Posts Tagged chronic stroke

[EDITOR’S NOTE] Harnessing Neuroplasticity for Functional Recovery – Journal of Neurologic Physical Therapy

Neuroplasticity is the capacity of the nervous system to change its chemistry, structure, and function in response to intrinsic or extrinsic stimuli.1 Neuroplastic mechanisms are activated by environmental, behavioral, or neural processes, and by disease; they underpin the motor and cognitive learning associated with physical therapy or exercise. Neuroplasticity can lead to positive or negative changes in function, which are referred to as adaptive and maladaptive neuroplasticity, respectively. In their roles as clinicians and as scientists, physical therapists and other rehabilitation professionals harness neuroplasticity using evidence-based interventions to maintain or enhance functional performance in individuals with neurological disorders. There is still much to learn about the optimal interventions and parameters of dose and intensity necessary to achieve adaptive neuroplastic changes.

Beyond questions related to dose and intensity, more information is needed regarding the degree to which factors such as past experiences, age, sex, genetics, and the presence of a neurological disorder affects capacity for neuroplastic change. In addition, it is likely that these factors interact with each other, making it even harder to understand their influence on neuroplastic change. Improved measures for assessment of neuroplasticity in humans are needed, such as biomarkers (including movement-related biomarkers) for diagnosing disorders, and predicting and monitoring treatment effectiveness. Greater knowledge of effective rehabilitation and exercise interventions that drive adaptive neuroplasticity, and are tailored to each person’s unique characteristics, will improve patient outcomes. The idea for this special issue was born out of a desire to advance understanding of the mechanisms driving functional change.

Two studies in this special issue use a newer neuroimaging method called functional near-infrared spectroscopy to measure cortical activity during dual-task walking.2,3 Impaired dual-task walking is common in neurological populations and can interfere with the ability to perform daily life activities. Hoppes et al2 examine frontal lobe activation patterns in individuals with and without visual vertigo during dual-task walking. The differences in cortical activation patterns identified increase our understanding of possible mechanisms underlying decrements in dual-task performance in individuals with vestibular disorders, and may be useful for diagnosis, and for predicting or determining functional recovery in this population. Stuart and Mancini3 investigate how open and closed-loop tactile cueing influences prefrontal cortex activity during single- and dual-task walking and turning in individuals with Parkinson disease. Tactile cues delivered to the feet in an open-loop (continuous rhythmic stimuli) or closed-loop (intermittent stimuli based on an individual’s movement) mode are associated with improved gait and turning performance, and it is hypothesized that attention arising from the prefrontal cortex may underlie these cueing effects.4 Their findings of unchanged prefrontal cortex activity are unexpected, and raise additional questions regarding the role of the prefrontal cortex during gait.

Rehabilitation approaches such as task-oriented training that emphasize high repetition and challenge have been shown to facilitate recovery of mobility and function in neurological populations, but responses are varied and residual deficits often remain.5,6 There is still much to be learned about how to deliver the best interventions to optimize nervous system adaptive neuroplasticity and learning that ultimately lead to optimal functional recovery. In a proof-of-principle case series article in this special issue, Peters et al7 explore whether deficits in motor planning of stepping can be reduced by physical therapy focused on fast stepping retraining, or by conventional therapy focused on balance and mobility training, in individuals with subacute stroke. Both interventions altered electroencephalogic measures indicative of motor planning duration and amplitude of stepping; furthermore, duration changes for all participants were in the direction of those acquired from healthy adult values. These findings suggest that physical therapy may be able to drive neuroplasticity to improve initiation of stepping in individuals after stroke.

A growing body of human and animal evidence supports thataerobic exercise  promotes neuroplasticity and functional recovery in many neurological disorders.1 Chaves et al8 utilized transcranial magnetic stimulation to examine changes in brain excitability measured in the upper extremity following a 40-minute bout of aerobic exercise (ie, body weight-supported treadmill walking) in individuals with progressive multiple sclerosis requiring devices for walking. Improvements in brain excitability were found following the aerobic exercise, which suggest that the capacity for neuroplasticity exists in this population. Participants’ responses to the exercise were greater in those with higher cardiorespiratory fitness and less body fat. The authors discuss that maintaining an active lifestyle and participating in aerobic exercise may be beneficial for improving brain health and neuroplasticity in people with progressive multiple sclerosis.

