Posts Tagged UE

[WEB SITE] Vivistim Therapy “Rewires” Brain to Help Move the Arms Post-Stroke

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Study participant Ken Meeks tests the use of Vivistim therapy to help him regain use of his arms after experiencing a stroke following a car accident. (Photo courtesy of Ohio State University Wexner Medical Center)

Study participant Ken Meeks tests the use of Vivistim therapy to help him regain use of his arms after experiencing a stroke following a car accident. (Photo courtesy of Ohio State University Wexner Medical Center)

An experimental treatment called Vivistim therapy is being tested for use with stroke patients to help them regain some function in their arms.

The therapy involves the use of a neurotransmitter implanted just below the skin on the chest during a minimally invasive outpatient surgery. The device is connected to the vagus nerve in the neck, which transmits signals to the brain.

A study being conducted at the Neurological Institute at Ohio State University’s Wexner Medical Center, as well as at other institutions across the United States and in the United Kingdom is investigating whether use of the device along with rehabilitative therapy may help improve patients’ upper limb movement after a stroke, according to a news story from Healthline.

Marcia Brockbrader, MD, PhD, one of the study’s principal investigators, notes that the device may be promising, but it won’t be a quick fix. It doesn’t work on its own, she adds.

“It’s a device that helps the brain get into a state where it can benefit more from therapy. There’s a button that the therapist presses to activate the device as participants do therapy. The intent of the pulse is much like a heart pacer — to pace the brain. It’s about half a second of stimulation. We think that this very brief pulse is like a ‘wake up and pay attention’ to the brain to use what happens next to help relearn how to use a paralyzed limb,” she explains.

Bockbrader states this trial is focusing on the upper limbs in part because people need their hands to take care of themselves.

“If you can use your hands, you can do a lot of what you need to do with a wheelchair. If you can’t use your hands, you need people around to help more,” she says.

According to the news story, 13 institutions in the United States and five institutions in the United Kingdom are participating in this trial, and they are still seeking participants.

“We’re looking at people in the chronic phase of stroke because it gives them the chance to recover naturally as much as possible,” Bockbrader states.

The typical participant is about 9 months out from a stroke and has done all the therapies they’re eligible for. In addition, per the news story, researchers are choosing a middle-of-the-road impaired population who can flex and extend the wrist and move the thumb, but can’t use their hands the way they should for daily living.

“This suggests to us that connections between the arm and the brain are still there but not working at 100 percent efficiency. There’s still room for improvement. If the device is found to be effective, we can start looking at whether it can be beneficial for those more severely affected by stroke. It’s early on in the evaluation process,” Bockbrader shares.

Recruitment will probably continue for the next 2 years.

Bockbrader says the study is a complicated three-phase design. The initial two phases can last up to a year and a half.

“But if people choose to, we will keep the stimulator in and follow them yearly after that. There’s no end in sight for people who want to keep the stimulator in place and feel it’s helping. If they don’t, removal is a short outpatient surgery,” she notes.

Patients interested in participating in the study should contact the recruitment office at their nearest participating institution, according to the news story.

[Source: Healthline]

via Vivistim Therapy “Rewires” Brain to Help Move the Arms Post-Stroke – Rehab Managment

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[ARTICLE] FES-UPP: A Flexible Functional Electrical Stimulation System to Support Upper Limb Functional Activity Practice – Full Text

There is good evidence supporting highly intensive, repetitive, activity-focused, voluntary-initiated practice as a key to driving recovery of upper limb function following stroke. Functional electrical stimulation (FES) offers a potential mechanism to efficiently deliver this type of therapy, but current commercial devices are too inflexible and/or insufficiently automated, in some cases requiring engineering support. In this paper, we report a new, flexible upper limb FES system, FES-UPP, which addresses the issues above. The FES-UPP system consists of a 5-channel stimulator running a flexible FES finite state machine (FSM) controller, the associated setup software that guides therapists through the setup of FSM controllers via five setup stages, and finally the Session Manager used to guide the patient in repeated attempts at the activities(s) and provide feedback on their performance. The FSM controller represents a functional activity as a sequence of movement phases. The output for each phase implements the stimulations to one or more muscles. Progression between movement phases is governed by user-defined rules. As part of a clinical investigation of the system, nine therapists used the FES-UPP system to set up FES-supported activities with twenty two patient participants with impaired upper-limbs. Therapists with little or no FES experience and without any programming skills could use the system in their usual clinical settings, without engineering support. Different functional activities, tailored to suit the upper limb impairment levels of each participant were used, in up to 8 sessions of FES-supported therapy per participant. The efficiency of delivery of the therapy using FES-UPP was promising when compared with published data on traditional face-face therapy. The FES-UPP system described in this paper has been shown to allow therapists with little or no FES experience and without any programming skills to set up state-machine FES controllers bespoke to the patient’s impairment patterns and activity requirements, without engineering support. The clinical results demonstrated that the system can be used to efficiently deliver high intensity, activity-focused therapy. Nevertheless, further work to reduce setup time is still required.

