Posts Tagged Kinematics.

[ARTICLE] Kinematics in the brain: unmasking motor control strategies? – Full Text

 

Abstract

In rhythmical movement performance, our brain has to sustain movement while correcting for biological noise-induced variability. Here, we explored the functional anatomy of brain networks during voluntary rhythmical elbow flexion/extension using kinematic movement regressors in fMRI analysis to verify the interest of method to address motor control in a neurological population. We found the expected systematic activation of the primary sensorimotor network that is suggested to generate the rhythmical movement. By adding the kinematic regressors to the model, we demonstrated the potential involvement of cerebellar–frontal circuits as a function of the irregularity of the variability of the movement and the primary sensory cortex in relation to the trajectory length during task execution. We suggested that different functional brain networks were related to two different aspects of rhythmical performance: rhythmicity and error control. Concerning the latter, the partitioning between more automatic control involving cerebellar–frontal circuits versus less automatic control involving the sensory cortex seemed thereby crucial for optimal performance. Our results highlight the potential of using co-registered fine-grained kinematics and fMRI measures to interpret functional MRI activations and to potentially unmask the organisation of neural correlates during motor control.

Introduction

During rhythmical movement, sensory and motor systems need to interact closely to sustain the rhythm and to meet task requirements. Understanding how our system controls such a basic, all day movement is a prerequisite to improve motor (re)learning models to ameliorate rehabilitation in case of neurological movement disorders, like stroke. Mathematically, the simplest way to model rhythmicity is by means of a continuous oscillator (e.g. Haken et al. 1985). Biological noise interfering with planning and execution makes human movements unavoidably variable, which asks for correction processes (Franklin and Wolpert 2011). One of the principles governing human motor control states that optimised control is characterised by a maximum efficiency, e.g. minimal costs (Guigon et al. 2007). Minimal cost is dependent on the varying interaction between different system characteristics, including anatomical constraints, force generating capacities, and biological noise inducing the intra and interpersonal variability that is inherent to our system’s output (van Galen and Hueygevoort 2000).

Current knowledge about the neural correlates of rhythmical upper limb movement is based on standard finger and wrist movement paradigms that compare different movement conditions within people (high frequency versus low frequency, Kelso et al. 1998; rhythmic versus discrete movements, Schaal et al. 2004). Using this paradigm, simple unilateral rhythmical movements have been shown to elicit contralateral activations of the primary sensorimotor cortex (S1 + M1) and of the supplementary motor area (SMA), complemented by an ipsilateral activation of the anterior cerebellum (Allison et al. 2000; Ball et al. 1999; Schaal et al. 2004). Bilateral movements are associated with a symmetric facilitation of neural activity in the sensorimotor network, with additional frontal activations to ensure coordination between limbs. It is mediated by increased intrahemispheric connectivity and enhanced transcallosal coupling of SMA and M1 (Grefkes et al. 2008; Jäncke et al. 2000).

The activation pattern is comparable between dominant and non-dominant sided movements in extension and intensity when people move at their preferred frequency (Lutz et al. 2005; Jäncke et al. 2000; Koeneke et al. 2004). However, when movement frequency is imposed, activations during non-dominant sided movements increase in intensity compared to those of the dominant side (Lutz et al. 2005). Second, activation increases and expands for both uni and bilateral movements when movement frequency is increased above the preferred frequency (e.g. Kelso et al. 1998; Rao et al. 1996). Together, this demonstrates that moving at a non-preferred frequency is marked by an increase in costs. Therefore, imposing a fixed frequency may lead to different task-induced cost levels between participants and thus lead to biased results when comparing rhythmical motion and its neural correlates between people.

Over the time course of the movement, fine-grained kinematic variables capture the outcome of the interaction between the planned movement and the noise-dependent variability (Newell and Corcos 1993). Here, we explored whether kinematics may additionally provide information on the underlying control system, when the kinematic outcome is linked directly to brain activity. We simultaneously recorded brain activation (fMRI) and movement kinematics during a sensorimotor task that consisted of a self-paced continuous flexion/extension of the elbow. We focused on uni as well as bilateral movements, as many daily living tasks involve bilateral coordination. The task is evaluated as a simple well-known movement that does not require complex motor learning.

