Changing stroke rehab and research worldwide now.Time is Brain! trillions and trillions of neurons that DIE each day because there are NO effective hyperacute therapies besides tPA(only 12% effective). I have 523 posts on hyperacute therapy, enough for researchers to spend decades proving them out. These are my personal ideas and blog on stroke rehabilitation and stroke research. Do not attempt any of these without checking with your medical provider. Unless you join me in agitating, when you need these therapies they won't be there.

What this blog is for:

My blog is not to help survivors recover, it is to have the 10 million yearly stroke survivors light fires underneath their doctors, stroke hospitals and stroke researchers to get stroke solved. 100% recovery. The stroke medical world is completely failing at that goal, they don't even have it as a goal. Shortly after getting out of the hospital and getting NO information on the process or protocols of stroke rehabilitation and recovery I started searching on the internet and found that no other survivor received useful information. This is an attempt to cover all stroke rehabilitation information that should be readily available to survivors so they can talk with informed knowledge to their medical staff. It lays out what needs to be done to get stroke survivors closer to 100% recovery. It's quite disgusting that this information is not available from every stroke association and doctors group.

Showing posts with label elbow. Show all posts
Showing posts with label elbow. Show all posts

Wednesday, October 25, 2023

A robot-aided visuomotor wrist training induces motor and proprioceptive learning that transfers to the untrained ipsilateral elbow

Useless for us since this was tested in healthy adults. It will never get tested in stroke survivors, there aren't two functioning neurons in our stroke medical 'professionals' to see this and recognize how it could help survivors. 


A robot-aided visuomotor wrist training induces motor and proprioceptive learning that transfers to the untrained ipsilateral elbow

Abstract

Background

Learning of a visuomotor task not only leads to changes in motor performance but also improves proprioceptive function of the trained joint/limb system. Such sensorimotor learning may show intra-joint transfer that is observable at a previously untrained degrees of freedom of the trained joint.

Objective

Here, we examined if and to what extent such learning transfers to neighboring joints of the same limb and whether such transfer is observable in the motor as well as in the proprioceptive domain. Documenting such intra-limb transfer of sensorimotor learning holds promise for the neurorehabilitation of an impaired joint by training the neighboring joints.

Methods

Using a robotic exoskeleton, 15 healthy young adults (18–35 years) underwent a visuomotor training that required them to make continuous, increasingly precise, small amplitude wrist movements. Wrist and elbow position sense just-noticeable‐difference (JND) thresholds and spatial movement accuracy error (MAE) at wrist and elbow in an untrained pointing task were assessed before and immediately after, as well as 24 h after training.

Results

First, all participants showed evidence of proprioceptive and motor learning in both trained and untrained joints. The mean JND threshold decreased significantly by 30% in trained wrist (M: 1.26° to 0.88°) and by 35% in untrained elbow (M: 1.96° to 1.28°). Second, mean MAE in untrained pointing task reduced by 20% in trained wrist and the untrained elbow. Third, after 24 h the gains in proprioceptive learning persisted at both joints, while transferred motor learning gains had decayed to such extent that they were no longer significant at the group level.

Conclusion

Our findings document that a one-time sensorimotor training induces rapid learning gains in proprioceptive acuity and untrained sensorimotor performance at the practiced joint. Importantly, these gains transfer almost fully to the neighboring, proximal joint/limb system.

Introduction

Within the context of motor learning, transfer of learning refers to how an acquired skill can be executed in a new context, a new workspace, or how a learnt motor pattern transfers from one effector system to another [1,2,3]. Of specific interest has been to determine what parameters influence such learning and, importantly, whether it transfers to other motor systems, such as between homologous muscle systems such as those controlling the left and right hand. There is evidence of inter- and intralimb transfer of motor learning [1, 4,5,6]. That is to say, untrained limb systems exhibit signs of motor learning without practice. Moreover, neuromotor systems adapt to unknown force fields [7, 8] and the learning of such new dynamics studies induces observable changes in the movement kinematics and kinetics of the untrained limb [9].

