Posts Tagged Training

[Abstract] EEG-guided robotic mirror therapy system for lower limb rehabilitation – IEEE Conference Publication

Abstract:

Lower extremity function recovery is one of the most important goals in stroke rehabilitation. Many paradigms and technologies have been introduced for the lower limb rehabilitation over the past decades, but their outcomes indicate a need to develop a complementary approach. One attempt to accomplish a better functional recovery is to combine bottom-up and top-down approaches by means of brain-computer interfaces (BCIs). In this study, a BCI-controlled robotic mirror therapy system is proposed for lower limb recovery following stroke. An experimental paradigm including four states is introduced to combine robotic training (bottom-up) and mirror therapy (top-down) approaches. A BCI system is presented to classify the electroencephalography (EEG) evidence. In addition, a probabilistic model is presented to assist patients in transition across the experiment states based on their intent. To demonstrate the feasibility of the system, both offline and online analyses are performed for five healthy subjects. The experiment results show a promising performance for the system, with average accuracy of 94% in offline and 75% in online sessions.

Source: EEG-guided robotic mirror therapy system for lower limb rehabilitation – IEEE Conference Publication

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[BLOG POST] Strength training improves the nervous system’s ability to drive muscles

Imagine that the New Year has just begun. You’ve made a resolution to improve your physical fitness. In particular, you want to improve your muscle strength. You’ve heard that people with stronger muscles live longer and have less difficulty standing, walking, and using the toilet when they get older (Rantanen et al. 1999; Ruiz et al. 2008). So, you join a fitness centre and hire a personal trainer. The trainer assesses your maximal strength, and then guides you through a 4-week program that involves lifting weights which are about 80% of your maximum.

Sure enough, after the program, you become stronger (probably around 20% stronger) (Carroll et al. 2011). You think this is great – and it is! You are so excited, you decide to stand in front of your mirror, flex your biceps, and take a selfie (your plan is to post the picture to Facebook to show your friends how much bigger your muscles got). However, after examining the picture, you realise your muscles did not get bigger. Or perhaps they did get a little bigger, but not enough to explain your substantial improvement in strength. You are somewhat disappointed in this, but then you remember your goal was to get stronger, not necessarily bigger, so you post the picture, anyway.

Magnetic stimulation of the brain can be used to test how well a person can voluntarily drive their muscles.

Interestingly, the observations you made are completely consistent with the scientific literature. Within the first weeks of strength training, muscle strength can improve without a change in the size or architecture of the muscle (e.g., Blazevich et al. 2007). Consequently, researchers have speculated that initial improvements in muscle strength from strength training are due primarily to changes in the central nervous system. One hypothesis has been that strength training helps the nervous system learn how to better “drive” or communicate with muscles. This ability is termed voluntary activation, and it can be tested by stimulating the motor area of an individual’s brain while they perform a maximal contraction (Todd et al. 2003). If the stimulation produces extra muscle force, it means that the individual’s nervous system was not maximally activating their muscles. Currently, there is no consensus as to whether voluntary activation can actually be improved by strength training.

Therefore, we conducted a randomised, controlled trial in which one group of participants completed four weeks of strength training, while a control group did not complete the training (Nuzzo et al. in press). For the group who performed the training, each exercise session consisted of four sets of strong contractions of the elbow flexor muscles (i.e., the muscles that bend the elbow, such as the biceps). Before and after the four week intervention, both groups were tested for muscle strength, voluntary activation, and several other measures. The participants were healthy, university-aged, and they had limited or no experience with strength training.

WHAT DID WE FIND?

Prior to the intervention, the strength training and control groups had similar levels of muscle strength and activation of the elbow flexor muscles. After the intervention, the group who performed the strength training improved their strength by 13%. They also improved their voluntary activation from 88.7% to 93.4%. The control group did not improve muscle strength or voluntary activation.