Based on the described theoretical model of motor control, we hypothesised that rhythmic voluntary flexion of the elbow is modulated by neural networks involved in (1) the sustained execution of the basic oscillatory rhythmical component and (2) correction processes in reaction to the variability resulting from biological noise. Sustaining the movement in rhythmical motion has been shown to involve the primary sensorimotor network, whereas discrete movements solicit additional higher cortical planning areas (Schaal et al. 2004). First, we expected to confirm the role of the sensorimotor network by performing a standard general linear-model analysis. Second, because task costs were as much equalised over participants as possible, we expected that correlating natural variation in movement execution with variation in BOLD-activation might unmask different brain regions involved in the secondary correction processes that could be (partly) separated from the primary sensorimotor network. […]

Continue —> Kinematics in the brain: unmasking motor control strategies? | SpringerLink

Fig. 2 Functional basis network: the main effect of task (flexion/extension of the elbow), FWE corrected, p < 0.05 at voxel level and the condition-specific activations p < 0.001, FWE corrected at cluster level, 22 degrees of freedom. R right sided, L left sided, B bilateral, U unilateral movement, RH right hemisphere, LH left hemisphere

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[ARTILE] Changes in gait kinematics and muscle activity in stroke patients wearing various arm slings – Full Text

Abstract

Stroke patients often use various arm slings, but the effects of different slings on the joint kinematics and muscle activity of the arm in the gait have not been investigated. The effects of joint kinematics and muscle activity in the gait were investigated to provide suggestions for gait training for stroke patients. In all, 10 chronic stroke patients were voluntarily recruited. An eight-camera three-dimensional motion analysis system was used to measure joint kinematics while walking; simultaneously, electromyography data were collected for the anterior and posterior deltoids and latissimus dorsi. The amplitude of pelvic rotation on the less-affected side differed significantly among the different arm slings (P<0.05). Changes in the knee kinematics of the less-affected side also differed significantly (P<0.05), while there were no significant differences in the muscle activity of the affected arm. In stroke patients, an extended arm sling is more useful than no sling or a flexed arm sling in terms of the amplitude of the rotation of the less-affected pelvic side in the stance phase while walking. The less-affected knee joint is flexed more without a sling than with any sling. All arm slings support the extension of the contralateral knee.

INTRODUCTION

Stroke is a major cause of morbidity worldwide. Approximately 800,000 patients have strokes annually (Lloyd-Jones et al., 2010). Patients with stroke have disabilities that result from paralysis, and most complain of difficulty walking (Jørgensen et al., 1995). Bovonsunthonchai et al. (2012) showed that the affected upper extremity is important for improving the performance and coordination of gait in stroke patients. In addition, the movement of the upper extremity improves the range of motion at the ankle as well as trunk stability (Stephenson et al., 2010).
Stroke patients often develop a subluxation of the shoulder on the affected side, because they can no longer support the weight of their own arm due to paralysis (Griffin et al., 1986). Consequently, arm slings are often necessary. Stroke patients often use a hemisling. Faghri et al. (1994) stated that use of a hemisling induced flexion synergy patterns of the upper trunk and delayed functional activity. However, few studies have examined how different arm slings, including a hemisling, affect the gait patterns of stroke patients. Reported studies have examined the hemisling in terms of the gait patterns (Yavuzer and Ergin, 2002), balance (Acar and Karatas, 2010), and energy consumption (Han et al., 2011) of stroke patients.
There are various types of arm sling, such as the flexed sling (a single-strap hemisling), extended sling (Bobath sling, Rolyan sling), GivMohr sling (Dieruf et al., 2005), and elastic arm sling (Hwang and An, 2015). The sling supports some of the weight of the arm and simultaneously limits the motion of the upper extremities. Pontzer et al. (2009)suggested that the arms serve as passive mass dampers to decrease the rotation of the torso and head. Lieberman et al. (20072008) also held that the arms serve as passive dampers to minimise vertical motion. The trunk and shoulders act as elastic linkages between the pelvis, shoulder girdle, and arms (Pontzer et al., 2009).
Some studies have examined the activities of the arm muscle during walking (Lieberman et al., 2007Prentice et al., 2001), while other studies have found that most of the arm swing is passive, while a small torque may actively occur in shoulder rotation (Jackson et al., 1978Kubo et al., 2004). The muscle activity of the upper extremities is still the subject of debate (Collins et al., 2009Kubo et al., 2004Kuhtz-Buschbeck and Jing, 2012). However, the restrictive effects and support provided by various arm slings could have different effects on the muscle activities of the affected arm in stroke patients.
Therefore, we investigated how the muscle activities of the affected arm and kinematic data taken during walking are influenced by flexion-type (hemisling), extension-type (Rolyan sling), and elastic arm slings under elastic tension. We discuss which arm should be used for clinical gait training.