Finally, for the first time Vive et al9 translate to the clinical setting the enriched environment model used in laboratory-based animal studies. Evidence from preclinical studies suggests that combinational therapies such as enriched environments, which take advantage of multiple mechanisms underlying neuroplasticity, may promote greater functional recovery than a single therapy.10 The researchers examine the effects of a high-dose enriched task-specific therapy, which combines physical therapy with social and cognitive stimulation on motor recovery in individuals with chronic stroke. Their findings demonstrate that the enriched task-specific therapy intervention is feasible, and suggest that it may be beneficial for repair and recovery long after a stroke.

The articles in this issue provide new insights to improve our understanding of adaptive neuroplastic changes in nervous system activity resulting from neurological disorders or following exercise interventions. Evidence regarding benefits of physical therapy and exercise interventions to promote motor and cognitive function across the lifespan and in the presence of neurological pathology may motivate individuals to adapt and adhere to healthier lifestyles.1 Physical therapists and rehabilitation professionals can use the evolving neuroplasticity research to assist with decision-making regarding individualized therapy goals, and the selection and monitoring of therapeutic interventions to best achieve compliance and goal attainment. Collaborations between rehabilitation clinicians and researchers will enhance and hasten the translation of neuroplasticity research into effective clinical therapies. In the end, these efforts will certainly lead us to improved interventions that help to restore function and health to our patients.

REFERENCES

1. Cramer SC, Sur M, Dobkin BH, et al Harnessing neuroplasticity for clinical applications. Brain. 2011;134(pt 6):1591–1609. doi:10.1093/brain/awr039.

2. Hoppes C, Huppert T, Whitney S, et al Changes in cortical activation during dual-task walking in individuals with and without visual vertigo. J Neurol Phys Ther. 2020;44(2):156–163.

3. Stuart S, Mancini M. Pre-frontal cortical activation with open and closed-loop tactile cueing when walking and turning in Parkinson disease: a pilot study. J Neurol Phys Ther. 2020;44(2):121–131.

4. Maidan I, Bernad-Elazari H, Giladi N, Hausdorff JM, Mirelman A. When is higher level cognitive control needed for locomotor tasks among patients with Parkinson’s disease? Brain Topogr. 2017;30(4):531–538. doi:10.1007/s10548-017-0564-0.

5. Dobkin BH. Motor rehabilitation after stroke, traumatic brain, and spinal cord injury: common denominators within recent clinical trials. Curr Opin Neurol. 2009;22(6):563–569. doi:10.1097/WCO.0b013e3283314b11.

6. Hornby T, Reisman D, Ward I, et al Clinical practice guideline to improve locomotor functional following chronic stroke, incomplete spinal cord injury, and brain injury. J Neurol Phys Ther. 2020;40(1):49–100.

7. Peters S, Ivanova T, Lakhani B, Boyd L, Garland SJ. Neuroplasticity of cortical planning for initiating stepping post-stroke: a case series. J Neurol Phys Ther. 2020;44(2):164–172.

8. Chaves A, Devsahayam A, Kelly L, Pretty R, Ploughman M. Exercise-induced brain excitability changes in progressive multiple sclerosis: a pilot study. J Neurol Phys Ther. 2020;44(2):132–144.

9. Vive S, Geijerstam JL, Kuhn HG, Kall LB. Enriched, task-specific therapy in the chronic phase after stroke. J Neurol Phys Ther. 2020;44(2):145–155.

10. Malá H, Rasmussen CP. The effect of combined therapies on recovery after acquired brain injury: systematic review of preclinical studies combining enriched environment, exercise, or task-specific training with other therapies. Restor Neurol Neurosci. 2017;35(1):25–64. doi:10.3233/RNN-160682.

via Harnessing Neuroplasticity for Functional Recovery : Journal of Neurologic Physical Therapy

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[Abstract] Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke

Background. Accurate prediction of clinical impairment in upper-extremity motor function following therapy in chronic stroke patients is a difficult task for clinicians but is key in prescribing appropriate therapeutic strategies. Machine learning is a highly promising avenue with which to improve prediction accuracy in clinical practice.