While there is solid evidence for motor learning transfer, the transfer of proprioceptive or somatosensory learning has received less attention. This is noteworthy given the fact that proprioceptive signals are essential for motor learning and that the major neural somatosensory and motor cortical areas have substantial reciprocal connections [10]. Moreover, there is solid evidence that proprioceptive and motor learning is bidirectional [11,12,13]. That is to say, gains in motor performance are associated with concurrent gains in proprioceptive function such as an increase in position sense acuity and vice versa [14].

With respect to the transfer of proprioceptive learning, recent work from our group documented that a short 45-min visuomotor training of the right wrist significantly reduced position sense thresholds in the trained wrist and that these gains in proprioceptive function transferred to the contralateral left wrist [15]. Interestingly, the position sense acuity of both wrists improved at nearly the same rate as their respective JND thresholds were reduced by approximately 30% at the end of training. Importantly, the time scale of memory consolidation differed for the transfer of proprioceptive and motor learning. The gains in proprioceptive acuity were measurable immediately after training and decayed quickly within 24 h, while a motor transfer was only observed 24 h past testing. In that study the fast decay of proprioceptive learning was likely owed to the short training period. A previous report [11] employing a robot-aided wrist visuomotor training over 5 days documented that consolidation of proprioceptive learning was observed over several days with improvements in position sense acuity still measurable up to 5 days after the last training.

The current study was designed to enhance our knowledge about the magnitude and extent of ipsilateral transfer of motor and proprioceptive learning. The term ipsilateral here refers to the transfer of learning to adjacent joints within the same limb that are controlled by different, non-homologous muscles. Using a robotic wrist exoskeleton, healthy adults learnt a visuomotor task that required them to make increasingly precise, small amplitude wrist movements. We then determined position sense thresholds of the wrist and the adjacent elbow to obtain a psychophysical marker of proprioceptive learning. In addition, participants performed a goal-directed pointing task that they had not practiced before and after training to assess to what extent motor learning had transferred from the wrist/hand to the elbow/forearm motor systems. Finally, we examined how well such learning retained after 24 h.

More at link.

Sunday, December 18, 2022

Wearable elbow robot in rehabilitation after a stroke

With mild or absent spasticity they cherry picked patients to get better results. Bad research because bad mentors and senior researchers allowed that.  I expect mentors and senior researchers to at least be competent in stroke, not like this.

Wearable elbow robot in rehabilitation after a stroke

Authors: Irina Benedek, Victor Dabala, Oana Vanta 

Keywords: stroke, wearable elbow robot, robotic neuro-rehab, early-stroke rehab

The burden of stroke

What is the role of wearable elbow robots in rehabilitation after a stroke? Acute stroke, also known as a cerebrovascular accident, represents the acute onset of a focal neurological deficit due to an impairment in a specific vascular territory. Annually, approximately 800.000 new cases are reported only in the United States; in other words, there is a new case every 40 seconds, and death occurs every 4 minutes. Therefore, stroke remains one of the most important causes of mortality and disability worldwide and a significant public health issue [1, 2].

There are two main types of stroke: ischemic stroke (see Figure 1 for Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification) -accounting for 85% of acute cerebrovascular events- and hemorrhagic. Ischemic stroke is due to the interruption of blood flow in a particular brain territory, while a rupture of a blood vessel supplying the brain leads to a hemorrhage [1]. Hemorrhagic strokes are broadly due to intracerebral hemorrhage or subarachnoid hemorrhage [2].

The categories of ischemic stroke are showcased in Figure 1 below  [2].

Graphic 1 Ischemic Stroke cathegories

Figure 1. Ischemic stroke categories

A vast etiology can lead to a cerebrovascular attack; the most common risk factors are presented in Figure 2  below.

Graph 2 Common risk factors for stroke

Figure 2. Common risk factors for stroke

When discussing the consequences of stroke, it is estimated that approximately 70% of the patients who survive a stroke will suffer from hemiparesis affecting the upper limbs, but most of the patients will remain with a type of neurological impairment. In addition, two-thirds of post-stroke patients will also experience a considerable impairment in upper limb motor function. As a result, stroke limits the ability to perform daily activities ( See Figure 3).