Continue —> Changes in gait kinematics and muscle activity in stroke patients wearing various arm slings – ScienceCentral

Fig. 1 The conditions of the various arm slings: (A) none, (B) a flexed type, (C) an extended type, and (D) an elastic type.

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[Abstract] An extended kinematic model for arm rehabilitation training and assessment

Abstract

In the rehabilitation training and assessment of upper limbs, the conventional kinematic model treats the arm as a serial manipulator and maps the rotations in the joint space to movements in the Cartesian space. While this model brings simplicity and convenience, and thus has been overwhelming used, its accuracy is limited, especially for the distal parts of the upper limb that execute dexterous movements.

In this paper, a novel kinematic model of the arm has been proposed, which has been inspired by the biomechanical analysis of the forearm and wrist anatomy. One additional parameter is introduced into the conventional arm model, and then both the forward and inverse kinematic models of five parameters are derived for the motion of upper arm medial/lateral rotation, elbow flexion/extension, forearm pronation/supination, wrist flexion/extension and ulnar/radial deviation. Then, experiments with an advanced haptic interface have been designed and performed to examine the presented arm kinematic model. Data analysis revealed that accuracy and robustness can be significantly improved with the new model.

This extended arm kinematic model will help device development, movement training and assessment of upper limb rehabilitation.

Published in: Advanced Robotics and Mechatronics (ICARM), International Conference on

Source: An extended kinematic model for arm rehabilitation training and assessment – IEEE Xplore Document

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[ARTICLE] Walking through Apertures in Individuals with Stroke – Full Text

Abstract

Objective

Walking through a narrow aperture requires unique postural configurations, i.e., body rotation in the yaw dimension. Stroke individuals may have difficulty performing the body rotations due to motor paralysis on one side of their body. The present study was therefore designed to investigate how successfully such individuals walk through apertures and how they perform body rotation behavior.

Method

Stroke fallers (n = 10), stroke non-fallers (n = 13), and healthy controls (n = 23) participated. In the main task, participants walked for 4 m and passed through apertures of various widths (0.9–1.3 times the participant’s shoulder width). Accidental contact with the frame of an aperture and kinematic characteristics at the moment of aperture crossing were measured. Participants also performed a perceptual judgment task to measure the accuracy of their perceived aperture passability.

Results and Discussion

Stroke fallers made frequent contacts on their paretic side; however, the contacts were not frequent when they penetrated apertures from their paretic side. Stroke fallers and non-fallers rotated their body with multiple steps, rather than a single step, to deal with their motor paralysis. Although the minimum passable width was greater for stroke fallers, the body rotation angle was comparable among groups. This suggests that frequent contact in stroke fallers was due to insufficient body rotation. The fact that there was no significant group difference in the perceived aperture passability suggested that contact occurred mainly due to locomotor factors rather than perceptual factors. Two possible explanations (availability of vision and/or attention) were provided as to why accidental contact on the paretic side did not occur frequently when stroke fallers penetrated the apertures from their paretic side.

Introduction

Stroke is a disease caused by infarction, or hemorrhages of the blood vessels in the brain. Stroke is the major cause of neurological disabilities that affect many aspects of daily living. As one such issue, individuals with stroke often exhibit impaired walking, primarily due to motor paralysis on one side (typically the contralateral side of the affected side of the brain) of their body. A typical symptom indicating impaired walking is gait asymmetry. Gait asymmetry is the irregular coordination between the lower limbs and is produced mainly by differences in the magnitude of force displayed between the paretic and non-paretic limbs [1]. Walking with gait asymmetry is biomechanically inefficient for achieving forward progression and makes maintaining balance more challenging

A particularly challenging aspect of maintaining balance becomes much more evident during adaptive locomotion, i.e., when basic movement patterns need to be modified adaptively in response to environmental constraints. Previous studies have shown that, as compared to control individuals, stroke individuals had difficulty stepping over an obstacle [4], walking fast while performing a cognitive task concurrently [5], changing their walking speed in response to changes in the optic flow [6], changing direction while walking [79], and turning [10,11]. In fact, the risk of falling is likely to increase when stroke individuals turn [1214].