Objectives. The objective was to evaluate the performance of 5 machine learning methods in predicting postintervention upper-extremity motor impairment in chronic stroke patients using demographic, clinical, neurophysiological, and imaging input variables.

Methods. A total of 102 patients (female: 31%, age 61 ± 11 years) were included. The upper-extremity Fugl-Meyer Assessment (UE-FMA) was used to assess motor impairment of the upper limb before and after intervention. Elastic net (EN), support vector machines, artificial neural networks, classification and regression trees, and random forest were used to predict postintervention UE-FMA. The performances of methods were compared using cross-validated R2Results. EN performed significantly better than other methods in predicting postintervention UE-FMA using demographic and baseline clinical data (median R2EN=0.91,R2RF=0.88,R2ANN=0.83,R2SVM=0.79,R2CART=0.70;REN2=0.91,RRF2=0.88,RANN2=0.83,RSVM2=0.79,RCART2=0.70; P < .05). Preintervention UE-FMA and the difference in motor threshold (MT) between the affected and unaffected hemispheres were the strongest predictors. The difference in MT had greater importance than the absence or presence of a motor-evoked potential (MEP) in the affected hemisphere.

Conclusion. Machine learning methods may enable clinicians to accurately predict a chronic stroke patient’s postintervention UE-FMA. Interhemispheric difference in the MT is an important predictor of chronic stroke patients’ response to therapy and, therefore, could be included in prospective studies.

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via Machine Learning Methods Predict Individual Upper-Limb Motor Impairment Following Therapy in Chronic Stroke – Ceren Tozlu, Dylan Edwards, Aaron Boes, Douglas Labar, K. Zoe Tsagaris, Joshua Silverstein, Heather Pepper Lane, Mert R. Sabuncu, Charles Liu, Amy Kuceyeski,

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[Abstract] An investigation into the validity and reliability of mHealth devices for counting steps in chronic stroke survivors

To investigate the validity and test–retest reliability of mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit Ultra) to estimate the number of steps in individuals after chronic stroke and to compare whether the measurement of the number of steps is affected by their location on the body (paretic and non-paretic side).

Observational study with repeated measures.

Fifty-five community-dwelling individuals with chronic stroke.

The number of steps was measured using mHealth devices (Google Fit, Health, STEPZ, Pacer, and Fitbit Ultra), and compared against criterion-standard measure during the Two-Minute Walk Test using habitual speed.

Our sample was 54.5% men, mean age of 62.5 years (SD 14.9) with a chronicity after stroke of 66.8 months (SD 55.9). There was a statistically significant association between the actual number of steps and those estimated by the Google Fit, STEPZ Iphone and Android applications, Pacer iphone and Android, and Fitbit Ultra (0.30 ⩽ r ⩾ 0.80). The Pacer iphone application demonstrated the highest reliability coefficient (ICC(2,1) = 0.80; P < 0.001). There were no statistically significant differences in device measurements that depended on body location.

mHealth devices (Pacer–iphone, Fitbit Ultra, Google Fit, and Pacer–Android) are valid and reliable for step counting in chronic stroke survivors. Body location (paretic or non-paretic side) does not affect validity or reliability of the step count metric.

 

via An investigation into the validity and reliability of mHealth devices for counting steps in chronic stroke survivors – Pollyana Helena Vieira Costa, Thainá Paula Dias de Jesus, Carolee Winstein, Camila Torriani-Pasin, Janaine Cunha Polese, 2020

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[Abstract] SMART Program in Chronic Stroke

Abstract

INTRODUCTION: Long-term functional cognitive impairments are common sequelae of stroke, often resulting in decreased participation in daily life activities. Earlier research showed the benefits of training paradigms targeted at memory, attention, and some executive functions.