Introduction

In the United Kingdom there are more than 100,000 new stroke cases each year and approximately 1.2 million people living with the consequences of stroke (Stroke Association, 2017). In the United Kingdom, during their entire in-patient stay, a typical patient will receive around 5 h of physiotherapy (McHugh and Swain, 2014), with much of that time focused on the rehabilitation of posture, balance and walking (Wit et al., 2005). The consequences of this are that patients do not receive anything approaching the intensity of upper limb therapy that research suggests is needed to drive functional recovery (Clarke et al., 2015). Possibly as a result, long term recovery of the upper limb remains very poor. Almost three quarters of stroke survivors are left with upper limb motor problems (Lawrence et al., 2001), which seriously impact on their quality of life.

There is strong evidence supporting intensive (Lohse et al., 2014), repetitive, activity-focused (Winstein et al., 2004Alon et al., 2007Langhorne et al., 2009), voluntary-initiated (Peckham and Knutson, 2005Knutson et al., 2009) practice for upper limb functional recovery. However, to enable such an approach, without significantly increasing the number of therapists, we need to look to rehabilitation technologies.

A number of rehabilitation technologies have been developed to encourage the recovery of upper limb motor function after stroke, including robotic devices, virtual reality and functional electrical stimulation (FES) systems (Howlett et al., 2015). Studies have shown positive results for FES in the rehabilitation of reaching and grasping function (Thrasher et al., 2008Knutson et al., 2009), elbow extension (Thrasher et al., 2008Hughes et al., 2010), shoulder motion (Hara et al., 2009), and stabilization of wrist joints (Malešević et al., 2012). In addition, FES offers the potential to increase therapy dose at a reasonable cost (Kitago and Krakauer, 2013), in a way that does not need the dedicated attention of a therapist.

Current upper limb FES systems can be categorized according to the methods of control over stimulation. The first group of systems use a push button operated by the patient’s unaffected hand, and/or are pre-programmed to repeat a fixed sequence of timed stimulations (Mann et al., 2005). Commercial systems of this type, which tend to be used largely for passive exercising, include Odstock Medical’s Microstim 2 and 4 Channel Stimulator Kit, and the Bioness H200. The Odstock 2 and 4 channel stimulators offer flexibility over which muscles are stimulated; the H200 (Snoek et al., 2000) offers 5 channels of stimulation, but is limited to stimulation of hand and wrist. Previous studies have suggested that cyclical stimulation is less clinically effective than voluntary triggered stimulation (de Kroon et al., 2005), although debate on this issue continues (Wilson et al., 2016). A recent report identified that the carryover, or therapeutic effect, in drop foot patients was only observed in patients who showed brain activation patterns consistent with movement planning (Gandolla et al., 2016). This supports Rushton’s hypothesis (Rushton, 2003) which proposed that when the F wave resulting from stimulation coincides with voluntary intention to move, connectivity between the intact upper motor and lower motor neurons is strengthened at the spinal cord level. These studies suggest that stimulation delivered without the active involvement of the patient may not be the most effective approach.

The second group of systems attempt to ensure that stimulation coincides with voluntary intention to move; thus increasing the likelihood of effective motor relearning. Examples of systems which use voluntary initiated neural signals to control FES include the EMG-based MeCFES (Thorsen et al., 2001) and STIWELL med4 (Rakos et al., 2007) systems and a small number of demonstrator projects which use brain-computer interface approaches (Müller-Putz et al., 2005Ajiboye et al., 2017). However, reliable surface EMG signal(s) from appropriate muscles are frequently either difficult to measure or absent in people with paretic upper limbs (Bolton et al., 2004Gazzoni, 2010), making EMG-controlled FES difficult to use with certain patients. Additionally, the voluntary effort in producing an EMG signal can increase spasticity, opposing the movement that is intended. Although systems using brain-implanted electrodes have been reported, most of the current EEG controlled systems use non-invasive electrodes, which provide limited information transfer rate, require patients to complete a significant amount of training prior to first use (Scherberger, 2009Bouton et al., 2016), and need frequent re-calibration (Ajiboye et al., 2017).