In line with these studies, the present study was designed to uncover challenging aspect of maintaining during adaptive locomotion in stroke individuals. The uniqueness of this study was to test their ability to safely walk through apertures. Adaptive modification of walking through a narrow aperture includes fine-tuning the walking direction toward the center of the aperture [15,16], decrease in movement speed [17,18], and changes in body configuration such as (upper-) body rotation in the yaw dimension [1726]. The most powerful means to avoid accidental contact is the body rotation because it effectively reduces horizontal space required for crossing. Testing the ability to safely walk through an aperture has helped not only to understand perceptual-motor control of adaptive locomotion for obstacle avoidance [17,2527] but also to describe the reason that controlling adaptive locomotion is difficult for some types of participants. Older adults had more variability in their body rotations at various aperture widths [28,29]. Patients with Parkinson’s disease (PD) showed sharply decreased walking speeds in front of an aperture, which could be caused by episodes of freezing [18]. When young adults used a manual wheelchair for the first time, contact with the frame of an aperture occurred more frequently with dramatically different spatial-temporal patterns of fixation [30,31]. To our knowledge, there has been no study testing the ability of stroke individuals to safely walk through an aperture.

 

Measuring the behavior of walking through an aperture potentially provides some new insights into the increased risk of instability during adaptive locomotion in stroke individuals. This is particularly because stroke individuals could show difficulty performing the body rotations due to their motor paralysis on one side of their body and, as a result, they could have difficulty avoiding accidental contact with the frame of apertures. Walking through a narrow aperture with body rotation results in unique postural configurations, i.e., the body is rotated in the yaw dimension while the walking direction is maintained toward the center of the aperture. The uniqueness of the body rotation behavior becomes clear when it is compared with the turning behavior, which also involves individuals rotating their bodies, while its purpose is to change the direction of walking. Rotating the body to walk through an aperture usually involves a pivot-like turn, in which the body rotates about its vertical axis on the trailing limb at the moment it crosses the aperture. If stroke individuals penetrate an aperture from the paretic side (i.e., the trailing limb is non-paretic), then they would be able to perform a pivot-like turn. However, they would have difficulty maintaining their balance after the turn because they need to shift their body weight to the leading, or paretic, limb to progress forward. In contrast, if stroke individuals penetrate an aperture from the non-paretic side (i.e., the trailing limb is paretic), then an alternate strategy, rather than a pivot-like turn, would be selected for rotating their bodies. In both cases, taking multiple steps to rotate the body, which has been observed in the turning behavior performed of older adults [32,33], was expected to occur. This was because it was effective, at least for stroke individuals, to avoid shifting their body weight onto the paretic limb for a relatively long time. However, because there has been no study, it remains unknown as to which strategy would be more preferable for strong individuals and which strategy would lead to safe walking through apertures without making any contact with the frame of an aperture. The rationale for conducting the present study was to clarify these issues.

 

In the present study, two groups of stroke individuals were recruited: stroke fallers and stroke non-fallers. Stroke fallers were identified as those having a history of falling history in the past year. A systematic review of the literature showed that a history of falling in the past year most strongly predicts the likelihood of future falls among community-living older adults [34]. Several previous studies have shown that significant gait characteristics of stroke individuals were more evident in those at high risk of falling [11,35]. Moreover, Takatori et al.(2009) reported that stroke individuals with a history of falls showed a large gap between the visual estimation of a reachable distance and the actual distance reachable [36]. If such a large gap between perception and action exists in various types of behavior, then stroke fallers would show inaccurate judgment of the passability of an aperture, which could lead to accidental contact with the frame of an aperture. To examine whether accidental contact was related to the inaccurate judgment of the passability of the aperture, participants in the present study performed both the behavioral task of walking through apertures and the perceptual judgment task of aperture passability.