METHODS: The current study examined the feasibility of a functionally relevant training program called Strategic Memory Advanced Reasoning Training (SMART). The SMART program teaches strategies to improve abstract reasoning skills and has been shown to enhance aspects of functional cognition, strengthen brain networks, and improve participation in daily life activities across clinical populations. The current study describes the benefits of the SMART program in adults (N = 12) between 54 and 77 years (64.46 ± 8.14 years) with chronic stroke. Participants had 10 sessions of the SMART program over a period of 6 weeks.

RESULTS: The findings showed significant gains in abstract reasoning (p < .05) and participation in daily activities after the SMART program. These gains were relatively stable 6 months later.

CONCLUSION: These findings offer the promise of cognitive gains, even years after stroke. Limitations of the study include a small sample size, potential confounding as a result of additional ongoing therapy, and a relatively short period of follow-up. Further research is needed to examine the benefits of the SMART program. [Annals of International Occupational Therapy. 2020;X(X):xx–xx.]

Source: Annals of International Occupational Therapy. https://doi.org/10.3928/24761222-20200116-03

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[Abstract] The Effect of IoT-based Upper and Lower Extremity Rehabilitation Medical Device Training on Gait in Chronic Stroke Survivor : A Case Study

Purpose: For stroke survivors, abnormal gait patterns lead to a significant risk of falls. We have recently developed an IoT-based Upper and Lower Extremity Rehabilitation Medical Device (RoBoGat) that enables continuous passive motion (CPM) training, squat training (ST), and gait training (GT). The purpose of this study was to test the effectiveness of RoBoGat on gait in a chronic stroke survivor.

Methods: In this study, an individual with right-side chronic hemiparesis post-stroke participated. The participant underwent 14 days of RoBoGat training that involved continuous passive motion training, squat training, and gait training. During the training, knee and hip joint angles were adjusted within the range where the subject felt no pain. We assessed gait, timed up and go test, and visual analog scale at baseline and after first and final interventions.

Results: After the intervention, positive changes were observed such as stride, gait velocity, and loading phase. Improvements were also observed in timed up and go tests. However, there was no significant change in VAS, which assessed pain in training and daily life.

Conclusion: The main finding of this case-control study is that robot-based upper and lower extremity training may be a feasible approach in the neurorehabilitation field. It can be concluded that repetitive and continuous robot rehabilitation exercises have a positive effect on improving the physical function of chronic stroke survivors.

Source: https://www.earticle.net/Article/A368653

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[ARTICLE] The effects of Ai Chi for balance in individuals with chronic stroke: a randomized controlled trial – Full Text

Abstract

This study investigated the effectiveness of Ai Chi compared to conventional water-based exercise on balance performance in individuals with chronic stroke. A total of 20 individuals with chronic stroke were randomly allocated to receive either Ai Chi or conventional water-based exercise for 60 min/time, 3 times/week, and a total of 6 weeks. Balance performance assessed by limit of stability (LOS) test and Berg balance scale (BBS). Fugl-Meyer assessment (FMA) and gait performance were documented for lower extremity movement control and walking ability, respectively. Excursion and movement velocity in LOS test was significantly increased in anteroposterior axis after receiving Ai Chi (p = 0.005 for excursion, p = 0.013 for velocity) but not conventional water-based exercise. In particular, the improvement of endpoint excursion in the Ai Chi group has significant inter-group difference (p = 0.001). Both groups showed significant improvement in BBS and FMA yet the Ai Chi group demonstrated significantly better results than control group (p = 0.025). Ai Chi is feasible for balance training in stroke, and is able to improve weight shifting in anteroposterior axis, functional balance, and lower extremity control as compared to conventional water-based exercise.

