No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Hand movement parameters calculated by the LEAP based Virtual Glove
... and interpreted with the help of tracking systems [7]. Furthermore, these parameters can be also calculated for the healthy hand, for designing a useful standard, patient-specific, goal scale. ...
Telerehabilitation is important for post-stroke or post-surgery rehabilitation because the tasks it uses are reproducible. When combined with assistive technologies, such as robots, virtual reality, tracking systems, or a combination of them, it can also allow the recording of a patient’s progression and rehabilitation monitoring, along with an objective evaluation. In this paper, we present the structure, from actors and functionalities to software and hardware views, of a novel framework that allows cooperation between patients and therapists. The system uses a computer-vision-based system named virtual glove for real-time hand tracking (40 fps), which is translated into a light and precise system. The novelty of this work lies in the fact that it gives the therapist quantitative, not only qualitative, information about the hand’s mobility, for every hand joint separately, while at the same time providing control of the result of the rehabilitation by also quantitatively monitoring the progress of the hand mobility. Finally, it also offers a strategy for patient–therapist interaction and therapist–therapist data sharing.
... From the experimental results, Figures 14-16, the LMC can be used to track the ROM continuously and used in the development of serious games. In [34], the LMC was used to calculate and represent graphically static and dynamic hand parameters of the ROM in a healthy subject. In [35], the LMC was used to measure the wrist ROM compared to the goniometry obtained good results except for ulnar/radial deviation in healthy subjects. ...
The Leap Motion Controller (LMC) is a low-cost markerless optical sensor that performs measurements of various parameters of the hands that has been investigated for a wide range of different applications. Research attention still needs to focus on the evaluation of its precision and accuracy to fully understand its limitations and widen its range of applications. This paper presents the experimental validation of the LMC device to verify the feasibility of its use in assessing and tailoring wrist rehabilitation therapy for the treatment of physical disabilities through continuous exercises and integration with serious gaming environments. An experimental set up and analysis is proposed using an industrial robot as motion reference. The high repeatability of the selected robot is used for comparisons with the measurements obtained via a leap motion controller while performing the basic movements needed for rehabilitation exercises of the human wrist. Experimental tests are analyzed and discussed to demonstrate the feasibility of using the leap motion controller for wrist rehabilitation.
Hand rehabilitation is fundamental after stroke or surgery. Traditional rehabilitation requires a therapist and implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, can be really effective when used in virtual reality (VR) environments. Mechanical devices are often expensive, cumbersome, patient specific and hand specific, while tracking-based devices are not affected by these limitations but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper, the implementation of a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, is described. The VG is calibrated and static positioning measurements are compared with those collected with an accurate spatial positioning system. The positioning error is lower than 6 mm in a cylindrical region of interest of radius 10 cm and height 21 cm. Real-time hand tracking measurements are also performed, analysed and reported. Hand tracking measurements show that VG operated in real-time (60 fps), reduced occlusions, and managed two LEAP sensors correctly, without any temporal and spatial discontinuity when skipping from one sensor to the other. A video demonstrating the good performance of VG is also collected and presented in the Supplementary Materials. Results are promising but further work must be done to allow the calculation of the forces exerted by each finger when constrained by mechanical tools (e.g., peg-boards) and for reducing occlusions when grasping these tools. Although the VG is proposed for rehabilitation purposes, it could also be used for tele-operation of tools and robots, and for other VR applications.
Objective. In the last few years, the interest in applying virtual reality systems for neurorehabilitation is increasing. Their compatibility with neuroimaging techniques, such as functional near-infrared spectroscopy (fNIRS), allows for the investigation of brain reorganization with multimodal stimulation and real-time control of the changes occurring in brain activity. The present study was aimed at testing a novel semi-immersive visuo-motor task (VMT), which has the features of being adopted in the field of neurorehabilitation of the upper limb motor function. Approach. A virtual environment was simulated through a three-dimensional hand-sensing device (the LEAP Motion Controller), and the concomitant VMT-related prefrontal cortex (PFC) response was monitored non-invasively by fNIRS. Upon the VMT, performed at three different levels of difficulty, it was hypothesized that the PFC would be activated with an expected greater level of activation in the ventrolateral PFC (VLPFC), given its involvement in the motor action planning and in the allocation of the attentional resources to generate goals from current contexts. Twenty-one subjects were asked to move their right hand/forearm with the purpose of guiding a virtual sphere over a virtual path. A twenty-channel fNIRS system was employed for measuring changes in PFC oxygenated–deoxygenated hemoglobin (O2Hb/HHb, respectively). Main results. A VLPFC O2Hb increase and a concomitant HHb decrease were observed during the VMT performance, without any difference in relation to the task difficulty. Significance. The present study has revealed a particular involvement of the VLPFC in the execution of the novel proposed semi-immersive VMT adoptable in the neurorehabilitation field.