Participants

 

Twenty-three individuals with stroke (eleven females) participated. The mean age was 60.7 years (SD = 10.1). Twenty-three age-, gender-, and height-matched healthy individuals also participated as control participants. This study was approved by the ethics committee of the Kameda Medical Center. The tenets of the Declaration of Helsinki were followed. All participants gave their written informed consent prior to participation. Notably, the individual shown in Fig 1 has given written informed consent (as outlined in PLOS consent form) to publish an image of the participant.

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Fig 1. An experimental task.

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A participant walks toward a door-like aperture. The individual shown in Fig 1 has given written informed consent (as outlined in PLOS consent form) to publish an image of the participant.

Continue —> Walking through Apertures in Individuals with Stroke

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[ARTICLE] Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients – Full Text

Abstract

Background

Common scales for clinical evaluation of post-stroke upper-limb motor recovery are often complemented with kinematic parameters extracted from movement trajectories. However, there is no a general consensus on which parameters to use. Moreover, the selected variables may be redundant and highly correlated or, conversely, may incompletely sample the kinematic information from the trajectories. Here we sought to identify a set of clinically useful variables for an exhaustive but yet economical kinematic characterization of upper limb movements performed by post-stroke hemiparetic subjects.

Methods

For this purpose, we pursued a top-down model-driven approach, seeking which kinematic parameters were pivotal for a computational model to generate trajectories of point-to-point planar movements similar to those made by post-stroke subjects at different levels of impairment.

Results

The set of kinematic variables used in the model allowed for the generation of trajectories significantly similar to those of either sub-acute or chronic post-stroke patients at different time points during the therapy. Simulated trajectories also correctly reproduced many kinematic features of real movements, as assessed by an extensive set of kinematic metrics computed on both real and simulated curves. When inspected for redundancy, we found that variations in the variables used in the model were explained by three different underlying and unobserved factors related to movement efficiency, speed, and accuracy, possibly revealing different working mechanisms of recovery.

Conclusion

This study identified a set of measures capable of extensively characterizing the kinematics of upper limb movements performed by post-stroke subjects and of tracking changes of different motor improvement aspects throughout the rehabilitation process.

Background

Upper limb functions are altered in about 80 % of acute stroke survivors and in about 50 % of chronic post-stroke patients [1]. With the increasing of life expectancy, it has been estimated that stroke related impairments will be ranked to the fourth most important causes of adult disability in 2030 [2], prompting the need to design more effective diagnostic and rehabilitative tools [3, 4].

Together with more traditional and widely accepted clinical scales in the last two decades investigators have characterized post-stroke motor recovery also in terms of kinematic parameters extracted from hand and arm task-oriented movements [3, 5], which offer more objective measures of motor performance [6]. Indeed, clinical scales, whose reliability has often been questioned [7, 8, 9], may not be sensitive to small and more specific changes [10] and could be of limited use to distinguish different aspects of motor improvement [11, 12].

Previous robot-assisted clinical and pilot studies have proposed a large set of kinematic parameters to characterize motor improvements [5, 6, 11]. A few of them focused on finding a significant relationship between robotic measures collected longitudinally in post-stroke patients and clinical outcome measures, to increase acceptance of kinematic evaluation scales in practice [5, 6]. Too little effort, however, has been made to identify the different aspects of movement improvement, how they can be described by kinematic robot-based measures [11], and whether they may dissociate with respect to recovery time course and to training response [11].

Indeed the range of potential changes in limb trajectory during recovery is not known a priori [12] and might not be fully represented by a set of arbitrarily selected parameters extracted from limb trajectories, even if the parameters were chosen according to a certain number of study hypotheses or to significant relationships with clinical scales. Moreover, these variables can be highly correlated and, thus, redundant. Although redundancy can be tackled by data reduction algorithms, such as Principal Component Analysis (PCA) or Independent Component Analysis (ICA) [5, 6], incomplete representation of information might still remain an overlooked issue.

In the present study we aimed at devising a novel method for identifying a set of kinematic measures potentially capable of fully highlighting and tracking changes of different aspects of movement performance throughout the rehabilitation training. Instead of starting from a certain number of a priori hypotheses, we sought to find which variables were essential for modeling trajectories of post-stroke patients and were, thus, informative of kinematic features of upper limb movements. We then tested whether the identified kinematic parameters i) were capable of highlighting changes in movement performance, ii) were to some extent redundant, and iii) were informative of different factors of post-stroke motor impairment, such as paresis, loss of fractionated movement and somatosensation, and abnormal muscle tone [13].