Graph 3 Daily Activities limited by stroke

Figure 3. Daily activities limited by stroke

Possibilities of recovery after a stroke

One of the main goals of stroke rehabilitation is to improve upper limb motor function to reduce disability and enhance the overall quality of life. The most crucial part of long-term recovery was reported in the first three months when spontaneous recovery and learning-dependent processes were dominant. However, scientific data suggests rehabilitation should not be limited only to this period. Unfortunately, several studies have demonstrated that hospitalized patients were inactive most of the day in the ward. The time estimated for physical and occupational therapy was limited to approximately three hours per day. Active and passive kinesiotherapy duration was about 30 minutes, while median repetition was 33-50 or even less for patients with severe deficits. Despite these aspects, it has been recognized that the most effective way to increase neuroplasticity and motor recovery after a cerebrovascular attack is through intensive treatments and repetitive motor tasks [3].

Learn more about:

Robots aid in physical therapy for motor recovery of the upper limb

Over the past years, rehabilitation robots have gained popularity in specific stroke rehabilitation since they have shown the capability to increase and individualize the number of movement repetitions compared to classic kinesiotherapy. These advantages can offer clinicians the possibility to adapt the recovery programs according to every patient’s needs and better chances of achieving the desired goals. Even though almost every patient with motor impairments should be considered for this type of rehabilitation, recent studies proved that chronic stroke patients with moderate deficits showed better improvements in motor function from robotic-assisted upper limb training than those with mild impairments. Therefore, the stratification of stroke patients based on their motor deficits was essential to obtain the best individual outcomes. Since the elbow joint is the most common and highly affected after a stroke, the 2021 study of Huang MZ et al. highlights the development of a portable exoskeleton robot targeting upper limb neurorehabilitation with a focus on flexion/extension of the elbow [3]. 

As such, the study was bidirectional, i.e., it was meant to:

  • Assess the effectiveness and suitability of a wearable elbow robotic device for in-bed training of patients with subacute stroke
  • Evaluate the patterns of the active motor recovery of the upper limb in patients with moderate and severe disabilities at this level [3]. (Since you didn't have patients with spasticity you didn't even get to moderate or severe disabilities. My god, was your research bad!)

The study included 11 patients (mean age 50 years) with early subacute stroke (7 days to 3 months) and late subacute stroke (3 to 6 months) who followed the eligibility criteria presented in Figure 4 below [3].

Graph 4 Patient eligibility

Figure 4. Eligibility criteria

The robotic device

The exoskeleton consisted of the upper arm and forearm braces, a servomotor, a gear head, and a computer screen for visual feedback. The wearable robot was designed to supply passive stretching, game-based active movement, and assessment of biomechanical properties such as muscle strength and elbow range of motion [3], as seen in Figure 5.

fnhum 15 669059 g001

Figure 5. A. The wearable elbow robotic device and B. Clinical in-bed setup 
(from Huang MZ et al. In-Bed Sensorimotor Rehabilitation in Early 
and Late Subacute Stroke Using a Wearable Elbow Robot: A Pilot Study [3]. Available here.

The functionality of the elbow robot

While lying on their back, patients wore the robot on the impaired upper limb with the shoulder at about 30 degrees flexion and 15-degree abduction. The device was mounted with one brace aligned to the elbow flexion axis and the output axis (Figure 5 – A), while the computer monitor was placed in front of the patient and adjusted as needed (Figure 5 – B) [3]. 

Each session consisted of passive stretching of the elbow (15 minutes), assisted active training through movement gameplay (15 minutes), and passive cool-down stretching (15 minutes). Elbow active range of motion (ROM) and maximum isometric voluntary contraction (MVC) of elbow flexors and extensor muscles were measured before and after each session. The training protocol was adapted to every patient’s needs. Patients benefited from four sessions per week during approximately a month of hospitalization, resulting in around 15 sessions [3]. 

Clinical outcome results such as upper limb motor recovery, spasticity, and muscle strength were followed in all patients before and after robotic training and 4 weeks after completion. In addition, parameters such as the Fugl-Meyer Assessment of the upper extremity, the Motricity Index, and the Modified Ashworth Scale were used to evaluate the progress [3].      

Some minor adverse effects were reported, such as:

  • Mild skin compression due to robot fixation
  • Muscle soreness after the first session of training (relieved after 24 h)
  • Mild fatigue after the active movements.