Functional near-infrared spectroscopy (fNIRS) is a non-invasive vascular-based functional neuroimaging technology that can assess, simultaneously from multiple cortical areas, concentration changes in oxygenated-deoxygenated hemoglobin at the level of the cortical microcirculation blood vessels. fNIRS, with its high degree of ecological validity and its very limited requirement of physical constraints to subjects, could represent a valid tool for monitoring cortical responses in the research field of neuroergonomics. In virtual reality (VR) real situations can be replicated with greater control than those obtainable in the real world. Therefore, VR is the ideal setting where studies about neuroergonomics applications can be performed. The aim of the present study was to investigate, by a 20-channel fNIRS system, the dorsolateral/ventrolateral prefrontal cortex (DLPFC/VLPFC) in subjects while performing a demanding VR hand-controlled task (HCT). Considering the complexity of the HCT, its execution should require the attentional resources allocation and the integration of different executive functions. The HCT simulates the interaction with a real, remotely-driven, system operating in a critical environment. The hand movements were captured by a high spatial and temporal resolution 3-dimensional (3D) hand-sensing device, the LEAP motion controller, a gesture-based control interface that could be used in VR for tele-operated applications. Fifteen University students were asked to guide, with their right hand/forearm, a virtual ball (VB) over a virtual route (VROU) reproducing a 42 m narrow road including some critical points. The subjects tried to travel as long as possible without making VB fall. The distance traveled by the guided VB was 70.2 ± 37.2 m. The less skilled subjects failed several times in guiding the VB over the VROU. Nevertheless, a bilateral VLPFC activation, in response to the HCT execution, was observed in all the subjects. No correlation was found between the distance traveled by the guided VB and the corresponding cortical activation. These results confirm the suitability of fNIRS technology to objectively evaluate cortical hemodynamic changes occurring in VR environments. Future studies could give a contribution to a better understanding of the cognitive mechanisms underlying human performance either in expert or non-expert operators during the simulation of different demanding/fatiguing activities.
This paper presents a Fitts' law-based analysis of the user's performance in selection tasks with the Leap Motion Controller compared with a standard mouse device. The Leap Motion Controller (LMC) is a new contact-free input system for gesture-based human-computer interaction with declared sub-millimeter accuracy. Up to this point, there has hardly been any systematic evaluation of this new system available. With an error rate of 7.8 % for the LMC and 2.8% for the mouse device, movement times twice as large as for a mouse device and high overall effort ratings, the Leap Motion Controller's performance as an input device for everyday generic computer pointing tasks is rather limited, at least with regard to the selection recognition provided by the LMC.
We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system. A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations. For the static measurements, a plastic arm model simulating a human arm was used. A set of 37 reference locations was selected to cover the controller's sensory space. For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers. In the static scenario, the standard deviation was less than 0.5 mm. The linear correlation revealed a significant increase in the standard deviation when moving away from the controller. The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controller's surface. The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system.
The Leap Motion Controller is a new device for hand gesture controlled user interfaces with declared sub-millimeter accuracy. However, up to this point its capabilities in real environments have not been analyzed. Therefore, this paper presents a first study of a Leap Motion Controller. The main focus of attention is on the evaluation of the accuracy and repeatability. For an appropriate evaluation, a novel experimental setup was developed making use of an industrial robot with a reference pen allowing a position accuracy of 0.2 mm. Thereby, a deviation between a desired 3D position and the average measured positions below 0.2 mm has been obtained for static setups and of 1.2 mm for dynamic setups. Using the conclusion of this analysis can improve the development of applications for the Leap Motion controller in the field of Human-Computer Interaction.