Introduction

Stroke is a cerebral vascular disease caused by the interruption of the blood supply to the brain, cutting off the supply of oxygen and nutrients1. Damage to the brain tissue leads to sensory, motor, cognitive, and emotional deficits. With impaired motor and sensory functions, stroke patients suffer from deficits in balance control which plays crucial role in ambulatory function and thus as an important clinical indicator2,3,4,5. Balance is defined as the ability to maintain center of mass (COM) within the stability limits, the boundaries of the base of support (BOS)6. Balance control can be quantified by limit of stability (LOS) test, expressed by movement velocity, displacement excursion, and directional control7,8. Individuals with stroke usually show decline in the abovementioned balance performance9,10,11,12. Bohannon13 noted the correlation between static standing ability and independent mobility in stroke patients (r = 0.62). Lee et al.14 found that walking velocity is associated with maximal displacement excursion in LOS test (r = 0.68, p < 0.01) and Berg balance scale (r = 0.66, p < 0.01) in patients with stroke. In addition, the balance-related fall risks should also be addressed in people with chronic stroke15,16. Therefore, it is crucial to improve balance control in order to improve the balance-related activities for individuals with stroke.

Several elements, such as strengthening, postural control, weight shifting, and agility exercise, are necessary to be incorporated during balance training17. It has also been noted that increased somatosensory inputs and visual deprivation might exert positive effects on top of balance training, as well as enriched environment4,5,18,19. Water-based exercise, by utilizing the properties of water, including buoyancy, viscosity, turbulence, and hydrostatic pressure, has been suggested to improve balance control20,21. Two reviews summarized that the water-based exercise for neurological disorder covers a wide variety, including resistance training, movement facilitation, motor control training, balance training, coordination training and other specific techniques21,22. They indicated that stroke patients improved significantly more in weight shifting ability, dynamic balance, and functional mobility as compared with the land-based intervention21,22.

Ai Chi, first developed by Jun Konno in 1990s23, is one kind of water-based exercise emphasizing characteristics of balance training24. It resembles Tai Chi on land, complemented by Zen shiatzu and Watsu concepts25. Ai Chi is composed of 16 katas (movements), including breathing, upper extremity movements, lower extremity movements, trunk control, and coordinated movements23. With the properties and advantages of water, less weight bearing is required and larger displacement can be achieved. Currently, some studies have mentioned the benefits of Ai Chi for neurological involved patients21,22. Bayraktar et al. showed positive effects of 8 weeks of Ai Chi training on muscle strength, muscle endurance, functional mobility, and fatigue severity in patients with multiple sclerosis26. Noh et al. found that the balance performance and knee flexors strength improved more in the Ai Chi combining Halliwick therapy group than the conventional physiotherapy group in patients with stroke27. Pérez-de la Cruz et al. also showed the feasibility of Ai Chi on balance and functional capacity for people with Parkinson’s disease28.

Taking together, water-based exercise is beneficial for balance performance in patients with stroke. Ai Chi is a specific water-based exercise which emphasizes the characteristics of balance control. However, whether Ai Chi can exert better effect on balance performance than conventional water-based exercise in people with stroke is not known. The aim of this study was to compare the effects of Ai Chi training with conventional water-based exercise on balance performance in people with stroke. We hypothesized that Ai Chi can result in superior effects on balance control than conventional water-based exercise people with stroke. […]

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[Abstract + References] Vibrotactile cueing using wearable computers for overcoming learned non-use in chronic stroke

ABSTRACT

Outpatient stroke rehabilitation is often lengthy and expensive due to patients’ lack of functional use of the impaired arm outside of the clinic caused by “learned non-use.” Learned non-use is detrimental to stroke recovery, often resulting in chronic disability. To overcome learned non-use, a wearable “personal assistant” solution is proposed that employs ubiquitous cueing to stimulate patient use of the paretic arm while outside of therapy sessions. A pilot user study is presented that evaluated stroke survivors’ tolerance and acceptance of cueing, and the usability of the proposed implementation.