Nonetheless, significant increases in the Maximum Voluntary Contractions were observed after the completion of training, with each session producing training-induced changes in the MVC of elbow muscle groups (1.93 Nm (muscle torque) increase in elbow flexors, 0.68 Nm (muscle torque) increase in elbow extensors).

Regarding the flexor muscle group, stroke survivors with severe upper limb disability had a lower initial performance value than the subjects with moderate motor deficits. By comparison, the post-session improvement rate was more prominent in the group of patients with severe motor impairment [3].

Patients were assessed both before and after the 15 training sessions and at four weeks after the end of the sessions, with no differences reported when comparing the data between the end of the sessions and the follow-up at 4 weeks. Moreover, no significant change was observed in coordination and muscle spasticity (mild or absent in most patients) [3].

The advantages of robotic training 

Robotic-assisted rehabilitation has a significant advantage, as this type of intervention can deliver higher dosage and higher-intensity training than conventional therapy. This aspect makes robotic-assisted therapy a promising novel technology for the rehabilitation of patients with motor deficits caused by stroke. Exoskeleton devices used in robotic-assisted therapy were found to have better rehabilitation results than conventional physiotherapy, and their efficacy was found to increase further when combining conventional therapy with robotic training [4]. 

The in-bed rehabilitation robotic device and training developed by Huang et al. [3] was found feasible for both early and late subacute stroke survivors. The superior aspects of the robotic device in contrast to conventional therapy are presented in Figure 6 below.

 

 

 

 

Graph 5 Superior aspects of the in bed rehabilitation robot

Figure 6. The superior aspects of the in-bed 
rehabilitation robot

 

Their [3] findings highlighted that applying in-bed rehabilitation robotic training in the subacute stroke stage is beneficial for motor recovery and is a patient-centered procedure. 

Future of the robotic elbow device in rehabilitation 

Considering the presented study by Huang et al. [3], it should be acknowledged that the use of such robotic elbow devices in patients with increased upper limb spasticity will help with the implementation of different clinical variables to evaluate muscle tone, synergistic movements, and active isolated movement in everyday practice in a more significant number of stroke survivors while enhancing a detailed analysis of the interferences between conventional rehabilitation and robotic procedures. 

Moreover, further developments of the current applications of robot-aided interventions in post-stroke therapy are expected to be used increasingly as robot-aided rehabilitation programs become more feasible and help improve stroke survivors’ clinical measurements and quality of life.

References

  1. Adams HP Jr, Bendixen BH, Kappelle LJ, Biller J et al. Classification of Subtype of Acute Ischemic Stroke Definitions for Use in a Multicenter Clinical Trial. Stroke Vol 24, No 1 Jan 1993, 35-41. doi/10.1161/01.STR.24.1.35
  2. Tadi P, Lui F. Acute Stroke. [Updated 2021 Sep 29]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK535369/
  3. Huang MZ, Yoon Y-S, Yang J, Yang C-Y, and Zhang L-Q. In-Bed Sensorimotor Rehabilitation in Early and Late Subacute Stroke Using a Wearable Elbow Robot: A Pilot Study. Front. Hum. Neurosci. 2021. 15:669059. doi: 10.3389/fnhum.2021.669059
  4. Chang WH, Kim YH. Robot-assisted Therapy in Stroke Rehabilitation. J Stroke. 2013;15(3):174-181. doi:10.5853/jos.2013.15.3.174

Wednesday, September 28, 2022

Shoulder and elbow muscle activity during fully supported trajectory tracking in people who have had a stroke

What have your doctors and therapists done with this in 13 years to help survivor recovery? NOTHING? Then why the fuck are you seeing and paying them? I expect my medical professionals to be professional, meaning up-to-date on all appropriate research. The massive number of research articles published every year is no excuse.

Shoulder and elbow muscle activity during fully supported trajectory tracking in people who have had a stroke


Received 19 February 2009
Received in revised form 4 August 2009 
Accepted 6 August 2009

Sunday, July 24, 2022

Effect of stretching of spastic elbow under intelligent control in chronic stroke survivors—a pilot study.

So where EXACTLY do we get this device so our hospitals can use it on us before we become chronic?

 Effect of stretching of spastic elbow under intelligent control in chronic stroke survivors—a pilot study.

