Formulación Topológica Adaptada para la Simulación y Control de Exoesqueletos Accionados con Transmisiones Harmonic Drive

[Resumen] Los sistemas de transmisión Harmonic Drive son muy utilizados en sistemas robóticos donde se requieren altas precisiones de trabajo. Este es el caso de los exosqueletos utilizados para la rehabilitación y asistencia de personas con problemas de movilidad. En la bibliografía existen diversos modelos de sistemas de transmisión Harmonic Drive, pero generalmente estos modelos son considerados de forma aislada, sin tener en cuenta su interacción con el entorno en el que son utilizados. Debido a la interacción que existe entre los exoesqueletos y las personas, es importante considerar los elementos de la transmisión de movimiento como una parte integral del sistema. Con este objetivo, en este artículo se presenta la inclusión de los sistemas Harmonic Drive dentro de una formulación topológica para la simulación de sistemas multicuerpo. El uso de coordenadas relativas hace que esta formulación sea especialmente idónea para el diseño de algoritmos de control para exoesqueletos donde los actuadores transmiten el movimiento a través de sistemas de transmisión Harmonic Drive. La formulación se ha implementado en Simulink y se ha presentado un ejemplo de control de posición en un modelo de exoesqueleto de una pierna con actuación en la cadera y la rodilla

Relative fascicle excursion effects on dynamic strength generation during gait in children with cerebral palsy

Evaluation of muscle structure gives us a better understanding of how muscles contribute to force generation which is significantly altered in children with cerebral palsy (CP). While most muscle structure parameters have shown to be significantly correlated to different expressions of strength development in children with CP and typically developing (TD) children, conflicting results are found for muscle fascicle length. Muscle fascicle length determines muscle excursion and velocity, and contrary to what might be expected, correlations of fascicle length to rate of force development have not been found for children with CP. The lack of correlation between muscle fascicle length and rate of force development in children with CP could be due, on the one hand, to the non-optimal joint position adopted for force generation on the isometric strength tests as compared to the position of TD children. On the other hand, the lack of correlation could be due to the erroneous assumption that muscle fascicle length is representative of sarcomere length. Thus, the relationship between muscle architecture parameters reflecting sarcomere length, such as relative fascicle excursions and dynamic power generation, should be assessed. Understanding of the underlying mechanisms of weakness in children with CP is key for individualized prescription and assessment of muscle-targeted interventions. Findings could imply the detection of children operating on the descending limb of the sarcomere length–tension curve, which in turn might be at greater risk of developing crouch gait. Furthermore, relative muscle fascicle excursions could be used as a predictive variable of outcomes related to crouch gait prevention treatments such as strength training

Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data

Upper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. To enrich the interpretation of data recorded during long-term tremor monitoring and to increase the intelligence of tremor suppression neuroprostheses we need to be aware of the context. Context awareness is a major challenge for neuroprostheses and would allow these devices to react more quickly and appropriately to the changing demands of the user and/or task. Traditionally kinematic features are used to extract context information, with most recently the use of joint angles as highly potential features. In this paper we present two algorithms that enable the robust extraction of joint angle and related features to enable long-term continuous monitoring of tremor with context awareness. First, we describe a novel relative sensor placement identification technique based on orientation data. We focus on relative rather than absolute sensor location, because in many medical applications magnetic and inertial measurement units (MIMU) are used in a chain stretching over adjacent segments, or are always placed on a fixed set of locations. Subsequently we demonstrate how tremor parameters can be extracted from orientation data using an adaptive estimation algorithm. Relative sensor location was detected with an accuracy of 94.12% for the 4 MIMU configuration, and 100% for the 3 MIMU configurations. Kinematic tracking error values with an average deviation of 8% demonstrate our ability to estimate tremor from orientation data. The methods presented in this study constitute an important step toward more user-friendly and context-aware neuroprostheses for tremor suppression and monitoring. © 2014 Lambrecht, Gallego, Rocon and Pons.This work has been funded by the European project NeuroTremor(ICT-2011.5.1-287739)andt he Spanish Consolider project HYPER (CSD2009-00067).Peer Reviewe

Automatic real-time monitoring and assessment of tremor parameters in the upper limb from orientation data