Motion-controlled FES systems offer an attractive alternative (Mann et al., 2011Sun et al., 2016a,b). An example of a motion controlled system is the Bionic Glove (Prochazka et al., 1997) which uses data from a wrist position sensor to control stimulation of hand and wrist muscles in C6/7 spinal cord injury (SCI) patients. More recently, the Southampton group have reported on a system based on iterative learning control (Meadmore et al., 2014) in which stimulation is applied to the triceps, anterior deltoid and wrist/finger extensors muscles to support specified reaching activities. Stimulation levels are adjusted cycle-to-cycle based on kinematic data collected from previous attempts in such a way that the patient is always challenged. These motion controlled FES systems have the potential to deliver appropriately timed neural inputs to promote re-learning and hence recovery (Rushton, 2003Sheffler and Chae, 2007) and recent studies have reported positive results (Knutson et al., 2012Meadmore et al., 2014), including sustained improvements in function (Persch et al., 2012), and improvements even in patients with severe hand arm paralysis (Popovic et al., 2005Thrasher et al., 2008). However, these systems are generally inflexible in terms of the number and location of muscles to be stimulated (Snoek et al., 2000Alon and McBride, 2003Mann et al., 2011) and/or require engineering support to accommodate a wide range of upper limb activities (Tresadern et al., 2008). Relatively little attention has been paid to the development of easy to use, flexible systems able to support a range of patients in practicing varied, yet challenging functional activities (Rakos et al., 2007Tresadern et al., 2008). In particular, if such systems are to be widely adopted, they must be sufficiently user-friendly to remove the need for routine engineering support.

In this paper, we report on a new, flexible upper limb FES system, FES-UPP, which address the issues discussed above. Below we report on the design of the upper limb FES controller and the setup software. Finally, we show data from a clinical investigation study of the system carried out without on-site engineering support to illustrate the potential for the system to be used in the delivery of intensive FES-supported practice.[…]

 

Continue —-> Frontiers | FES-UPP: A Flexible Functional Electrical Stimulation System to Support Upper Limb Functional Activity Practice | Neuroscience

FIGURE 1. Example set-up of the FES-UPP system for the “Sweeping coins” activity. (A) Anterior view; and (B) Lateral view (informed consent was obtained from all participants).

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[VIDEO] MOTORE++ – A new Rehabilitation Robot for the upper limb – YouTube

ECHORD Plus PlusΔημοσιεύτηκε στις 12 Μαΐ 2017
The goal of this experiment was to continue the development of a rehabilitation robot named MOTORE to restore upper limb functionality. MOTORE++ improved the existing MOTORE rehabilitation device by improving the system to the level which is required for commercialization: it works without any links or wire and it is the first robot small enough to be easily carried and as such suitable for in-home rehabilitation. A proprietary software was developed with several exercises and a wide range of exercise parameters. Moreover, a patient database permits the customization of the therapy. The commercial application of this technological development will allow building smaller and lighter robotic systems which are able to interact with patients in hospitals, in retirement homes or are even suitable for in-home therapy. The improved prototype was tested in home-based rehabilitation sessions.

via MOTORE++ – A new Rehabilitation Robot for the upper limb – YouTube

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[Abstract] Design and Development of a Robot Guided Rehabilitation Scheme for Upper Extremity Rehabilitation

Abstract

To rehabilitate individuals with impaired upper-limb function, we have designed and developed a robot guided rehabilitation scheme. A humanoid robot, NAO was used for this purpose. NAO has 25 degrees of freedom. With its sensors and actuators, it can walk forward and backward, can sit down and stand up, can wave his hand, can speak to the audience, can feel the touch sensation, and can recognize the person he is meeting. All these qualities have made NAO a perfect coach to guide the subjects to perform rehabilitation exercises. To demonstrate rehabilitation exercises with NAO, a library of recommended rehabilitation exercises involving shoulder (i.e., abduction/adduction, vertical flexion/extension, and internal/external rotation), and elbow (i.e., flexion/extension) joint movements was formed in Choregraphe (graphical programming interface). In experiments, NAO was maneuvered to instruct and demonstrate the exercises from the NRL. A complex ‘touch and play’ game was also developed where NAO plays with the subject that represents a multi-joint movement’s exercise. To develop the proposed tele-rehabilitation scheme, kinematic model of human upper-extremity was developed based modified Denavit-Hartenberg notations. A complete geometric solution was developed to find a unique inverse kinematic solution of human upper-extremity from the Kinect data. In tele-rehabilitation scheme, a therapist can remotely tele-operate the NAO in real-time to instruct and demonstrate subjects different arm movement exercises. Kinect sensor was used in this scheme to get tele-operator’s kinematics data. Experiments results reveals that NAO can be tele-operated successfully to instruct and demonstrate subjects to perform different arm movement exercises. A control algorithm was developed in MATLAB for the proposed robot guided supervised rehabilitation scheme. Experimental results show that the NAO and Kinect sensor can effectively be used to supervise and guide the subjects in performing active rehabilitation exercises for shoulder and elbow joint movements.