Hand gestures recognition (HGR) is one of the main areas of research for the engineers, scientists and bioinformatics. HGR is the natural way of Human Machine interaction and today many researchers in the academia and industry are working on different application to make interactions more easy, natural and convenient without wearing any extra device. HGR can be applied from games control to vision enabled robot control, from virtual reality to smart home systems. In this paper we are discussing work done in the area of hand gesture recognition where focus is on the intelligent approaches including soft computing based methods like artificial neural network, fuzzy logic, genetic algorithms etc. The methods in the preprocessing of image for segmentation and hand image construction also taken into study. Most researchers used fingertips for hand detection in appearance based modeling. Finally the comparison of results given by different researchers is also presented.
Robotic systems that are interfaced with virtual reality gaming and task simulations are increasingly being developed to provide repetitive intensive practice to promote increased compliance and facilitate better outcomes in rehabilitation post-stroke. A major development in the use of virtual environments (VEs) has been to incorporate tactile information and interaction forces into what was previously an essentially visual experience. Robots of varying complexity are being interfaced with more traditional virtual presentations to provide haptic feedback that enriches the sensory experience and adds physical task parameters. This provides forces that produce biomechanical and neuromuscular interactions with the VE that approximate real-world movement more accurately than visual-only VEs, simulating the weight and force found in upper extremity tasks. The purpose of this article is to present an overview of several systems that are commercially available for ambulation training and for training movement of the upper extremity. We will also report on the system that we have developed (NJIT-RAVR system) that incorporates motivating and challenging haptic feedback effects into VE simulations to facilitate motor recovery of the upper extremity post-stroke. The NJIT-RAVR system trains both the upper arm and the hand. The robotic arm acts as an interface between the participants and the VEs, enabling multiplanar movements against gravity in a three-dimensional workspace. The ultimate question is whether this medium can provide a motivating, challenging, gaming experience with dramatically decreased physical difficulty levels, which would allow for participation by an obese person and facilitate greater adherence to exercise regimes.
Hand gestures recognition (HGR) is one of the main areas of research for the engineers,scientists and bioinformatics. HGR is the natural way of Human Machine interaction and today manyresearchers in the academia and industry are working on different application to make interactions moreeasy, natural and convenient without wearing any extra device. HGR can be applied from games controlto vision enabled robot control, from virtual reality to smart home systems. In this paper we arediscussing work done in the area of hand gesture recognition where focus is on the intelligentapproaches including soft computing based methods like artificial neural network, fuzzy logic, geneticalgorithms etc. The methods in the preprocessing of image for segmentation and hand imageconstruction also taken into study. Most researchers used fingertips for hand detection in appearancebased modeling. Finally the comparison of results given by different researchers is also presented.
For over 25 years, personal assistant robots for severely disabled individuals have been in development. More recently, using robots to deliver rehabilitation therapy has been proposed. This paper summarizes the development and clinical testing of three mechatronic systems for post-stroke therapy conducted at the VA Palo Alto in collaboration with Stanford University. We describe the philosophy and experiences that guided their evolution. Unique to the Palo Alto approach is provision for bimanual, mirror-image, patient-controlled therapeutic exercise. Proof-of-concept was established with a 2-degree-of-freedom (DOF) elbow/forearm manipulator. Tests of a second-generation therapy robot producing planar forearm movements in 19 hemiplegic and control subjects confirmed the validity and reliability of interaction forces during mechanically assisted upper-limb movements. Clinical trials comparing 3-D robot-assisted therapy to traditional therapy in 21 chronic stroke subjects showed significant improvement in the Fugl-Meyer (FM) measure of motor recovery in the robot group, which exceeded improvements in the control group.
Hand rehabilitation, following stroke or hand surgery, is repetitive and long duration and can be facilitated with the assistance of complex, heavy and cumbersome haptic gloves based on sensors. The present paper describes a virtual glove, software based, which tracks hand movements by using images collected from webcams and numerical analysis. Finger forces are calculated from the deformations impressed to some objects (of known elastic coefficient) grasped by the patient hand. The presented system is notable for simplicity, generality and low cost. Implementation and results of the proposed virtual glove will be the objects of a future paper.