SIGNIFICANCE AND IMPLICATIONS

The results from our study show that four weeks of strength training improves the brain’s ability to “drive” the elbow flexor muscles to produce their maximal force. This helps to explain how muscles can become stronger, without a change in muscle size or architecture. Moreover, the results suggest that clinicians should consider strength training as a treatment for patients with motor impairments (e.g., stroke), as these individuals are likely to have poor voluntary activation (Bowden et al. 2014).

PUBLICATION

Nuzzo JL, Barry BK, Jones MD, Gandevia SC, Taylor JL. Effects of four weeks of strength training on the corticomotoneuronal pathway. Med Sci Sports Exerc,  doi: 10.1249/MSS.0000000000001367.

KEY REFERENCES

Blazevich AJ, Gill ND, Deans N, Zhou S. Lack of human muscle architectural adaptation after short-term strength training. Muscle Nerve 35: 78-86.

Bowden JL, Taylor JL, McNulty PA. Voluntary activation is reduced in both the more- and less-affected upper limbs after unilateral stroke.Front Neurol 5: 239, 2014.

Carroll TJ, Selvanayagam VS, Riek S, Semmler RG. Neural adaptations to strength training: moving beyond transcranial magnetic stimulation and reflex studies. Acta Physiol 202: 119-140, 2011.

Rantanen T, Guralnik JM, Foley D, Masaki K, Leveille S, Curb JD, White L. Midline hand grip strength as a predictor of old age disability.JAMA 281: 558-560, 1999.

Ruiz JR, Sui X, Lobelo F, Morrow Jr. JR, Jackson AW, Sjöström M, Blair SN. Association between muscular strength and mortality in men: prospective cohort study. BMJ 337: a439, 2008.

Todd G, Taylor JL, Gandevia SC. Measurement of voluntary activation of fresh and fatigued human muscles using transcranial magnetic stimulation. J Physiol 555: 661-671, 2003.

AUTHOR BIO

Jim Nuzzo is a Postdoctoral Fellow at Neuroscience Research Australia (NeuRA). His research investigates how strength training alters the neural connections between the brain and muscles. Click here to read Jim’s other blogs.

Source: Strength training improves the nervous system’s ability to drive muscles – Motor Impairment

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[Abstract] Robot-assisted arm training in physical and virtual environments: A case study of long-term chronic stroke

Abstract:

Robot-assisted training (RT) is a novel technique with promising results for stroke rehabilitation. However, benefits of RT on individuals with long-term chronic stroke have not been well studied. For this case study, we developed an arm-based RT protocol for reaching practice in physical and virtual environments and tracked the outcomes in an individual with a long-term chronic stroke (20+ years) over 10 half-hour sessions. We analyzed the performance of the reaching movement with kinematic measures and the arm motor function using the Fugl-Meyer Assessment-Upper Extremity scale (FMA-UE). The results showed significant improvements in the subject’s reaching performance accompanied by a small increase in FMA-UE score from 18 to 21. The improvements were also transferred into real life activities, as reported by the subject. This case study shows that even in long-term chronic stroke, improvements in motor function are still possible with RT, while the underlying mechanisms of motor learning capacity or neuroplastic changes need to be further investigated.

Source: Robot-assisted arm training in physical and virtual environments: A case study of long-term chronic stroke – IEEE Xplore Document

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[Abstract] Virtual reality and non-invasive brain stimulation in stroke: How effective is their combination for upper limb motor improvement?