Frontiers in Neurology , Volume 12 , Pgs. 742260.

NARIC Accession Number: J89144.  What's this?
ISSN: 1664-2295.
Author(s): Rao, Sanjana; Huang, Meizhen; Chung, Sun G.; Zhang, Li-Qun.
Project Number: 90REMM0001.
Publication Year: 2021.
Number of Pages: 10.
Abstract: Study assessed the short-term effects of strenuous dynamic stretching of the elbow joint using an intelligent stretching device in chronic spastic stroke survivors. The intelligent stretching device was utilized to provide a single session of intensive stretching to the spastic elbow joint in the sagittal plane (i.e., elbow flexion and extension). The stretching was provided to the extreme range, safely, with control of the stretching velocity and torque to increase the joint range of motion (ROM) and reduce spasticity and joint stiffness. Eight chronic stroke survivors completed a single 40-minute stretching intervention session. Elbow passive and active ROM, strength, passive stiffness (quantifying the non-reflex component of spasticity), and instrumented tendon reflex test of the biceps tendon (quantifying the reflex component of the spasticity) were measured before and after stretching. After stretching, there was a significant increase in passive ROM of elbow flexion and extension. Also, elbow active ROM and the spastic elbow flexors showed a trend of increase in their strength. Findings suggest that intelligent stretching can be used to repeatedly and regularly stretch spastic elbow joints, which subsequently helps to reduce upper-limb impairments post-stroke.
Descriptor Terms: EXERCISE, JOINTS, LIMBS, MOBILITY IMPAIRMENTS, MOTOR SKILLS, SPASTICITY, STROKE.


Can this document be ordered through NARIC's document delivery service*?: Y.
Get this Document: https://doi.org/10.3389/fneur.2021.742260.

Citation: Rao, Sanjana, Huang, Meizhen, Chung, Sun G., Zhang, Li-Qun. (2021). Effect of stretching of spastic elbow under intelligent control in chronic stroke survivors—a pilot study.  Frontiers in Neurology , 12, Pgs. 742260. Retrieved 7/24/2022, from REHABDATA database.

Saturday, April 16, 2022

Shoulder and elbow muscle activity during fully supported trajectory tracking in people who have had a stroke

Well you described something, but I see nothing produced from here that is going to do survivors one fucking bit of good.

Shoulder and elbow muscle activity during fully supported trajectory tracking in people who have had a stroke


 

A.M. Hughes a,*, 
C.T. Freeman b, 
J.H. Burridge a, 
P.H. Chappell b, 
P.L. Lewin b, 
E. Rogers b
a School of Health Sciences, University of Southampton, Southampton, SO17 1BJ, UK
b School of Electronics and Computer Science, University of Southampton, Southampton, SO17 1BJ, UK

 abstract

An inability to perform tasks involving reaching is a common problem for stroke patients. This paper provides an insight into mechanisms associated with recovery of upper limb function by examining how stroke participants’ upper limb muscle activation patterns differ from those of neurologically intact participants, and how they change in response to an intervention.In this study, five chronic stroke participants undertook nine tracking tasks in which trajectory (orientation and length), speed and resistance to movement were varied. During these tasks, EMG signals were recorded from triceps, biceps, anterior deltoid, upper, middle and lower trapezius and pectoralis major.Data collection was performed in sessions both before, and after, an intervention in which participants performed a similar range of tracking tasks with the addition of responsive electrical stimulation applied to their triceps muscle. The intervention consisted of eighteen one hour treatment sessions, with two participants attending an additional seven sessions. During all sessions, each participant’s arm was supported by a hinged arm holder which constrained their hand to move in a two dimensional plane.Analysis of the pre intervention EMG data showed that timing and amplitude of peak EMG activity for all stroke participants differed from neurologically intact participants. Analysis of post intervention EMG data revealed that statistically significant changes in these quantities had occurred towards those of neu-rologically intact participants.

Saturday, January 23, 2021

NEUROExos: A Powered Elbow Exoskeleton for Physical Rehabilitation

 Useless. You tell us something is designed but give us NOTHING  on the results from its use.