Robot-assisted movement training improves arm movement ability following acute and chronic stroke. Such training involves two interacting processes: the patient trying to move and the robot applying forces to the patient's arm. A fundamental principle of motor learning is that movement practice improves motor function; the role of applied robotic forces in improving motor function is still unclear. This article reviews our work addressing this question. Our pilot study using the Assisted Rehabilitation and Measurement (ARM) Guide, a linear robotic trainer, found that mechanically assisted reaching improved motor recovery similar to unassisted reaching practice. This finding is inconclusive because of the small sample size (n = 19), but suggest that future studies should carefully control the amount of voluntary movement practice delivered to justify the use of robotic forces. We are optimistic that robotic forces will ultimately show additional therapeutic benefits when coupled with movement practice. We justify this optimism here by comparing results from the ARM Guide and the Mirror Image Movement Enabler robotic trainer. This comparison suggests that requiring a patient to generate specific patterns of force before allowing movement is more effective than mechanically completing movements for the patient. We describe the engineering implementation of this "guided-force training" algorithm.
Postural stability is often compromised in many pathological states and decreases with age. In clinical practice, an objective tool for balance is fundamental. Recently, virtual tools, based on the use of depth cameras, have been presented. In this paper, a new virtual system for postural stability assessment was presented, involving the use of a Time of Flight camera (TOF) and of a mirror for the reduction of the occlusions errors by allowing the camera to see the hidden body surface. The validity of the tool was assessed through some experimental results. Data were also compared with those measured by a physical force platform and those calculated with another virtual stability assessment system, in order to highlight the error reduction while maintaining simplicity and low-cost.
Purpose
– The Leap Motion represents a new generation of depth sensing cameras designed for close range tracking of hands and fingers, operating with minimal latency and high spatial precision (0.01 mm). The purpose of this paper is to develop virtual reality (VR) simulations of three well-known hand-based rehabilitation tasks using a commercial game engine and utilising a Leap camera as the primary mode of interaction. The authors present results from an initial evaluation by professional clinicians of these VR simulations for use in their hand and finger physical therapy practice.
Design/methodology/approach
– A cross-disciplinary team of researchers collaborated with a local software company to create three dimension interactive simulations of three hand focused rehabilitation tasks: Cotton Balls, Stacking Blocks, and the Nine Hole Peg Test. These simulations were presented to a group of eight physiotherapists and occupational therapists (n=8) based in the Regional Acquired Brain Injury Unit, Belfast Health, and Social Care Trust for evaluation. After induction, the clinicians attempted the tasks presented and provided feedback by filling out a questionnaire.
Findings
– Results from questionnaires (using a Likert scale 1-7, where 1 was the most favourable response) revealed a positive response to the simulations with an overall mean score across all questions equal to 2.59. Clinicians indicated that the system contained tasks that were easy to understand (mean score 1.88), and though it took several attempts to become competent, they predicted that they would improve with practice (mean score 2.25). In general, clinicians thought the prototypes provided a good illustration of the tasks required in their practice (mean score 2.38) and that patients would likely be motivated to use the system (mean score 2.38), especially young patients (mean score 1.63), and in the home environment (mean score 2.5).
Originality/value
– Cameras offer an unobtrusive and low maintenance approach to tracking user motion in VR therapy in comparison to methods based on wearable technologies. This paper presents positive results from an evaluation of the new Leap Motion camera for input control of VR simulations or games. This mode of interaction provides a low cost, easy to use, high-resolution system for tracking fingers and hands, and has great potential for home-based physical therapies, particularly for young people.
First, to evaluate the clinical effectiveness of a virtual reality-based telerehabilitation program in the balance recovery of hemiparetic individuals post-stroke in comparison to an in-clinic program; second, to compare the subjective experiences; and finally, to contrast the costs.
Single-blind randomized controlled trial.
Neurorehabilitation unit.
Chronic outpatients with stroke (N=30) with residual hemiparesis.
Twenty 45-minute training sessions with the telerehabilitation system, administered three times a week, in the clinic or in home.
First, Berg Balance Scale for balance assessment. Balance and gait subscales of the Performance-Oriented Mobility Assessment, and the Brunel Balance Assessment were secondary outcomes. Clinical assessments were conducted at baseline, 8 weeks (post treatment), and 12 weeks (follow-up); Second, the System Usability Scale and the Intrinsic Motivation Inventory for subjective experiences; Finally, expenses in dollars for cost.
Significant improvement in both groups from the initial to the final assessment in the Berg Balance Scale (p=0.001, η(2)p =0.68), in the balance (p=0.006, η(2)p =0.24) and gait subscales (p=0.001, η(2)p =0.57) of the Tinetti Performance-Oriented Mobility Assessment, and in the Brunel Balance Assessment (x(2)=15.0' p=0.002; x(2)=21.9 p=0.001). No significant differences between groups in any balance scale, nor in the feedback questionnaires. With regards to subjective experiences, both groups considered the VR system similarly usable and motivating. The in-clinic intervention resulted in more expenses than the telerehabilitation program (654.72 $ per person).