Continue —> Model-based variables for the kinematic assessment of upper-extremity impairments in post-stroke patients | Journal of NeuroEngineering and Rehabilitation | Full Text

Fig. 1 Schematic overview of the computational model for post-stroke trajectories simulation. (1) Endpoint kinematics of one pathological subject making point to point forward and backward movements from the center of the workspace to one of eight different targets equally spaced around a circle of 14 cm of radius assisted by InMotion2. (2) Kinematic parameters are extracted from the real trajectories of the post-stroke subjects. The tangential speed profile of real trajectories (for each movement direction and subject, separately for each group of patients and time of therapy) is analyzed to extract probability distributions of nPK, <σ>, T, and MV. (3) Based on the inferred probability distributions, tangential speed profiles of simulated trajectories are generated by solving a constrained optimization problem (Eq. 2). (4) The transversal and longitudinal speed profiles of real trajectories are analyzed to extract probability distributions of ratio-amp L , ratio-amp N , ratio-nPK, MV N , CONT L , and CONT N . (5) From the simulated tangential velocities and the inferred distributions of kinematic parameters, transversal and longitudinal speed profiles of simulated trajectories are generated, by solving an unconstrained optimization problem (Eq. 4). (6) The trajectories in the Cartesian space defined by the (L, N) axes (see step 4) are obtained from the speed profiles by numerical integration. (7) The generated trajectories are then rotated by means of a geometrical transformation to reproduce the point-to-point movements performed by post-stroke subjects during a turn in the InMotion2 coordinate frame system

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[Abstract] Constraining movement reveals motor capability in chronic stroke: An initial study

Abstract

Objective: To determine if persons with chronic stroke and decreased hip and knee flexion during swing can walk with improved swing-phase kinematics when the task demands constrained gait to the sagittal plane.

Design: A one-day, within-subject design comparing gait kinematics under two conditions: Unconstrained treadmill walking and a constrained condition in which the treadmill walking space is reduced to limit limb advancement to occur in the sagittal plane.

Setting: Outpatient physical therapy clinic.

Subjects: Eight individuals (mean age, 64.1 ±9.3, 2 F) with mild-moderate paresis were enrolled.

Main measures: Spatiotemporal gait characteristics and swing-phase hip and knee range of motion during unconstrained and constrained treadmill walking were compared using paired t-test and Cohen’s d (d) to determine effect size.

Results: There was a significant, moderate-to-large effect of the constraint on hip flexion (p < 0.001, d = –1.1) during initial swing, and hip (p < 0.05, d = –0.8) and knee (p < 0.001, d = –1.1) flexion during midswing. There was a moderate effect of constraint on terminal swing knee flexion (p = 0.238, d = –0.6). Immediate and significant changes in step width (p < 0.05, d = 0.9) and paretic step length (p < 0.05, d = –0.5) were noted in the constrained condition compared with unconstrained.

Conclusion: Constraining the treadmill walking path altered the gait patterns among the study’s participants. The immediate change during constrained walking suggests that patients with chronic stroke may have underlying movement capability that they do not preferentially utilize.

 

Source: Constraining movement reveals motor capability in chronic stroke: An initial study

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[Abstract] Design and Analysis of a Cable-Driven Articulated Rehabilitation System for Gait Training – ASME

Abstract

Assisted motor therapies play a critical role in enhancing functional musculoskeletal recovery and neurological rehabilitation. Our long term goal is to assist and automate the performance of repetitive motor-therapy of the human lower limbs. Hence, in this paper, we examine the viability of a light-weight and reconfigurable hybrid (articulated-multibody and cable) robotic system for assisting lower-extremity rehabilitation and analyze its performance. A hybrid cable-actuated articulated multibody system is formed when multiple cables are attached from a ground-frame to various locations on an articulated-linkage based orthosis. Our efforts initially focus on developing an analysis and simulation framework for the kinematics and dynamics of the cable-driven lower limb orthosis. A Monte Carlo approach is employed to select configuration parameters including cuff sizes, cuff locations, and the position of fixed winches. The desired motions for the rehabilitative exercises are prescribed based upon motion patterns from a normative subject cohort. We examine the viability of using two controllers — a joint-space feedback linearized PD controller and a task-space force-control strategy — to realize trajectory- and path- tracking of the desired motions within a simulation environment. In particular, we examine performance in terms of (i) coordinated control of the redundant system; (ii) reducing internal stresses within the lower-extremity joints; and (iii) continued satisfaction of the unilateral cable-tension constraints throughout the workspace.