Recommended Citation
Assad-Uz-Zaman, Md, “Design and Development of a Robot Guided Rehabilitation Scheme for Upper Extremity Rehabilitation” (2017). Theses and Dissertations. 1578.
https://dc.uwm.edu/etd/1578

via “Design and Development of a Robot Guided Rehabilitation Scheme for Upp” by Md Assad-Uz-Zaman

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[Abstract + References] Virtual Rehabilitation System for Fine Motor Skills Using a Functional Hand Orthosis –

Abstract

This article describes a virtual rehabilitation system with work and entertainment environments to treat fine motor injuries through an active orthosis. The system was developed in the Unity 3D graphic engine, which allows the patient greater immersion in the rehabilitation process through proposed activities; to identify the movement performed, the Myo armband is used, a device capable of receiving and sending the signals obtained to a mathematical algorithm which will classify these signals and activate the physical hand orthosis completing the desired movement. The benefits of the system is the optimization of resources, infrastructure and personnel, since the therapy will be assisted by the same virtual environment, in addition it allows selecting the virtual environment and the activity to be carried out according to the disability present in the patient. The results show the correct functioning of the system performed.

References

1.
Sanchez, J.S., et al.: Virtual Rehabilitation System for Carpal Tunnel Syndrome Through Spherical Robots. Accepted 2014
Google Scholar
2.
Naiker, A.: Repetitive Strain Injuries (RSI) – an ayurvedic approach. J. Ayurveda Integr. Med. Sci. 2(2), 170–173 (2017). ISSN 2456-3110
Google Scholar
3.
Rosales, R.S., Martin-Hidalgo, Y., Reboso-Morales, L., Atroshi, I.: Reliability and construct validity of the Spanish version of the 6-item CTS symptoms scale for outcomes assessment in carpal tunnel syndrome. BMC Musculoskelet. Disord. 17, 115 (2016)
CrossRefGoogle Scholar
4.
Uehli, K., et al.: Sleep problems and work injuries: a systematic review and meta-analysis. Sleep Med. Rev. 18(1), 61–73 (2014)
CrossRefGoogle Scholar
5.
Patti, F., et al.: The impact of outpatient rehabilitation on quality of life in multiple sclerosis. J. Neurol. 249(8), 1027–1033 (2002)
CrossRefGoogle Scholar
6.
Ueki, S., et al.: Development of a hand-assist robot with multi-degrees-of-freedom for rehabilitation therapy. IEEEASME Trans. Mechatron. 17(1), 136–146 (2012)
CrossRefGoogle Scholar
7.
Chang, W.H., Kim, Y.-H.: Robot-assisted therapy in stroke rehabilitation. J. Stroke 15(3), 174–181 (2013)
CrossRefGoogle Scholar
8.
Laver, K., George, S., Thomas, S., Deutsch, J.E., Crotty, M.: Virtual reality for stroke rehabilitation. Stroke 43(2), e20–e21 (2012)
CrossRefGoogle Scholar
9.
Lohse, K.R., Hilderman, C.G.E., Cheung, K.L., Tatla, S., der Loos, H.F.M.V.: Virtual reality therapy for adults post-stroke: a systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS ONE 9(3), e93318 (2014)
CrossRefGoogle Scholar
10.
North, M.M., North, S.M., Coble, J.R.: Virtual reality therapy: an effective treatment for the fear of public speaking. Int. J. Virtual Real. IJVR 03(3), 1–6 (2015)
Google Scholar
11.
Turolla, A., et al.: Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J. Neuroeng. Rehabil. 10, 85 (2013)
CrossRefGoogle Scholar
12.
Romero, P., León, A., Arteaga, O., Andaluz, V.H., Cruz, M.: Composite materials for the construction of functional orthoses. Accepted 2017
Google Scholar
13.
Benalcázar, M.E., Jaramillo, A.G., Jonathan, A., Zea, A., Páez, V.H.: Andaluz: hand gesture recognition using machine learning and the Myo armband. In: 2017 25th European Signal Processing Conference (EUSIPCO), pp. 1040–1044 (2017)
Google Scholar
14.
Maroukis, B.L., Chung, K.C., MacEachern, M., Mahmoudi, E.: Hand trauma care in the united states: a literature review. Plast. Reconstr. Surg. 137(1), 100e–111e (2016)
CrossRefGoogle Scholar
15.
Feron, L.O., Boniatti, C.M., Arruda, F.Z., Butze, J., Conde, A.: lesões por esforço repetitivo em cirurgiões-dentistas: uma revisão da literatura. Rev. Ciênc. Saúde 16(2), 79–86 (2014)
Google Scholar
16.
Putz-Anderson, V.: Cumulative Trauma Disorders. CRC Press, Boca Raton (2017)
Google Scholar
17.
Oktayoglu, P., Nas, K., Kilinç, F., Tasdemir, N., Bozkurt, M., Yildiz, I.: Assessment of the presence of carpal tunnel syndrome in patients with diabetes mellitus, hypothyroidism and acromegaly. J. Clin. Diagn. Res. JCDR 9(6), OC14–OC18 (2015)
Google Scholar
18.
Villafañe, J., Cleland, J., Fernánde-de-las-Peñas, C.: the effectiveness of a manual therapy and exercise protocol in patients with thumb carpometacarpal osteoarthritis: a randomized controlled trial. J. Orthop. Sports Phys. Ther. 43(4), 204–213 (2013)
CrossRefGoogle Scholar
19.
Langer, D., Maeir, A., Michailevich, M., Applebaum, Y., Luria, S.: Using the international classification of functioning to examine the impact of trigger finger. Disabil. Rehabil. 38(26), 2530–2537 (2016)
CrossRefGoogle Scholar
20.
da Silva Dulci Medeiros, M., Santana, D.V.G., de Souza, G.D., Souza, L.R.Q.: Tenossinovite de Quervain: aspectos diagnósticos. Rev. Med. E Saúde Brasília 5(2), 307–312 (2016)
Google Scholar
21.
Werthel, J.-D., Cortez, M., Elhassan, B.T.: Modified percutaneous trigger finger release. Hand Surg. Rehabil. 35(3), 179–182 (2016)
CrossRefGoogle Scholar
22.
Chang, K.-H.: Motion Simulation and Mechanism Design with SOLIDWORKS Motion 2016. SDC Publications (2016)
Google Scholar
23.
Andaluz, V.H., Pazmiño, A.M., Pérez, J.A., Carvajal, C.P., Lozada, F., Lascano, J., Carvajal, J.: Training of tannery processes through virtual reality. In: De Paolis, L.T., Bourdot, P., Mongelli, A. (eds.) AVR 2017. LNCS, vol. 10324, pp. 75–93. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-60922-5_6
CrossRefGoogle Scholar