First, virtual reality-based telerehabilitation interventions can promote the reacquisition of locomotor skills associated with balance in a similar way that in-clinic interventions, both complemented with a conventional therapy program; second, the usability and the motivation of both interventions can be similar; and finally, the telerehabilitation interventions can involve savings that vary depending on each particular scenario.
Copyright © 2014 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
Background and objective:
The degeneration of the balance control system in the elderly and in many pathologies requires measuring the equilibrium conditions very often. In clinical practice, equilibrium control is commonly evaluated by using a force platform (stabilometric platform) in a clinical environment. In this paper, we demonstrate how a simple movement analysis system, based on a 3D video camera and a 3D real time model reconstruction of the human body, can be used to collect information usually recorded by a physical stabilometric platform.
Methods:
The algorithm used to reconstruct the human body model as a set of spheres is described and discussed. Moreover, experimental measurements and comparisons with data collected by a physical stabilometric platform are also reported. The measurements were collected on a set of 6 healthy subjects to whom a change in equilibrium condition was stimulated by performing an equilibrium task.
Results:
The experimental results showed that more than 95% of data collected by the proposed method were not significantly different from those collected by the classic platform, thus confirming the usefulness of the proposed system.
Conclusions:
The proposed virtual balance assessment system can be implemented at low cost (about 500 and requires periodical calibration. The proposed system does not require periodical calibration, as is necessary for stabilometric force platforms, and it is easy to use. In future, the proposed system with little integration can be used, besides being an emulator of a stabilometric platform, also to recognize and track, in real time, head, legs, arms and trunk, that is to collect information actually obtained by sophisticated optoelectronic systems.
Recent work on the role of knowledge of results (KR) in motor learning has challenged some traditional assumptions. In particular, the guidance hypothesis suggests that there is a detriment to learning when KR guides the learner toward correct performance. Three experiments that explored this hypothesis are reported here. These experiments contrasted the effects of relative frequency of guidance versus the relative frequency of KR. According to the guidance hypothesis, it was predicted that parallel effects of the relative frequency manipulation on motor learning and performance would result under guided and KR conditions. The movement task was a reciprocal timing task that was either paced by a metronome (Experiment 1) or augmented by auditory KR (Experiments 2 and 3). The results of Experiments 1 and 3 revealed a number of parallel effects, thus providing support for the guidance hypothesis. The contrast of Experiments 1 and 2 resulted in a number of dissociable effects, however. These findings are discussed in relation to the potential guiding properties of KR and their impact on motor performance and learning.
Post-stroke patients and people suffering from hand diseases often need rehabilitation therapy. The recovery of original skills, when possible, is closely related to the frequency, quality, and duration of rehabilitative therapy. Rehabilitation gloves are tools used both to facilitate rehabilitation and to control improvements by an evaluation system. Mechanical gloves have high cost, are often cumbersome, are not re-usable and, hence, not usable with the healthy hand to collect patient-specific hand mobility information to which rehabilitation should tend. The approach we propose is the virtual glove, a system that, unlike tools based on mechanical haptic interfaces, uses a set of video cameras surrounding the patient hand to collect a set of synchronized videos used to track hand movements. The hand tracking is associated with a numerical hand model that is used to calculate physical, geometrical and mechanical parameters, and to implement some boundary constraints such as joint dimensions, shape, joint angles, and so on. Besides being accurate, the proposed system is aimed to be low cost, not bulky (touch-less), easy to use, and re-usable. Previous works described the virtual glove general concepts, the hand model, and its characterization including system calibration strategy. The present paper provides the virtual glove overall design, both in real-time and in off-line modalities. In particular, the real-time modality is described and implemented and a marker-based hand tracking algorithm, including a marker positioning, coloring, labeling, detection and classification strategy, is presented for the off-line modality. Moreover, model based hand tracking experimental measurements are reported, discussed and compared with the corresponding poses of the real hand. An error estimation strategy is also presented and used for the collected measurements. System limitations and future work for system improvement are also discussed.
Objective:
To investigate the influence of different design characteristics of virtual reality exercises on engagement during lower extremity motor rehabilitation.
Design:
Correlational study.