Abstract:

Upper limb (UL) hemiparesis is frequently a disabling consequence of stroke. The ability to improve UL functioning is associated with motor relearning and experience dependent neuroplasticity. Interventions such as non-invasive brain stimulation (NIBS) and task-practice in virtual environments (VEs) can influence motor relearning as well as adaptive plasticity. However, the effectiveness of a combination of NIBS and task-practice in VEs on UL motor improvement has not been systematically examined. The objective of this review was to examine the evidence regarding the effectiveness of combining NIBS with task-practice in VEs on UL motor impairment and activity levels. A systematic review of the published literature was conducted using standard methodology. Study quality was assessed using the PEDro scale and Down’s and Black checklist. Four studies examining the effects of a combination of NIBS (involving transcranial direct current stimulation; tDCS and repetitive transcranial magnetic stimulation; rTMS) were retrieved. Of these, three studies were randomized controlled trials (RCTs) and one was a cross-sectional study. There was 1a level evidence that the combination of NIBS and task-practice in a VE was beneficial in the sub-acute stage. A combination of training in a VE with rTMS as well as tDCS was beneficial for motor improvements in the UL in sub-acute stage of stroke (1b level). The combination was not found to be superior compared to task practice in VEs alone in the chronic stage (1b level). The results suggest that people with stroke may be capable of improving levels of motor impairment and activity in the sub-acute stage if their rehabilitation program involves a combination on NIBS and VE training. Emergent questions regarding the use of more sensitive outcomes, different types of stimulation parameters, locations and training environments still need to be addressed.

Source: Virtual reality and non-invasive brain stimulation in stroke: How effective is their combination for upper limb motor improvement? – IEEE Xplore Document

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[Abstract] The eWrist — A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation.

Abstract:

Chronic wrist impairment is frequent following stroke and negatively impacts everyday life. Rehabilitation of the dysfunctional limb is possible but requires extensive training and motivation. Wearable training devices might offer new opportunities for rehabilitation. However, few devices are available to train wrist extension even though this movement is highly relevant for many upper limb activities of daily living. As a proof of concept, we developed the eWrist, a wearable one degree-of-freedom powered exoskeleton which supports wrist extension training. Conceptually one might think of an electric bike which provides mechanical support only when the rider moves the pedals, i.e. it enhances motor activity but does not replace it. Stroke patients may not have the ability to produce overt movements, but they might still be able to produce weak muscle activation that can be measured via surface electromyography (sEMG). By combining force and sEMG-based control in an assist-as-needed support strategy, we aim at providing a training device which enhances activity of the wrist extensor muscles in the context of daily life activities, thereby, driving cortical reorganization and recovery. Preliminary results show that the integration of sEMG signals in the control strategy allow for adjustable assistance with respect to a proxy measurement of corticomotor drive.

Source: The eWrist — A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation – IEEE Xplore Document

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[Abstract] Applying a soft-robotic glove as assistive device and training tool with games to support hand function after stroke: Preliminary results on feasibility and potential clinical impact

Published in: Rehabilitation Robotics (ICORR), 2017 International Conference on

Abstract:

Recent technological developments regarding wearable soft-robotic devices extend beyond the current application of rehabilitation robotics and enable unobtrusive support of the arms and hands during daily activities. In this light, the HandinMind (HiM) system was developed, comprising a soft-robotic, grip supporting glove with an added computer gaming environment. The present study aims to gain first insight into the feasibility of clinical application of the HiM system and its potential impact. In order to do so, both the direct influence of the HiM system on hand function as assistive device and its therapeutic potential, of either assistive or therapeutic use, were explored. A pilot randomized clinical trial was combined with a cross-sectional measurement (comparing performance with and without glove) at baseline in 5 chronic stroke patients, to investigate both the direct assistive and potential therapeutic effects of the HiM system. Extended use of the soft-robotic glove as assistive device at home or with dedicated gaming exercises in a clinical setting was applicable and feasible. A positive assistive effect of the soft-robotic glove was proposed for pinch strength and functional task performance ‘lifting full cans’ in most of the five participants. A potential therapeutic impact was suggested with predominantly improved hand strength in both participants with assistive use, and faster functional task performance in both participants with therapeutic application.

