation robotics. The review and recommendations provided in this paper aim to guide the design of the next generation of robot-aided functional assessments, their validation and their translation to clinical practice.

Motor adaptation with passive machines: A first study on the effect of real and virtual stiffness

Motor adaptation to novel force fields is considered as a key mechanism not only for the understanding of skills learning in healthy subjects but also for rehabilitation of neurological subjects. Several studies conducted over the last two decades used active robotic manipulanda to generate force fields capable of perturbing the baseline trajectories of both healthy and impaired subjects. Recent studies showed how motor adaptation to novel force fields can be induced also via virtual environments, whereas the effects of the force are projected onto a virtual hand, while the real hand remains constrained within a channel. This has great potentials of being translated into passive devices, rather than robotic ones, with clear benefits in terms of costs and availability of the devices. However, passive devices and virtual environments have received much less attention at least with regard to motor adaptation. This paper investigates the effects of both the real and virtual stiffness on motor adaptation. In particular, we tested 20 healthy subjects under two different real stiffness conditions (Stiff Channel vs Compliant Channel) and two different virtual conditions (Viscous vs Springy). Our main finding is that compliance of the channel favours a better adaptation featured with less lateral errors and longer retention of the after-effect. We posit that the physical compliance of the channel induces a proprioceptive feedback which is otherwise absent in a stiff condition.

On the assessment of coordination between upper extremities: towards a common language between rehabilitation engineers, clinicians and neuroscientists

Well-developed coordination of the upper extremities is critical for function in everyday life. Interlimb coordination is an intuitive, yet subjective concept that refers to spatio-temporal relationships between kinematic, kinetic and physiological variables of two or more limbs executing a motor task with a common goal. While both the clinical and neuroscience communities agree on the relevance of assessing and quantifying interlimb coordination, rehabilitation engineers struggle to translate the knowledge and needs of clinicians and neuroscientists into technological devices for the impaired. The use of ambiguous definitions in the scientific literature, and lack of common agreement on what should be measured, present large barriers to advancements in this area. Here, we present the different definitions and approaches to assess and quantify interlimb coordination in the clinic, in motor control studies, and by state-of-the-art robotic devices. We then propose a taxonomy of interlimb activities and give recommendations for future neuroscience-based robotic- and sensor-based assessments of upper limb function that are applicable to the everyday clinical practice. We believe this is the first step towards our long-term goal of unifying different fields and help the generation of more consistent and effective tools for neurorehabilitation.

Transfer of dynamic motor skills acquired during isometric training to free motion.

Recent studies have explored the prospects of learning to move without moving, by displaying virtual arm movement related to exerted force. However, it has yet to be tested whether learning the dynamics of moving can transfer to the corresponding movement. Here we present a series of experiments that investigate this isometric training paradigm. Subjects were asked to hold a handle and generate forces as their arms were constrained to a static position. A precise simulation of reaching was used to make a graphic rendering of an arm moving realistically in response to the measured interaction forces and simulated environmental forces. Such graphic rendering was displayed on a horizontal display that blocked their view to their actual (statically constrained) arm and encouraged them to believe they were moving. We studied adaptation of horizontal, planar, goal-directed arm movements in a velocity-dependent force field. Our results show that individuals can learn to compensate for such a force field in a virtual environment and transfer their new skills to the actual free motion condition, with performance comparable to practice while moving. Such nonmoving techniques should impact various training conditions when moving may not be possible.NEW & NOTEWORTHY This study provided early evidence supporting that training movement skills without moving is possible. In contrast to previous studies, our study involves 1) exploiting cross-modal sensory interactions between vision and proprioception in a motionless setting to teach motor skills that could be transferable to a corresponding physical task, and 2) evaluates the movement skill of controlling muscle-generated forces to execute arm movements in the presence of external forces that were only virtually present during training.

Acquisition of motor skills in isometric conditions through synesthetic illusions of movement

Interactive technologies can help people acquire movement skills, and one way is by using visual distortions to boost neural adaptation. An extreme version of such approach is to train a movement without moving by creating a synesthetic illusion of movement - displaying virtual motions when there is none. While this approach uses no proprioceptive error to drive adaptation, our results show encouraging evidence that motor skills can be acquired through such illusions of movement.

A wearable soft-robotic glove enables hand support in ADL and rehabilitation: A feasibility study on the assistive functionality

Background Elderly people frequently experience a decline in hand function, due to ageing or diseases. This leads to decreased independence in activities of daily living (ADL). Assistive technology may enhance independence. Objectives The objective of this paper was to explore user acceptance of an affordable wearable soft-robotic glove (ironHand (iH) system), that supports grip and hand opening in ADL. In addition, functional performance with the iH system was explored. Methods For this study 28 elderly people used the iH system across two sessions. During these sessions, participants performed six functional tasks with and without the iH system. Outcome measures were System Usability Scale (SUS), Intrinsic Motivation Inventory (IMI) and performance time of the functional tasks. Results User acceptance scored highly, with a mean SUS score of at least 63.4 (SD = 19.0) and a mean IMI score of 5.1 points (SD = 0.97 points). Functional task performance improved across repetitions both with and without the glove (p ≤ 0.017), but all functional tasks were performed faster without the glove (p ≤ 0.032). Conclusion Participants perceived the iH system as useful, pleasant and meaningful. The learning curve in functional performance time (improvements across repetitions) is promising, since it suggests there is room for improved performance when a longer acquaintance period is applied.

Haptic perception of multi-joint hypertonia during simulated patient-therapist physical tele-interaction

A potential solution to provide individualized physical therapy in remote areas is tele-interaction via robotic devices. To maintain stability during tele-interaction, transmission delay-compensation algorithms bound the impedance between the patient and the therapist. This can compromise the haptic perception of the patient being assessed, which can in turn lead to a bad diagnosis or intervention. We investigated how the perception of the severity of hypertonia (a common condition after neurological disorders) varied by modifying the connection impedance on a physical simulator. We found that assessing hypetonia using a low impedance connection may result in an overestimation of mild impairments.

Haptic recognition of dystonia and spasticity in simulated multi-joint hypertonia

This paper investigates the capability of naïve individuals to recognize dystonic- or spastic- like conditions through physical manipulation of a virtual arm. Subjects physically interact with a two-joint, six-muscle hypertonic arm model, rendered on a two degrees-of-freedom robotic manipulandum. This paradigm aims to identify the limitation of manual manipulation during diagnosis of hypertonia. Our results indicate that there are difficulties to discriminate between the two conditions at low to medium level of severity. We found that the sample entropy of the executed motion and the force experienced during physical manipulation, tended to be higher during incorrectly identified trials than in those correctly assessed.