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[Abstract + References] Virtual System Using Haptic Device for Real-Time Tele-Rehabilitation of Upper Limbs – Conference paper

Abstract

This paper proposes a tool to support the rehabilitation of upper limbs assisted remotely, which makes it possible for the physiotherapist to be able to assist and supervise the therapy to patients who can not go to rehabilitation centers. This virtual system for real-time tele-rehabilitation is non-invasive and focuses on involving the patient with mild or moderate mobility alterations within a dynamic therapy based on virtual games; Haptics Devices are used to reeducate and stimulate the movement of the upper extremities, at the same time that both motor skills and Visual-Motor Integration skills are developed. The system contains a virtual interface that emulates real-world environments and activities. The functionality of the Novint Falcon device is exploited to send a feedback response that corrects and stimulates the patient to perform the therapy session correctly. In addition, the therapy session can vary in intensity through the levels presented by the application, and the amount of time, successes and mistakes made by the patient are registered in a database. The first results show the acceptance of the virtual system designed for real-time tele-rehabilitation.

References

  1. 1.
    Ingram, T.T.S.: A historical review of the definition of cerebral palsy, the epidemiology of the cerebral palsies. In: Stanley, F.A.E. (ed.) The Epidemiology of the Cerebral Palsies, pp. 1–11. Lippincott, Philadelphia (1984)Google Scholar
  2. 2.
    Jones, M.W., Morgan, E., Shelton, J.E., Thorogood, C.: Cerebral palsy: introduction and diagnosis (part I). J. Pediatr. Health Care 21(3), 146–152 (2007)CrossRefGoogle Scholar
  3. 3.
    Aicardi, J.: Disease of the Nervous System in Childhood. MacKeith Press, London (1992)Google Scholar
  4. 4.
    Feldman, H.M., Chaves-Gnecco, D., Hofkosh, D.: Developmental-behavioral pediatrics. In: Zitelli, B.J., McIntire, S.C., Norwalk, A.J. (eds.) Atlas of Pediatric Diagnosis, Chap. 3, 6th edn. Elsevier Saunders, Philadelphia (2012)Google Scholar
  5. 5.
    Ketelaar, M., Vermeer, A., Hart, H., et al.: Effects of a functional therapy program on motor abilities of children with cerebral palsy. Phys. Ther. 81, 1534–1545 (2001)CrossRefGoogle Scholar
  6. 6.
    Taub, E., Ramey, S., DeLuca, S., Echols, K.: Efficacy of constraint-induced movement therapy for children with cerebral palsy with asymmetric motor impairment. Pediatrics 113, 305–312 (2004)CrossRefGoogle Scholar
  7. 7.
    Sakzewski, L., Ziviani, J., Boyd, R.N.: Efficacy of upper limb therapies for unilateral cerebral palsy: a meta-analysis. Pediatrics 133(1), e175–e204 (2014)CrossRefGoogle Scholar
  8. 8.
    Galil, A., Carmel, S., Lubetzky, H., Heiman, N.: Compliance with home rehabilitation therapy by parents of children with disabilities in Jews and Bedouin in Israel. Dev. Med. Child Neurol. 43(4), 261–268 (2001)CrossRefGoogle Scholar
  9. 9.
    De Campos, A.C., da Costa, C.S., Rocha, N.A.: Measuring changes in functional mobility in children with mild cerebral palsy. Dev. Neurorehabil. 14, 140–144 (2011)CrossRefGoogle Scholar
  10. 10.
    Prosser, L.A., Lee, S.C., Barbe, M.F., VanSant, A.F., Lauer, R.T.: Trunk and hip muscle activity in early walkers with and without cerebral palsy – a frequency analysis. J. Electromyogr. Kinesiol. 20, 851–859 (2010)CrossRefGoogle Scholar
  11. 11.
    Weiss, P.L.T., Tirosh, E., Fehlings, D.: Role of virtual reality for cerebral palsy management. J. Child Neurol. 29(8), 1119–1124 (2014). 0883073814533007CrossRefGoogle Scholar
  12. 12.