Setting:
Spinal cord injury (SCI) rehabilitation center.
Participants:
Subjects with SCI (n=12) and control subjects (n=10).
Interventions:
Not applicable.
Main outcome measures:
Heart rate and electromyographic activity from both legs at the tibialis anterior, the gastrocnemius medialis, the rectus femoris, and the biceps femoris were recorded.
Results:
Interactivity (ie, functionally meaningful reactions to motor performance) was crucial for the engagement of subjects. No significant differences in engagement were found between exercises that differed in feedback frequency, explicit task goals, or aspects of competition.
Conclusions:
Functional feedback is highly important for the active participation of patients during robotic-assisted rehabilitation. Further investigations on the design characteristics of virtual reality exercises are of great importance. Exercises should thoroughly be analyzed regarding their effectiveness, while user preferences and expectations should be considered when designing virtual reality exercises for everyday clinical motor rehabilitation.
Rehabilitation is often required after stroke, surgery, or degenerative diseases. It has to be specific for each patient and can be easily calibrated if assisted by human-computer interfaces and virtual reality. Recognition and tracking of different human body landmarks represent the basic features for the design of the next generation of human-computer interfaces. The most advanced systems for capturing human gestures are focused on vision-based techniques which, on the one hand, may require compromises from real-time and spatial precision and, on the other hand, ensure natural interaction experience. The integration of vision-based interfaces with thematic virtual environments encourages the development of novel applications and services regarding rehabilitation activities. The algorithmic processes involved during gesture recognition activity, as well as the characteristics of the virtual environments, can be developed with different levels of accuracy. This paper describes the architectural aspects of a framework supporting real-time vision-based gesture recognition and virtual environments for fast prototyping of customized exercises for rehabilitation purposes. The goal is to provide the therapist with a tool for fast implementation and modification of specific rehabilitation exercises for specific patients, during functional recovery. Pilot examples of designed applications and preliminary system evaluation are reported and discussed.
The paper proposes a new methodology to interactively simulate grasping of virtual product prototypes with the goal to evaluate the contact forces between the grasping hand and product as well as the load on the human arm. Interaction between product concepts and the users happens in a virtual environment, in which the user controls a virtual hand interactively. The contact between the virtual hand and the grasped product is simulated and visual feedback is provided to the user. Controlling the virtual hand interactively in real time holds many challenges. One of the challenges is mapping the motion of the user to contact forces, which then results in stable grasping of objects. In this paper we present a new methodology to convert and map the measured position of the real hand into contact forces so that the contact between the virtual hand and the object remains stable. Our approach applies a multi-objective optimization that takes into account the posture and anthropometric properties of grasping hand, as well as the penetration of the hand in the grasped virtual object in order to find the optimal arrangement of contact forces. The paper reports on the principle of our grasping control methodology as well as presents some test cases to show the advantages and disadvantages of the proposed approach.
Hand rehabilitation, following stroke or hand surgery, is a repetitive and long duration therapy that can be facilitated with the assistance of gloves based on sensors. These devices can be substituted by a simple and inexpensive system based on the images acquired by 4 cameras and numerical analysis. In this paper we present a numerical hand model used in this system which describes the kinematic of the hand. Preliminary experimental data to test the proposed model have also been reported.
Hand rehabilitation, is a repetitive and long duration therapy that can be facilitated with the assistance of gloves based
on sensors. These devices can be substituted by the Virtual Glove, a simple and low-cost system based on the images acquired
by four cameras and numerical analysis. In this paper the implementation of the numerical hand model used in this system has
been characterized in term of errors in joints position calculation and inverse kinematics. The first preliminary experimental
data to test the proposed model have also been reported.
This paper describes a general purpose, representation independent
method for the accurate and computationally efficient registration of
3-D shapes including free-form curves and surfaces. The method handles
the full six-degrees of freedom and is based on the iterative closest
point (ICP) algorithm, which requires only a procedure to find the
closest point on a geometric entity to a given point. The ICP algorithm
always converges monotonically to the nearest local minimum of a
mean-square distance metric, and experience shows that the rate of
convergence is rapid during the first few iterations. Therefore, given
an adequate set of initial rotations and translations for a particular
class of objects with a certain level of 'shape complexity', one can
globally minimize the mean-square distance metric over all six degrees
of freedom by testing each initial registration. For examples, a given
'model' shape and a sensed 'data' shape that represents a major portion
of the model shape can be registered in minutes by testing one initial
translation and a relatively small set of rotations to allow for the
given level of model complexity. One important application of this
method is to register sensed data from unfixtured rigid objects with an
ideal geometric model prior to shape inspection. The described method is
also useful for deciding fundamental issues such as the congruence
(shape equivalence) of different geometric representations as well as
for estimating the motion between point sets where the correspondences
are not known. Experimental results show the capabilities of the
registration algorithm on point sets, curves, and surfaces.