References

  1. V. L. Roger et al., “Heart disease and stroke statistics—2012 update: A report from the American Heart Association,” Circulation, vol. 125, no. 1, pp. e2–e220, Jan. 2012.Google Scholar
  2. E. Taub, J. E. Crago, L. D. Burgio, T. E. Groomes, E. W. Cook, S. C. DeLuca, and N. E. Miller, “An operant approach to rehabilitation medicine: Overcoming learned nonuse by shaping,” J Exp Anal Behav, vol. 61, no. 2, pp. 281–293, Mar. 1994.Google ScholarCross Ref
  3. C. E. Lang et al., “Upper extremity use in people with hemiparesis in the first few weeks after stroke,” Journal of Neurologic Physical Therapy, vol. 31, no. 2, pp. 55–63, Jun. 2007.Google ScholarCross Ref
  4. W. S. Verplanck, “The operant conditioning of human motor behavior,” Psychological Bulletin, vol. 53, no. 1, pp. 70–83, 1956.Google ScholarCross Ref
  5. M. S. Cameirão, S. B. i Badia, E. Duarte, A. Frisoli, and P. F. M. J. Verschure, “The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke,” Stroke, vol. 43, no. 10, pp. 2720–2728, Oct. 2012.Google ScholarCross Ref
  6. J. Lieberman and C. Breazeal, “TIKL: Development of a wearable vibrotactile feedback suit for improved human motor learning,” IEEE Transactions on Robotics, vol. 23, no. 5, pp. 919–926, Oct. 2007. Google ScholarDigital Library
  7. P. Kapur, M. Jensen, L. J. Buxbaum, S. A. Jax, and K. J. Kuchenbecker, “Spatially distributed tactile feedback for kinesthetic motion guidance,” in IEEE Haptics Symposium, pp. 519–526, 2010. Google ScholarDigital Library
  8. T. Markow et al., “Mobile Music Touch: Vibration stimulus in hand rehabilitation,” in International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth), pp. 1–8, 2010.Google Scholar
  9. P. Markopoulos, A. A. A. Timmermans, L. Beursgens, R. van Donselaar, and H. A. M. Seelen, “Us’em: The user-centered design of a device for motivating stroke patients to use their impaired arm-hand in daily life activities,” in Annual Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 5182–5187, 2011.Google Scholar
  10. G. Uswatte, C. Giuliani, C. Winstein, A. Zeringue, L. Hobbs, and S. L. Wolf, “Validity of accelerometry for monitoring real-world arm activity in patients with subacute stroke: Evidence from the extremity constraint-induced therapy evaluation trial,” Archives of Physical Medicine and Rehabilitation, vol. 87, no. 10, pp. 1340–1345, Oct. 2006.Google ScholarCross Ref

via Vibrotactile cueing using wearable computers for overcoming learned non-use in chronic stroke | Proceedings of the 7th International Conference on Pervasive Computing Technologies for Healthcare

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[WEB SITE] Vagal Nerve Stimulation Improves Arm Function After Stroke

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HOUSTON, Texas — An implanted device that stimulates the vagus nerve has shown promising improvement of arm function in stroke patients in a second small clinical study.

While the primary endpoint — change in functional score after 6 weeks of therapy — was not significantly different between treatment groups, the improvement did appear to become significant after a further 60 days of treatment, as did responder rates.

Lead investigator, Jesse Dawson, MD, University of Glasgow, United Kingdom, reported that the group receiving active stimulation with the device showed a 9-point improvement in upper-limb Fugl-Meyer (UEFM) score at this time point.

Dr Jesse Dawson

“All in all, we feel this is quite promising,” Dr Dawson said. “A 9-point change in this scale is highly likely to be clinically significant.”

This magnitude of change would mean different things for different patients, depending on where they start, he said. “If they start at 20 — which is not much function at all — they might regain some grasp ability so they might be able to carry a plate, for example. If they were in the 30s to start with, they would probably already have the grasp function but they would be able to get back to do more specific tasks.”

The results were presented here at the International Stroke Conference (ISC) 2017.

“Spectacular” Results

Commenting on the study, American Heart Association/American Stroke Association spokesperson, Philip Gorelick, MD, MPH, medical director, Hauenstein Neuroscience Center, Grand Rapids, Michigan, described the results as “pretty spectacular.”

Dr Philip Gorelick

“It is always difficult to know what you are getting with these scales, but when you see jumps like this I think it’s safe to conclude that there is clinical significance. There is probably something real going on,” Dr Gorelick said.