Source: Article

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[BOOK] Control System Design for in Upper Limb Rehabilitation – Chris Freeman – Google Books

This book presents a comprehensive framework for model-based electrical stimulation (ES) controller design, covering the whole process needed to develop a system for helping people with physical impairments perform functional upper limb tasks such as eating, grasping and manipulating objects.

The book first demonstrates procedures for modelling and identifying biomechanical models of the response of ES, covering a wide variety of aspects including mechanical support structures, kinematics, electrode placement, tasks, and sensor locations. It then goes on to demonstrate how complex functional activities of daily living can be captured in the form of optimisation problems, and extends ES control design to address this case. It then lays out a design methodology, stability conditions, and robust performance criteria that enable control schemes to be developed systematically and transparently, ensuring that they can operate effectively in the presence of realistic modelling uncertainty, physiological variation and measurement noise.

 

Source: Control System Design for Electrical Stimulation in Upper Limb … – Chris Freeman – Βιβλία Google

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[ARTICLE] Kinematic analysis of upper limb motion: Feasibility, preliminary results in controls and hemiparetic subjects, prospects

Objectives

The aim of this study is to develop a valid and standardized instrumental analysis of upper limb (UL) motion in stroke patients.

Methods

Sixteen controls and 15 hemiparetic subjects (mean age = 54 ± 18,2 years old; Fugl-Meyer Upper Limb 41,4 ± 12,4) underwent kinematic motion analysis (passive markers, Optitrack) of pointing and grasping tasks. We examined the ability to perform a single pointing task and three reach-to-grasp tasks: key turning, reaching and grasping a can, reaching and grasping a cube; at a self-selected speed and as fast as possible. Speed, accuracy and efficiency of each movement were quantified and compared between controls and hemiparetic subjects, and between the ipsilateral of control subjects and the affected side; to describe reaching and grasping.

Results

For reaching, movement time of hemiparetic UL was longer, less smooth (peak velocity, jerk), less direct (higher index path ratio) and associated with more trunk compensation (higher trunk/hand ratio). Movement time, jerks and trunk/hand ratio were the most discriminant variables between hemiparetic UL and ipsilateral/control UL, in any task analysed. Trunk displacement was greater in grasping than in reaching tasks. For grapsing tasks, movement time is the most discriminant factor between hemiparetic and control/ipsilateral UL, especially for the key turn task. Movement alterations were also found for ipsilateral limb. Association between kinematic variables and clinical features during reaching time (Fugl-Meyer, MAL, WFMT, ARAT) was greater for the task “grasping a can”.

Discussion/conclusion

Our results are similar to those of the literature, but suggest that we have to privilege some of the most relevant kinematic parameters. This standardization phase emerging after a validation phase of the techniques can make the biomechanical analysis of the upper limb as easy and valid as gait analysis and should help to develop the quantified measurement of prehension. This protocol is currently in process to objectively assess the therapeutic effects of rehabilitation treatments (botulinum toxin, induced constraint therapy).

Source: Kinematic analysis of upper limb motion: Feasibility, preliminary results in controls and hemiparetic subjects, prospects

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[ARTICLE] Static and dynamic characterization of the LIGHTarm exoskeleton for rehabilitation

Abstract

This paper presents LIGHTarm, a passive gravity compensated exoskeleton for upper-limb rehabilitation suitable for the use both in the clinical environment and at home. Despite the low-cost and not actuated design, LIGHTarm aims at providing remarkable back-drivability in wide portions of the upper-limb workspace. The weight-support and back-drivability features are experimentally investigated on three healthy subjects through the analysis of the EMG activity recorded in static conditions and during functional movements. Kinematics is also monitored. Preliminary results suggest that LIGHTarm sharply reduces muscular effort required for limb support, quite uniformly in the workspace, and that remarkable back-drivability is achieved during the execution of functional movements.

Source: IEEE Xplore Abstract (Abstract) – Static and dynamic characterization of the LIGHTarm exoskeleton for rehabilitation

 

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