This paper is a review conducted to provide an overview of accumulated evidence on contemporary rehabilitation methods for stroke survivors. Loss of functional movement is a common consequence of stroke for which a wide range of interventions has been developed. Traditional therapeutic approaches have shown limited results for motor deficits as well as lack evidence for their effectiveness. Stroke rehabilitation is now based on the evidence of neuroplasticity, which is responsible for recovery following stroke. The neuroplastic changes in the structure and function of relevant brain areas are induced primarily by specific rehabilitation methods. The therapeutic method which induces neuroplastic changes, leads to greater motor and functional recovery than traditional methods. Further, the recovery is permanent in nature. During the last decade various novel stroke rehabilitative methods for motor recovery have been developed. This review focuses on the methods that have evidence of associated cortical level reorganization, namely task-specific training, constraint-induced movement therapy, robotic training, mental imaging, and virtual training. All of these methods utilize principles of motor learning. The findings from this review demonstrated convincing evidence both at the neural and functional level in response to such therapies. The main aim of the review was to determine the evidence for these methods and their application into clinical practice.
Many diseases and injuries can impair joint mobility. Normal reference values are needed to determine extent of impairment to assess and monitor joint motion. There is very little published data describing normal joint range of motion (ROM) for healthy men and women across a wide span of ages. We enrolled male and female subjects aged between 2 and 69 years who were free from conditions that could potentially limit joint mobility for the study. Nine licensed physical therapists used universal goniometers to determine passive joint motion bilaterally of elbow flexion, extension, supination and pronation, shoulder flexion, hip flexion and extension, knee flexion and extension, and ankle dorsiflexion and plantarflexion. Descriptive statistics were calculated for male and female subjects in four age groups: 2-8, 9-19, 20-44 and 45-69 years. Joint ROM measurements were obtained on a total of 674 (53.6% female) healthy, normal subjects aged 2-69 years. Female subjects had greater joint mobility in all age groups in nearly all joints and the gender difference was most obvious in measures of ankle plantarflexion, elbow pronation and supination. Range of motion average values for all joints decreased with advancing age for both men and women and, in most cases, were significantly different than most commonly used normative values. Our study of ROM measurements taken by trained physical therapists on a large sample of healthy individuals revealed significant gender- and age-related variation that may be an important consideration in patient assessment.
Little research has been conducted on aging and the learning of motor skills. In this study, we examined the effects of different schedules of knowledge of results (KR) on the acquisition and retention of a movement timing task by young adults (20-23 years) and older adults (60-82 years). The results indicated that there were differences between young and older adults in the accuracy and consistency of motor performance when KR was provided. Accuracy effects persisted during a retention interval when KR was no longer provided, although there were no differences in variability. There were no interactions of age with any of the KR-related variables. These findings suggest that the ability to process KR, and the effects of KR on motor learning, are similar in young and older adults. These findings are discussed in terms of age-related issues in movement control and learning processes.
Neuroplasticity might play a beneficial role in the recovery of function after stroke but empirical evidence for this is lacking thus far. Constraint-induced (CI) therapy was used to increase the use of a paretic upper extremity in four hemiparetic stroke patients. Dipole modeling of steady-state movement-related cortical potentials was applied before and after training and 3 months later. The source locations associated with affected hand movement were unusual at follow-up because activation of the ipsilateral hemisphere was found in the absence of mirror movements of the unaffected hand. This long-term change may be considered as an initial demonstration of large-scale neuroplasticity associated with increased use of the paretic limb after application of CI therapy.