NEUROExos: A Powered Elbow Exoskeleton for Physical Rehabilitation

Publisher: IEEE
Nicola Vitiello; Tommaso Lenzi; Stefano Roccella; Stefano Marco Maria De Rossi; Emanuele Cattin; Francesco Giovacchini; Fabrizio Vecchi; Maria Chiara Carrozza

Abstract:
This paper presents the design and experimental testing of the robotic elbow exoskeleton NEUROBOTICS Elbow Exoskeleton (NEUROExos). The design of NEUROExos focused on three solutions that enable its use for poststroke physical rehabilitation. First, double-shelled links allow an ergonomic physical human-robot interface and, consequently, a comfortable interaction. Second, a four-degree-of-freedom passive mechanism, embedded in the link, allows the user's elbow and robot axes to be constantly aligned during movement. The robot axis can passively rotate on the frontal and horizontal planes 30° and 40°, respectively, and translate on the horizontal plane 30 mm. Finally, a variable impedance antagonistic actuation system allows NEUROExos to be controlled with two alternative strategies: independent control of the joint position and stiffness, for robot-in-charge rehabilitation mode, and near-zero impedance torque control, for patient-in-charge rehabilitation mode. In robot-in-charge mode, the passive joint stiffness can be changed in the range of 24-56 N·m/rad. In patient-in-charge mode, NEUROExos output impedance ranges from 1 N·m/rad, for 0.3 Hz motion, to 10 N·m/rad, for 3.2 Hz motion.
Published in: IEEE Transactions on Robotics ( Volume: 29, Issue: 1, Feb. 2013

Sunday, September 20, 2020

NEUROExos: A Powered Elbow Exoskeletonfor Physical Rehabilitation

You really think your hospital is going to afford this? They can't even get you music players to help with rehab costing $18.00 or tell you how to get a music app on your phone. 

THAT IS HOW INCOMPETENT YOUR STROKE HOSPITAL IS.

  NEUROExos: A Powered Elbow Exoskeletonfor Physical Rehabilitation

 Nicola Vitiello , Member, IEEE
, Tommaso Lenzi, Student Member, IEEE
, Stefano Roccella,Stefano Marco Maria De Rossi, Student Member, IEEE
, Emanuele Cattin, Francesco Giovacchini,Fabrizio Vecchi, Member, IEEE
, and Maria Chiara Carrozza, Member, IEEE

 Abstract

—This paper presents the design and experimental testing of the robotic elbow exoskeleton NEUROBOTICS Elbow Exoskeleton (NEUROExos). The design of NEUROExos focused on three solutions that enable its use for post stroke physical rehabilitation. First, double-shelled links allow an ergonomic physical human–robot interface and, consequently, a comfortable interaction. Second, a four-degree-of-freedom passive mechanism, em-bedded in the link, allows the user’s elbow and robot axes to beconstantly aligned during movement. The robot axis can passively rotate on the frontal and horizontal planes 30 and 40, respectively, and translate on the horizontal plane 30 mm. Finally, a variable impedance antagonistic actuation system allows NEUROExos to be controlled with two alternative strategies: independent con-trol of the joint position and stiffness, for robot-in-charge rehabilitation mode, and near-zero impedance torque control, for patient-in-charge rehabilitation mode. In robot-in-charge mode, the passive joint stiffness can be changed in the range of 24–56 N·m/rad. Inpatient in charge mode, NEUROExos output impedance ranges from 1 N·m/rad, for 0.3 Hz motion, to 10 N·m/rad, for 3.2 Hzmotion.
 
 


Tuesday, November 12, 2019

Tuesday, July 17, 2018

Is spasticity or spastic cocontraction of the elbow flexors associated with the limitation of voluntary elbow extension in adults with acquired hemiparesis?

I don't care that spasticity causes the problem of elbow extension. What the fuck is the intervention solution? Don't researchers understand survivors want solutions NOT descriptions of our problems?
Where the fuck is the strategy leading to solutions?
https://www.sciencedirect.com/science/article/pii/S1877065718310947

Introduction/Background

Muscle overactivity, including spasticity and spastic cocontraction, is an involuntary motor unit recruitment participating in the spastic paresis syndrome after cerebral injury. Spasticity is defined as velocity-dependent increase in tonic stretch reflexes. Spastic cocontraction refers to increased antagonist muscles recruitment triggered by the volitional command of agonist muscles. This study aimed to clarify the association between spasticity and spastic cocontraction of elbow flexors and to study their contribution to the limitation of active elbow extension in hemiparetic adults.