Upper limb tremor is the most prevalent movement disorder and, unfortunately, it is not effectively managed in a large proportion of the patients. Neuroprostheses that stimulate the sensorimotor pathways are one of the most promising alternatives although they are still under development. To enrich the interpretation of data recorded during long-term tremor monitoring and to increase the intelligence of tremor suppression neuroprostheses we need to be aware of the context. Context awareness is a major challenge for neuroprostheses and would allow these devices to react more quickly and appropriately to the changing demands of the user and/or task. Traditionally kinematic features are used to extract context information, with most recently the use of joint angles as highly potential features. In this paper we present two algorithms that enable the robust extraction of joint angle and related features to enable long-term continuous monitoring of tremor with context awareness. First, we describe a novel relative sensor placement identification technique based on orientation data. We focus on relative rather than absolute sensor location, because in many medical applications magnetic and inertial measurement units (MIMU) are used in a chain stretching over adjacent segments, or are always placed on a fixed set of locations. Subsequently we demonstrate how tremor parameters can be extracted from orientation data using an adaptive estimation algorithm. Relative sensor location was detected with an accuracy of 94.12% for the 4 MIMU configuration, and 100% for the 3 MIMU configurations. Kinematic tracking error values with an average deviation of 8% demonstrate our ability to estimate tremor from orientation data. The methods presented in this study constitute an important step toward more user-friendly and context-aware neuroprostheses for tremor suppression and monitoring

Technical validation of a body-weight controlled clutch for ankle-foot orthoses of children with cerebral palsy

[Abstract] Ankle-foot orthoses (AFOs) greatly improve gait in patients with Cerebral Palsy (CP). Some AFO designs allow for passive push-off support, however, these often limit the ankle’s ROM during the swing phase of gait. This contribution presents the technical validation of a body-weight controlled clutch (BWC) designed for children with CP, to passively engage and disengage the push-off support without restricting ankle kinematics. We determined the friction coefficient (μ) of different BWC prototypes, and used it as an indicator for the amount off force that can be exerted on the mechanism before slippage occurs. Four clutch configurations were tested, containing a rigid or flexible spacer and a nylon strapping webbing or neoprene rubber slider. The best tested configuration was the one composed by the rigid spacer–nylon slider combination, which yielded a μ as high as 0.98. We envision that a lightweight solution like the BWC presented here can benefit new AFO designs to support push-off on children with gait deficiencies.Royal Netherlands Academy of Arts & Sciences; KNAWWF/1327/TMB202101Dutch Research Council; 1807

Advances in selective activation of muscles for non-invasive motor neuroprostheses

Non-invasive neuroprosthetic (NP) technologies for movement compensation and rehabilitation remain with challenges for their clinical application. Two of those major challenges are selective activation of muscles and fatigue management. This review discusses how electrode arrays improve the efficiency and selectivity of functional electrical stimulation (FES) applied via transcutaneous electrodes. In this paper we review the principles and achievements during the last decade on techniques for artificial motor unit recruitment to improve the selective activation of muscles. We review the key factors affecting the outcome of muscle force production via multi-pad transcutaneous electrical stimulation and discuss how stimulation parameters can be set to optimize external activation of body segments. A detailed review of existing electrode array systems proposed by different research teams is also provided. Furthermore, a review of the targeted applications of existing electrode arrays for control of upper and lower limb NPs is provided. Eventually, last section demonstrates the potential of electrode arrays to overcome the major challenges of NPs for compensation and rehabilitation of patient-specific impairments.This work has been done with partial financial support of the Ministry of Science and Innovation, in the framework of national project HYPER(CSD 2009-00067- Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders) and European Union in the framework of TREMOR Project: “TREMOR: An ambulatory BCI-driven tremor suppression system based on functional electrical stimulation”, ICT-2007-224051, and “NeuroTREMOR: A novel concept for support to diagnosis and remote management of tremor”, ICT-2011.5.1-287739.Peer reviewe