Source: Applying a soft-robotic glove as assistive device and training tool with games to support hand function after stroke: Preliminary results on feasibility and potential clinical impact – IEEE Xplore Document

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[Abstract] Design factors and opportunities of rehabilitation robots in upper-limb training after stroke

Abstract:

The occurrence of strokes has been progressively increasing. Upper limb recovery after stroke is more difficult than lower limb. One of the rapidly expanding technologies in post-stroke rehabilitation is robot-aided therapy. The advantage of robots is that they are able to deliver highly repetitive therapeutic tasks with minimal supervision of a therapist. However, from the literature, the focus of robotic design in stroke rehabilitation has been technology-driven. Clinical and therapeutic requirements were not seriously considered in the design of rehabilitation robots. The purpose of this study was twofold: (1) demonstrate the missing elements of current robot-aided therapy; (2) identify design factors and opportunities of rehabilitation robots (in upper-limb training after stroke). In this study, we performed a literature review on articles relevant to rehabilitation robots in upper-limb training after stroke. We identified the design foci of current rehabilitation robots for upper limb stroke recovery. Using the therapeutic framework for stroke rehabilitation in occupational therapy, we highlighted design factors and opportunities of rehabilitation robots. The outcomes of this study benefit the robotics design community in the design of rehabilitation robots.

1. Introduction

A robot is defined as a machine programmable to perform and modify tasks in response to changes in the environment [1]. The benefits of robots are noticeable in productivity, safety, and in saving time and money. The advancement of robot technologies in the past decade caused the wide adoption of robots in our lives and in the society. For instance, in education, robots were implemented in undergraduate courses to teach core artificial intelligence concepts, e.g., algorithms for searching tree data structures [2]. In agriculture, robotic milking systems (being able to reduce labor/operational costs) were installed to replace conventional milking that gave cows the freedom to be milked throughout the day [3]. In healthcare, service robots were implemented to provide functional assistance for the elderly in home environments, e.g., bringing medication for the emergency and picking up heavy objects low on the ground [4].

Source: Design factors and opportunities of rehabilitation robots in upper-limb training after stroke – IEEE Xplore Document

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[Abstract] Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects  

Abstract:

Rehabilitation robots have become increasingly popular for stroke rehabilitation. However, the high cost of robots hampers their implementation on a large scale. This study implements the concept of a modular and reconfigurable robot, reducing its cost and size by adopting different therapeutic end effectors for different training movements using a single robot. The challenge is to increase the robot’s portability and identify appropriate kinds of modular tools and configurations. Because literature on the effectiveness of this kind of rehabilitation robot is still scarce, this paper presents the design of a portable and reconfigurable rehabilitation robot and describes its use with a group of post-stroke patients for wrist and forearm training. Seven stroke subjects received training using a reconfigurable robot for 30 sessions, lasting 30 minutes per session. Post-training, statistical analysis showed significant improvement of 3.29 points (16.20%, p = 0.027) on the Fugl-Meyer Assessment Scale for forearm and wrist components (FMA-FW). Significant improvement of active range of motion (AROM) was detected in both pronation-supination (75.59%, p = 0.018) and wrist flexion-extension (56.12%, p = 0.018) after the training. These preliminary results demonstrate that the developed reconfigurable robot could improve subjects’ wrist and forearm movement.

Source: Portable and Reconfigurable Wrist Robot Improves Hand Function for Post-Stroke Subjects – IEEE Xplore Document

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[BOOK + References] Adaptation and Rehabilitation in Patients with Homonymous Visual Field Defects

Abstract

Hemianopia leads to severe impairment of spatial orientation and mobility. In cases without macular sparing an additional reading disorder occurs. Persistent visual deficits require rehabilitation. The goal is to compensate for the deficits to regain independence and to maintain the patient’s quality of life. Spontaneous adaptive mechanisms, such as shifting the field defect towards the hemianopic side by eye movements or eccentric fixation, are beneficial, but often insufficient. They can be enhanced by training, e.g., saccadic training to utilize the full field of gaze in order to improve mobility and by special training methods to improve reading performance. At present only compensatory interventions are evidence-based.

References (71)

Source: Adaptation and Rehabilitation in Patients with Homonymous Visual Field Defects – Springer

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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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