Material and method

Ten adults with acquired hemiparesis and ten healthy participants were included. Surface EMG recorded from elbow muscles during elbow isometric extension contractions was used to compute the index of cocontraction (ICC) for each participant, while spasticity, limitation of active elbow extension, and upper extremity Fugl-Meyer Assessment (FMA-UE) score were obtained in hemiparetic participants. Non-parametric Spearman correlations were performed to investigate the relationship between ICC and (i) limitation of active elbow extension, (ii) elbow flexors spasticity and (iii) FMA-UE.

Results

Our results showed significant ICC in three hemiparetic participants compared with healthy participants, and significant associations between cocontraction and (i) active elbow extension limitation (rs = 0.81, P < 0.001) and iii) Fugl-Meyer Assessment score (rs = −0.53, P = 0.017) in hemiparetic participants. No significant correlation was found between spasticity and active elbow extension limitation.

Conclusion

Our results are the first to show that spastic cocontraction directly contributes to elbow extension deficit in adults with acquired hemiparesis, and further confirm that spasticity and spastic cocontraction have different functional repercussions with regards to impaired motor function. Our findings support the conclusion that spastic cocontraction, rather than spasticity, has significant functional repercussions on impaired active motor function in hemiparetic adults. Therapeutic innovations should be directed toward reduction of spastic cocontraction to improve motor function in acquired hemiparesis.

Choose an option to locate/access this article:

Check if you have access through your login credentials or your institution.

Thursday, July 5, 2018

A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke

Useless until your stroke hospital gets the protocol for using this.  They've had 4 years and I bet nothing was accomplished in those 4 years. Incompetence reigns supreme in your stroke hospital.

A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke




Electroencephalography (EEG)–based motor imagery (MI) brain-computer interface (BCI) technology has the potential to restore motor function by inducing activity-dependent brain plasticity. The purpose of this study was to investigate the efficacy of an EEG-based MI BCI system coupled with MIT-Manus shoulder-elbow robotic feedback (BCI-Manus) for subjects with chronic stroke with upper-limb hemiparesis. In this single-blind, randomized trial, 26 hemiplegic subjects (Fugl-Meyer Assessment of Motor Recovery After Stroke [FMMA] score, 4-40; 16 men; mean age, 51.4 years; mean stroke duration, 297.4 days), prescreened with the ability to use the MI BCI, were randomly allocated to BCI-Manus or Manus therapy, lasting 18 hours over 4 weeks. Efficacy was measured using upper-extremity FMMA scores at weeks 0, 2, 4 and 12. ElEG data from subjects allocated to BCI-Manus were quantified using the revised brain symmetry index (rBSI) and analyzed for correlation with the improvements in FMMA score. Eleven and 15 subjects underwent BCI-Manus and Manus therapy, respectively. One subject in the Manus group dropped out. Mean total FMMA scores at weeks 0, 2, 4, and 12 weeks improved for both groups: 26.3 ± 10.3, 27.4 ± 12.0, 30.8 ± 13.8, and 31.5 ± 13.5 for BCI-Manus and 26.6 ± 18.9, 29.9 ± 20.6, 32.9 ± 21.4, and 33.9 ± 20.2 for Manus, with no intergroup differences (P = .51). More subjects attained further gains in FMMA scores at week 12 from BCI-Manus (7 of 11 [63.6%]) than Manus (5 of 14 [35.7%]). A negative correlation was found between the rBSI and FMMA score improvement (P = .044). BCI-Manus therapy was well tolerated and not associated with adverse events. In conclusion, BCI-Manus therapy is effective and safe for arm rehabilitation after severe poststroke hemiparesis. Motor gains were comparable to those attained with intensive robotic therapy (1,040 repetitions/session) despite reduced arm exercise repetitions using EEG-based MI-triggered robotic feedback (136 repetitions/session). The correlation of rBSI with motor improvements suggests that the rBSI can be used as a prognostic measure for BCI-based stroke rehabilitation.