Height-Speed dependent three-dimensional gait generator

[Resumen] En el campo de la rehabilitación robótica de la marcha, a menudo es necesario controlar los dispositivos robóticos para que sigan trayectorias de referencia específicas similares a las humanas. En los últimos años, se han propuesto varios modelos de generadores de marcha que proporcionan patrones de marcha personalizados ajustables a una serie de alturas y velocidades de marcha. Estos trabajos se desarrollaron centrándose principalmente en dispositivos de rehabilitación de la marcha que controlan las trayectorias angulares de las articulaciones inferiores. Otros dispositivos de rehabilitación similares, como los robots de rehabilitación con efector final que controlan las trayectorias de posición y orientación de sus articulaciones en el espacio cartesiano, no pueden implementarlos fácilmente. En este artículo se propone un nuevo generador de patrones de marcha que genera trayectorias tridimensionales individualizadas para robots de rehabilitación de la marcha. El modelo utiliza predicciones de las trayectorias angulares de las articulaciones, basadas en modelos de regresión multivariable, proporciones antropométricas humanas y modulaciones espaciotemporales para predecir las trayectorias cartesianas de las articulaciones inferiores de la pelvis, la cadera, la rodilla y el tobillo durante la marcha. Las trayectorias reconstruidas se compararon con la cinemática medida de un conjunto de datos de la marcha con 42 participantes que caminaban a 8 velocidades diferentes cada uno. Las trayectorias generadas coincidieron con las medidas con un error medio RMSE de 15,27 mm y coeficiente de correlación R medio de 89% para todos los ejes articulares, lo que sugiere que se trata de una buena solución para su aplicación en dispositivos robóticos de rehabilitación de la marcha con efector final.[Abstract] In the robotic gait rehabilitation field, it is often required to control the robotic devices to follow specific human-like reference trajectories. In the recent years, various gait generator models have been proposed, providing customized gait patterns adjustable to a range of heights and gait speeds. These works were developed focusing mainly on gait rehabilitation devices that control the angular trajectories of the lower joints. Similar rehabilitation devices, such as end-effector rehabilitation robots that control their joint position and orientation trajectories in the Cartesian space cannot easily implement them. In this article, it is proposed a new gait pattern generator that outputs individualized three-dimensional joints' trajectories for gait rehabilitation robots. The algorithm uses joint’s angular trajectories predictions, based on multi-variable regressions-models, human anthropometric proportions and spatiotemporal modulations to predict the cartesian lower joints trajectories of the pelvis, hip, knee and ankle during gait. The reconstructed trajectories were compared to the measured joint kinematics of a gait dataset with 42 participants walking at 8 different velocities each. The predicted trajectories matched the measured ones with an RMSE average error of 15.27mm and mean R coefficient of 89% for all the joints axis, suggesting to be a good solution to be applied in end-effector gait robotic rehabilitation devices.Ministerio de Ciencia e Innovación; PID2019-105110RB-C3

One central oscillatory drive is compatible with experimental motor unit behaviour in essential and Parkinsonian tremor

Pathological tremors are symptomatic to several neurological disorders that are difficult to differentiate and the way by which central oscillatory networks entrain tremorogenic contractions is unknown. We considered the alternative hypotheses that tremor arises from one oscillator (at the tremor frequency) or, as suggested by recent findings from the superimposition of two separate inputs (at the tremor frequency and twice that frequency). Approach. Assuming one central oscillatory network we estimated analytically the relative amplitude of the harmonics of the tremor frequency in the motor neuron output for different temporal behaviors of the oscillator. Next, we analyzed the bias in the relative harmonics amplitude introduced by superimposing oscillations at twice the tremor frequency. These findings were validated using experimental measurements of wrist angular velocity and surface electromyography (EMG) from 22 patients (11 essential tremor, 11 Parkinson’s disease). The ensemble motor unit action potential trains identified from the EMG represented the neural drive to the muscles. Main results. The analytical results showed that the relative power of the tremor harmonics in the analytical models of the neural drive was determined by the variability and duration of the tremor bursts and the presence of the second oscillator biased this power towards higher values. The experimental findings accurately matched the analytical model assuming one oscillator, indicating a negligible functional role of secondary oscillatory inputs. Furthermore, a significant difference in the relative power of harmonics in the neural drive was found across the patient groups, suggesting a diagnostic value of this measure (classification accuracy: 86%). This diagnostic power decreased substantially when estimated from limb acceleration or the EMG. Signficance. The results indicate that the neural drive in pathological tremor is compatible with one central network providing neural oscillations at the tremor frequency. Moreover, the regularity of this neural oscillation varies across tremor pathologies, making the relative amplitude of tremor harmonics a potential biomarker for diagnostic use

Trajectory Clustering for the Classification of Eye-Tracking Users With Motor Disorders

[Abstract] This paper presents a pilot study completed in the framework of the INTERAAC project. The aim of the project is to develop a new human-computer interaction (HCI) solution based on eye-gaze estimation from webcam images for people with motor disorders such as cerebral palsy, neurodegenerative diseases, and spinal cord injury that are otherwise unable to use a keyboard or mouse. In this study, we analyzed cursor trajectories recorded during the experiment and validated that users with different diseases can be automatically classi ed in groups based on trajectory metrics. For the clustering, Ward's method was used. The metrics are based on speed and acceleration statistics from full fi ltered tracks. The results show that the participants can be grouped into two main clusters. The main contribution of this work is the evaluation of the clustering techniques applied to eye-gaze trajecto- ries for the automatic classi cation of users diseases based on a real experiment carried with the help of three clinical partners in Spain.This work has been funded by the Spanish Ministry of Economy and Competitiveness, under the call Retos-Colaboración 2015 of the the National Programme for Research Aimed at the Challenges of Society 2009-2016 (RTC-2015-4327-1)https://doi.org/10.17979/spudc.978849749808