Forty adults, post-stroke from anterior circulation unilateral cerebrovascular accident (approximately 2 years post onset) and 40 age-matched controls (M = 57 years) practiced a rapid, spatially and temporally constrained programmed action under one of two augmented feedback practice conditions. Participants in the stroke group used the upper limb ipsilateral to the lesion. After an extended practice period (198 trials), acquisition, retention, and reacquisition performance was assessed for accuracy and consistency and compared over trials, between groups and feedback conditions. Both stroke and control groups demonstrated significant improvement in accuracy and consistency over practice with relative persistence of these changes during retention. There were no differences between groups (stroke vs control) in performance patterns across trials for acquisition, retention, or reacquisition phases. In addition, there were no differential effects of the two augmented feedback conditions on performance and no interactions of feedback condition with group. However, independent of feedback condition, the stroke group performed with more error than did the control group during all experimental phases (i.e., acquisition, retention, reacquisition). These results suggest that unilateral stroke-related damage in the sensorimotor areas primarily effects the processes underlying the control and execution of motor skills but not the learning of those skills. Implications of these findings for physical rehabilitation are discussed.
Injury-induced cortical reorganization is a widely recognized phenomenon. In contrast, there is almost no information on treatment-induced plastic changes in the human brain. The aim of the present study was to evaluate reorganization in the motor cortex of stroke patients that was induced with an efficacious rehabilitation treatment.
We used focal transcranial magnetic stimulation to map the cortical motor output area of a hand muscle on both sides in 13 stroke patients in the chronic stage of their illness before and after a 12-day-period of constraint-induced movement therapy.
Before treatment, the cortical representation area of the affected hand muscle was significantly smaller than the contralateral side. After treatment, the muscle output area size in the affected hemisphere was significantly enlarged, corresponding to a greatly improved motor performance of the paretic limb. Shifts of the center of the output map in the affected hemisphere suggested the recruitment of adjacent brain areas. In follow-up examinations up to 6 months after treatment, motor performance remained at a high level, whereas the cortical area sizes in the 2 hemispheres became almost identical, representing a return of the balance of excitability between the 2 hemispheres toward a normal condition.
This is the first demonstration in humans of a long-term alteration in brain function associated with a therapy-induced improvement in the rehabilitation of movement after neurological injury.
By a variety of mechanisms, the human brain is constantly undergoing plastic changes. Plasticity can be studied with phenomena such as peripheral deafferentation and motor learning. Spontaneous recovery from stroke in the chronic stag likely comes about because of plasticity, and the best recovery seems to result from reorganization in the damaged hemisphere. Knowledge about the physiology of brain plasticity has led to the development of new techniques for rehabilitation. Published by Elsevier Science BY.
The regional specificity and functional significance of learning-dependent synaptogenesis within physiologically defined regions of the adult motor cortex are described. In comparison to rats in a motor activity control group, rats trained on a skilled reaching task exhibited an areal expansion of wrist and digit movement representations within the motor cortex. No expansion of hindlimb representations was seen. This functional reorganization was restricted to the caudal forelimb area, as no differences in the topography of movement representations were observed within the rostral forelimb area. Paralleling the physiological changes, trained animals also had significantly more synapses per neuron than controls within layer V of the caudal forelimb area. No differences in the number of synapses per neuron were found in either the rostral forelimb or hindlimb areas. This is the first demonstration of the co-occurrence of functional and structural plasticity within the same cortical regions and provides strong evidence that synapse formation may play a role in supporting learning-dependent changes in cortical function.
Recent work on the role of knowledge of results (KR) in motor learning has challenged some traditional assumptions. In particular, the guidance hypothesis suggests that there is a detriment to learning when KR guides the learner toward correct performance. Three experiments that explored this hypothesis are reported here. These experiments contrasted the effects of relative frequency of guidance versus the relative frequency of KR. According to the guidance hypothesis, it was predicted that parallel effects of the relative frequency manipulation on motor learning and performance would result under guided and KR conditions. The movement task was a reciprocal timing task that was either paced by a metronome (Experiment 1) or augmented by auditory KR (Experiments 2 and 3). The results of Experiments 1 and 3 revealed a number of parallel effects, thus providing support for the guidance hypothesis. The contrast of Experiments 1 and 2 resulted in a number of dissociable effects, however. These findings are discussed in relation to the potential guiding properties of KR and their impact on motor performance and learning.
Assumptions underlying physical therapy intervention: theoretical and historical perspectives
- gordon
J. Gordon, "Assumptions underlying physical therapy intervention:
theoretical and historical perspectives," In: Movement science:
foundations for physical therapy in rehabilitation. Rockville: Aspen
Publishers, pp. 1-31; 2000.
Motor control and learning: a behavioral emphasis
- scmidt