    Mitchell, L., Ziviani, J., Oftedal, S., Boyd, R.: The effect of virtual reality interventions on physical activity in children and adolescents with early brain injuries including cerebral palsy. Dev. Med. Child Neurol. 54, 667–671 (2012)CrossRefGoogle Scholar
  13. 13.
    Snider, L., Majnemer, A., Darsaklis, V.: Virtual reality as a therapeutic modality for children with cerebral palsy. Dev. Neurorehabil. 13, 120–128 (2010)CrossRefGoogle Scholar
  14. 14.
    Chen, Y.P., Lee, S.Y., Howard, A.M.: Effect of virtual reality on upper extremity function in children with cerebral palsy: a meta-analysis. Pediatric Phys. Therapy 26(3), 289–300 (2014)CrossRefGoogle Scholar
  15. 15.
    Golomb, M.R., McDonald, B.C., Warden, S.J., Yonkman, J., Saykin, A.J., Shirley, B., et al.: In-home virtual reality videogame telerehabilitation in adolescents with hemiplegic cerebral palsy. Arch. Phys. Med. Rehabil. 91, 1–8 (2010)CrossRefGoogle Scholar
  16. 16.
    Shin, J., Song, G., Hwangbo, G.: Effects of conventional neurological treatment and a virtual reality training program on eye-hand coordination in children with cerebral palsy. J. Phys. Therapy Sci. 27(7), 2151–2154 (2015).  https://doi.org/10.1589/jpts.27.2151CrossRefGoogle Scholar
  17. 17.
    Chen, Y.P., Kang, L.J., Chuang, T.Y., Doong, J.L., Lee, S.J., Tsai, M.W., Sung, W.H.: Use of virtual reality to improve upper-extremity control in children with cerebral palsy: a single-subject design. Phys. Therapy 87(11), 1441–1457 (2007)CrossRefGoogle Scholar
  18. 18.
    Bortone, I., Leonardis, D., Solazzi, M., Procopio, C., Crecchi, A., Bonfiglio, L., Frisoli, A.: Integration of serious games and wearable haptic interfaces for Neuro Rehabilitation of children with movement disorders: a feasibility study. In: 2017 International Conference on Rehabilitation Robotics (ICORR), pp. 1094–1099. IEEE, July 2017Google Scholar
  19. 19.
    Gupta, A., O’Malley, M.K.: Design of a haptic arm exoskeleton for training and rehabilitation. IEEE/ASME Trans. Mechatron. 11(3), 280–289 (2006)CrossRefGoogle Scholar
  20. 20.
    Kozhaeva, T., Zhestkov, S., Bulakh, D., Houlden, N.: Programmable gesture manipulator for hand injuries rehabilitation. In: Internet Technologies and Applications (ITA), pp. 134–136. IEEE, September 2017Google Scholar
  21. 21.
    Pruna, E., et al.: 3D virtual system using a haptic device for fine motor rehabilitation. In: Rocha, Á., Correia, A.M., Adeli, H., Reis, L.P., Costanzo, S. (eds.) WorldCIST 2017. AISC, vol. 570, pp. 648–656. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-56538-5_66CrossRefGoogle Scholar
  22. 22.
    Bortone, I., Leonardis, D., Solazzi, M., Procopio, C., Crecchi, A., Briscese, L., Andre, P., Bonfiglio, L., Frisoli, A.: Serious game and wearable haptic devices for neuro motor rehabilitation of children with cerebral palsy. In: Converging Clinical and Engineering Research on Neurorehabilitation II, pp. 443–447. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-46669-9_74Google Scholar
  23. 23.
    Khor, K.X., Chin, P.J.H., Hisyam, A.R., Yeong, C.F., Narayanan, A.L.T., Su, E.L.M.: Development of CR2-Haptic: a compact and portable rehabilitation robot for wrist and forearm training. In: IEEEIECBES International Conference on Biomedical Engineering and Sciences, pp. 424–429 (2014)Google Scholar
  24. 24.
    Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Troy, A., Leonhardt, S.: A survey on robotic devices for upper limb rehabilitation. J. Neuroeng. Rehabil. 11, 3 (2014)CrossRefGoogle Scholar
  25. 25.
    Lum, P.S., Burgar, C.G., Shor, P.C., Majmundar, M., Van der Loos, M.: Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch. Phys. Med. Rehabil. 83, 952–959 (2002)CrossRefGoogle Scholar