“You must remember that these are chronic patients with moderate to severe arm weakness at 18 months down the line from their stroke,” he added. “We think these patients are finished — they are not going to be doing much with that arm. Obviously this study is exploratory, but this raises a lot of hope.”

A larger trial in 120 patients is now planned.

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[ARTICLE] Relearning functional and symmetric walking after stroke using a wearable device: a feasibility study – Full Text

Abstract

Background

Gait impairment is a common consequence of stroke and typically involves a hemiparetic or asymmetric walking pattern. Asymmetric gait patterns are correlated with decreased gait velocity and efficiency as well as increased susceptibility to serious falls and injuries.

Research Question

This paper presents an innovative device worn on a foot for gait rehabilitation post stroke. The device generates a backward motion to the foot, which is designed to exaggerate the existing step length asymmetry while walking over ground. We hypothesize this motion will decrease gait asymmetry and improve functional walking in individuals with chronic stroke.

Methods

Six participants with chronic stroke, more than one year post stroke, received four weeks of gait training with three sessions per week. Each session included 30 min of walking over ground using the wearable device. Gait symmetry and functional walking were assessed before and after training.

Results

All participants improved step length symmetry, and four participants improved double limb support symmetry. All participants improved on all three functional outcomes (gait velocity, Timed Up and Go Test, and 6-Minute Walk Test), and five participants improved beyond the minimal detectable change or meaningful change in at least one functional outcome.

Conclusion

The results indicate that the presented device may help improve stroke patients’ walking ability and warrant further study. A gait training approach using this new device may enable and expand long-term continuous gait rehabilitation outside the clinic following stroke.

Introduction

Each year approximately 800,000 Americans experience a new or recurrent stroke, and an estimated six million are living with gait impairments from a stroke [1]. One such disability is a ‘hemiparetic’ gait [2], which can be characterized by asymmetries in gait measures such as step length and support times [34]. Hemiparetic gait is correlated with decreased gait velocity [56], reduced walking efficiency [7], increased joint and bodily degradation [8], and increased susceptibility to injuries and falls [910].

While patients and health providers desire effective gait therapy, few effective long-term remedies have been identified. Treatments of gait commonly rely on traditional rehabilitation approaches, such as the Bobath method [1112] and lower limb strength training [1314], to re-train walking patterns. Unfortunately, results are inconsistent across patient populations with these treatment options, and there are not set devices facilitating these treatments. Some other gait correction methods currently being studied include Constraint Induced Movement Therapy [1516], body-weight support [17], robotic [18], functional electrical stimulation [19], transcranial magnetic stimulation [20], and full-body gait exoskeletons [21].

In this paper, we present a novel device (shown in Fig. 1) designed to help individuals post stroke re-learn how to walk with little to no therapeutic infrastructure needed. Unlike many of the existing gait rehabilitation devices, this device is passive, portable, wearable, and does not require any external energy. It functions by moving the nonparetic foot backward while the individual walks over ground [22]. The backward motion of the shoe is generated passively by redirecting the wearer’s downward force during stance phase [23]. Since the motion is generated by the wearer’s force, the person is in control, which allows easier adaptation to the motion, but this also causes the speed to vary slightly from person to person. The generated motion is demonstrated in Fig. 2. A height and weight matched shoe is attached to the paretic foot, but does not generate any motion.

figure1

Photo of the rehabilitative shoe that is worn on the nonparetic foot

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Continue —-> Relearning functional and symmetric walking after stroke using a wearable device: a feasibility study | Journal of NeuroEngineering and Rehabilitation | Full Text

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[ARTICLE] Clinical Practice Guideline to Improve Locomotor Function Following Chronic Stroke, Incomplete Spinal Cord Injury, and Brain Injury

Abstract

Background:

Individuals with acute-onset central nervous system (CNS) injury, including stroke, motor incomplete spinal cord injury, or traumatic brain injury, often experience lasting locomotor deficits, as quantified by decreases in gait speed and distance walked over a specific duration (timed distance). The goal of the present clinical practice guideline was to delineate the relative efficacy of various interventions to improve walking speed and timed distance in ambulatory individuals greater than 6 months following these specific diagnoses.