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[Abstract] Within-session effects of selected physical rehabilitation interventions for a dysfunctional arm post-stroke on arm movement and muscle firing patterns

Introduction/Background

Upper extremity (UE) impairments and activity limitations are a common problem in individuals following a cerebrovascular accident (CVA). Eighty-five percent of individuals with CVA report UE functional limitations that are associated with decreased health-related quality of life. Occupational therapy (OT) and physical therapy (PT) approaches are typically aimed to treat impairments, activity limitations, and participation restrictions following a CVA. This study examines the effects of five therapeutic approaches on upper extremity (UE) movement and muscle activation patterns in persons with CVAs: (1) proprioceptive neuromuscular facilitation (PNF); (2) neurodevelopmental treatment (NDT); (3) functional electrical stimulation (FES); (4) weight-bearing and (5) modified Constraint-Induced Movement Therapy (mCIMT).

Material and method

This is a case report involving a 61-year-old male who underwent 30-minute intervention sessions for each approach stated above. Electromyography (EMG) and 3D motion capture data were collected pre- and post-intervention and at 30 minute follow-up. Data were analyzed for reaching a cup at waist level, maximum shoulder flexion, and moving cup to mouth as in drinking.

Results

No significant differences were seen for UE movements across all interventions for kinematic or EMG data. There appears to be a trend towards normal elbow movement following NMES, mCIMT and PNF and increased variability in shoulder flexion in mCIMT and NDT interventions. Weight-bearing provided the least amount of evidence for improved kinematic motion. Improvement in elbow kinematics may indicate proximal stability following PNF, FES, and mCIMT allows for increased distal mobility at the elbow.

Conclusion

Some interventions produced trends that indicate better UE movement. Increased proximal stability may have caused better distal mobility as shown by improved elbow movement. Increased variability of shoulder flexion may indicate the participant learned different options to perform the same movement. Further research is needed o provide a more transparent understanding of the efficacy of interventions for individuals with hemiparesis following a CVA.

 

via Within-session effects of selected physical rehabilitation interventions for a dysfunctional arm post-stroke on arm movement and muscle firing patterns – ScienceDirect

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[Abstract] EEG predicts upper limb motor improvement after robotic rehabilitation in chronic stroke patients

Introduction/Background

Robotic rehabilitation is known to be at least as effective as conventional training for upper limb motor recovery after stroke; nevertheless, which patients could benefit from this treatment is unknown and finding markers that could predict rehabilitation outcome is a challenge.

We aimed at understanding the neural mechanisms of motor function recovery after upper limb robotic rehabilitation in chronic stroke patients using neurophysiological markers obtained by electroencephalography recording (EEG).

Material and method

Fourteen chronic stroke patients (M/F: 11/3; 59.5 ± 13 yrs) with mild to moderate upper limb paresis were subjected to 10 sessions of upper limb rehabilitation with a planar mobile robotic device (MOTORE, Humanware). Fugl–Meyer Assessment Scale (FMAS) and Wolf Motor Function Test (WMFT) were administered before (t0), at the end (t1) and at 1 month follow-up (t2); at the same timing 64-channals EEG was recorded.