Methods:

A systematic review of the literature published between 1995 and 2016 was performed in 4 databases for randomized controlled clinical trials focused on these specific patient populations, at least 6 months postinjury and with specific outcomes of walking speed and timed distance. For all studies, specific parameters of training interventions including frequency, intensity, time, and type were detailed as possible. Recommendations were determined on the basis of the strength of the evidence and the potential harm, risks, or costs of providing a specific training paradigm, particularly when another intervention may be available and can provide greater benefit.

Results:

Strong evidence indicates that clinicians should offer walking training at moderate to high intensities or virtual reality–based training to ambulatory individuals greater than 6 months following acute-onset CNS injury to improve walking speed or distance. In contrast, weak evidence suggests that strength training, circuit (ie, combined) training or cycling training at moderate to high intensities, and virtual reality–based balance training may improve walking speed and distance in these patient groups. Finally, strong evidence suggests that body weight–supported treadmill training, robotic-assisted training, or sitting/standing balance training without virtual reality should not be performed to improve walking speed or distance in ambulatory individuals greater than 6 months following acute-onset CNS injury to improve walking speed or distance.

Discussion:

The collective findings suggest that large amounts of task-specific (ie, locomotor) practice may be critical for improvements in walking function, although only at higher cardiovascular intensities or with augmented feedback to increase patient’s engagement. Lower-intensity walking interventions or impairment-based training strategies demonstrated equivocal or limited efficacy.

Limitations:

As walking speed and distance were primary outcomes, the research participants included in the studies walked without substantial physical assistance. This guideline may not apply to patients with limited ambulatory function, where provision of walking training may require substantial physical assistance.

Summary:

The guideline suggests that task-specific walking training should be performed to improve walking speed and distance in those with acute-onset CNS injury although only at higher intensities or with augmented feedback. Future studies should clarify the potential utility of specific training parameters that lead to improved walking speed and distance in these populations in both chronic and subacute stages following injury.

Disclaimer:

These recommendations are intended as a guide for clinicians to optimize rehabilitation outcomes for persons with chronic stroke, incomplete spinal cord injury, and traumatic brain injury to improve walking speed and distance.

TABLE OF CONTENTS

INTRODUCTION AND METHODS

Summary of Action Statements………………………………………………..53

Levels of Evidence and Grade of Recommendations…………………54

Methods………………………………………………………………………………….57

ACTION STATEMENTS AND RESEARCH RECOMMENDATIONS

Action Statements…………………………………………………………………..63

Discussion…………………………………………………………………………….79

Conclusions…………………………………………………………………………..82

Summary of Research Recommendations……………………………….83

ACKNOWLEDGMENTS AND REFERENCES

Acknowledgments…………………………………………………………………84

References……………………………………………………………………………84

TABLES AND FIGURE

Table 1: Levels of Evidence for Studies……………………………………54

Table 2: Standard and Revised Definitions for Recommendations………………..54

Table 3: Example of PICO Search Terms for Strength Training………………….58

Table 4: Survey Results………………………………………………….59

Figure 1: Flow chart for article searches and appraisals…………………….60

Table 5: Final Recommendations for Clinical Practice Guideline on Locomotor Function…..79

APPENDIX: EVIDENCE TABLES

Appendix Table 1: Walking Training at Moderate to High Aerobic Intensities…….91

Appendix Table 2: Walking Training With Augmented Feedback/Virtual Reality…….92

Appendix Table 3: Strength Training……………………………………….93

Appendix Table 4: Cycling and Recumbent Stepping Training……………………94

Appendix Table 5: Circuit and Combined Exercise Training…………………….95

Appendix Table 6A: Balance Training: Sitting/Standing With Altered Feedback/Weight Shift……..96

Appendix Table 6B: Balance Training: Augmented Feedback With Vibration………..97

Appendix Table 6C: Balance Training: Augmented Visual Feedback……………….98

Appendix Table 7: Body Weight–Supported Treadmill Walking………………99

Appendix Table 8: Robotic-Assisted Walking Training………………………..100

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