We analyzed power spectrum density in different frequency bands of the affected and unaffected hemispheres with 64-ch EEG and their correlation with motor impairment as measured by clinical scales. Correlation analyses were performed to identify the indicators of good rehabilitative outcome.

Results

Clinical assessment indicated a significant functional improvement in upper limb motor function at the end of rehabilitation as assessed with FMAS and WMFT score that is maintained at follow-up. We found a positive correlation between global Alpha activity at t0 and WMFT score variation (t0–t1) and between global Beta activity at t0 and WMFT time variation (t0–t1) and a positive correlation between Beta activity at t0 in the unaffected hemisphere and FMAS variation (t0–t1 and t0–t2).

Conclusion

Robotic rehabilitation improves upper limb motor performance in stroke patients even in the chronic phase. The amount of Alpha and Beta band power at t0 is suggestive of rehabilitation-related motor outcome. Our results suggest that EEG recording preliminarily to robotic rehabilitation could help identifying good responders to treatment thus optimizing results.

 

via EEG predicts upper limb motor improvement after robotic rehabilitation in chronic stroke patients – ScienceDirect

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[Abstract] Hybrid robotic system combining passive exoskeleton and functional electrical stimulation for upper limb stroke rehabilitation: Preliminary results of the retrainer multi-center randomized controlled trial

Introduction/Background

Stroke is the main cause of acquired adult disability with major impact on arm function. The combined use of Functional Electrical Stimulation (FES) and robotic technologies is strongly advocated to improve rehabilitation outcomes after stroke. We present the preliminary data of a multi-center Randomized Controlled Trial aimed at evaluating the effectiveness of this system with respect to conventional therapy for sub-acute stroke upper limb rehabilitation.

Material and method

The RETRAINER system consists of a lightweight and non-cumbersome passive arm exoskeleton for weight relief, a current-controlled stimulator with 2 channels of stimulation and 2 channels of EMG recordings.

In this work we are presenting the preliminary results of 39 sub-acute stroke patients with a distance from the acute event between two weeks and nine months. The inclusion criteria was: age between 18 and 85 years, Motricity Index (MI) < 80%, muscular activity for arm and shoulder at least 1 Medical Research Council (MRC) with a visible contraction, no joint limitation, pain or spasticity. They were randomized in two group: 1 conventional rehabilitation methods, 2 experimental group using Retrainer System. Each participant performed 9 weeks of treatment 3 times for week. We measured MI, Action Research Arm Test (ARAT) and Motor Activity Log (MAL) at beginning (T0) and at the end of treatment (T1).

Results

Results are showed in the next Table 1.

Conclusion

Both groups showed statistical improvement in outcome measures. Experimental group showed a statistical better improvement regarding time and group effect.

 

via Hybrid robotic system combining passive exoskeleton and functional electrical stimulation for upper limb stroke rehabilitation: Preliminary results of the retrainer multi-center randomized controlled trial – ScienceDirect

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[Abstract] Upper limb rehabilitation with movement-sound coupling after brain lesions

Introduction/Background

Recent studies showed that auditory feedback, sound and music can improve upper limb motor-recovery after stroke or Traumatic Brain Injury. However, the specific influence of different sound features and musical parameters has never been explored in this context. This study designed and tested different patterns of movement-sound coupling (sonification) that could stimulate arm movement during rehabilitation.

Material and method

Five sonification patterns were developed through a participative design process. These included two basic sound parameters, two musical extracts and environmental sounds. Upper limb movement was recorded using three Inertial Measurements Units placed on each upper limb. Movement analysis, sound-movement coupling and sound synthesis were performed using Max/MSP software (Ircam). The experimental protocol included three steps. (1) An interview to evaluate the sound universe of individuals (French Psychomusical Appraisal) and Evaluation of Amusia (Montreal Battery). (2) Sonification of two tasks: functional gestures and elbow extension, compared with the same tasks without sound. The two sides were examined, the less affected first. The IMU data were used to quantify the kinematics of arm movement. (3) A semi-directive interview to provide detail on the participant’s subjective experience.

Results

At this stage, data has been obtained for 9 patients (stroke and TBI) and 7 healthy subjects. The subjective responses were positive, most of patients judged the sonification as interesting and stimulating. Most participants had a preference for environmental sound coupling. The observation of kinematic data showed large inter-individual differences and variable effects of sonification on movement amplitude, smoothness and velocity that varied between sides.

Conclusion

This study has established a novel sonification protocol which may be used to enhance and vary motor rehabilitation tasks. However, further analyses are needed, particularly on symmetry, before concluding on a quantitative effect of sonification. In addition, we need to examine the relationships between quantitative data and participants’ subjective experience.

 

via Upper limb rehabilitation with movement-sound coupling after brain lesions – ScienceDirect

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