[Abstract+References] Restoring Motor Functions After Stroke: Multiple Approaches and Opportunities

More than 1.5 million people suffer a stroke in Europe per year and more than 70% of stroke survivors experience limited functional recovery of their upper limb, resulting in diminished quality of life. Therefore, interventions to address upper-limb impairment are a priority for stroke survivors and clinicians. While a significant body of evidence supports the use of conventional treatments, such as intensive motor training or constraint-induced movement therapy, the limited and heterogeneous improvements they allow are, for most patients, usually not sufficient to return to full autonomy. Various innovative neurorehabNIBSilitation strategies are emerging in order to enhance beneficial plasticity and improve motor recovery. Among them, robotic technologies, brain-computer interfaces, or noninvasive brain stimulation (NIBS) are showing encouraging results. These innovative interventions, such as NIBS, will only provide maximized effects, if the field moves away from the “one-fits all” approach toward a “patient-tailored” approach. After summarizing the most commonly used rehabilitation approaches, we will focus on  and highlight the factors that limit its widespread use in clinical settings. Subsequently, we will propose potential biomarkers that might help to stratify stroke patients in order to identify the individualized optimal therapy. We will discuss future methodological developments, which could open new avenues for poststroke rehabilitation, toward more patient-tailored precision medicine approaches and pathophysiologically motivated strategies.

References

Adeyemo BOSimis MMacea DDFregni F. 2012Systematic review of parameters of stimulation, clinical trial design characteristics, and motor outcomes in non-invasive brain stimulation in stroke. Front Psychiatry 3:88Google Scholar Crossref,

MedlineAltschuler ELWisdom SBStone LFoster CGalasko DLlewellyn DM, and others. 1999Rehabilitation of hemiparesis after stroke with a mirror. Lancet 353(9169):20356Google Scholar CrossrefMedline

Ang KKChua KSPhua KSWang CChin ZYKuah CW, and others. 2015A randomized controlled trial of EEG-based motor imagery brain-computer interface robotic rehabilitation for stroke. Clin EEG Neurosci 46(4):31020Google Scholar Link
Basmajian JVGowland CAFinlayson MAHall ALSwanson LRStratford PW, and others. 1987Stroke treatment: comparison of integrated behavioral-physical therapy vs traditional physical therapy programs. Arch Phys Med Rehabil 68(5 Pt 1):26772Google Scholar Medline
Bergmann TOGroppa SSeeger MMolle MMarshall LSiebner HR2009Acute changes in motor cortical excitability during slow oscillatory and constant anodal transcranial direct current stimulation. J Neurophysiol 102(4):230311Google Scholar CrossrefMedline
Bhagat NAVenkatakrishnan AAbibullaev BArtz EJYozbatiran NBlank AA, and others. 2016Design and optimization of an EEG-based brain machine interface (BMI) to an upper-limb exoskeleton for stroke survivors. Front Neurosci 10:122Google Scholar CrossrefMedline
Birbaumer NMurguialday ARCohen L. 2008Brain-computer interface in paralysis. Curr Opin Neurol 21(6):6348Google Scholar CrossrefMedline
Borich MRWheaton LABrodie SMLakhani BBoyd LA2016Evaluating interhemispheric cortical responses to transcranial magnetic stimulation in chronic stroke: a TMS-EEG investigation. Neurosci Lett618:2530Google Scholar
Brown JALutsep HLWeinand MCramer SC2008Motor cortex stimulation for the enhancement of recovery from stroke: a prospective, multicenter safety study. Neurosurgery 62(Suppl 2):85362Google Scholar CrossrefMedline
Buetefisch CM2015Role of the contralesional hemisphere in post-stroke recovery of upper extremity motor function. Front Neurol 6:214Google Scholar CrossrefMedline
Burke Quinlan EDodakian LSee JMcKenzie ALe VWojnowicz M, and others. 2015Neural function, injury, and stroke subtype predict treatment gains after stroke. Ann Neurol 77(1):13245Google Scholar CrossrefMedline
Butler AJShuster MO’Hara EHurley KMiddlebrooks DGuilkey K. 2013A meta-analysis of the efficacy of anodal transcranial direct current stimulation for upper limb motor recovery in stroke survivors. J Hand Ther 26(2):16270Google Scholar CrossrefMedline
Capogrosso MMilekovic TBorton DWagner FMoraud EMMignardot JB, and others. 2016A brain-spine interface alleviating gait deficits after spinal cord injury in primates. Nature 539(7628):2848Google ScholarCrossrefMedline
Carey JRDeng HGillick BTCassidy JMAnderson DCZhang L, and others. 2014Serial treatments of primed low-frequency rTMS in stroke: characteristics of responders vs. nonresponders. Restor Neurol Neurosci 32(2):32335Google Scholar Medline
Carter ARShulman GLCorbetta M. 2012Why use a connectivity-based approach to study stroke and recovery of function? Neuroimage 62(4):227180Google Scholar CrossrefMedline
Cassidy JMGillick BTCarey JR. 2014Priming the brain to capitalize on metaplasticity in stroke rehabilitation. Phys Ther 94(1):13950Google Scholar CrossrefMedline
Cecere RRees GRomei V. 2015Individual differences in alpha frequency drive crossmodal illusory perception. Curr Biol 25(2):2315Google Scholar CrossrefMedline
Chang WDLai PT2015New design of home-based dynamic hand splint for hemiplegic hands: a preliminary study. J Phys Ther Sci 27(3):82931Google Scholar CrossrefMedline
Chaudhary UBirbaumer NCurado MR2015Brain-machine interface (BMI) in paralysis. Ann Phys Rehabil Med 58(1):913Google Scholar CrossrefMedline
Chechlacz MHumphreys GWSotiropoulos SNKennard CCazzoli D. 2015Structural organization of the corpus callosum predicts attentional shifts after continuous theta burst stimulation. J Neurosci 35(46):1535368Google Scholar CrossrefMedline
Collinger JLWodlinger BDowney JEWang WTyler-Kabara ECWeber DJ, and others. 2013High-performance neuroprosthetic control by an individual with tetraplegia. Lancet 381(9866):55764Google Scholar CrossrefMedline
Conde VVollmann HSehm BTaubert MVillringer ARagert P. 2012Cortical thickness in primary sensorimotor cortex influences the effectiveness of paired associative stimulation. Neuroimage 60(2):86470Google Scholar CrossrefMedline
Corbetta DSirtori VCastellini GMoja LGatti R. 2015Constraint-induced movement therapy for upper extremities in people with stroke. Cochrane Database Syst Rev (10):CD004433Google Scholar Medline
Coupar FPollock ARowe PWeir CLanghorne P. 2012Predictors of upper limb recovery after stroke: a systematic review and meta-analysis. Clin Rehabil 26(4):291313Google Scholar Link
Dahl AEAskim TStock RLangorgen ELydersen SIndredavik B. 2008Short- and long-term outcome of constraint-induced movement therapy after stroke: a randomized controlled feasibility trial. Clin Rehabil 22(5):43647Google Scholar Link
De Vico Fallani FRichiardi JChavez MAchard S2014Graph analysis of functional brain networks: practical issues in translational neuroscience. Philos Trans R Soc Lond B Biol Sci 369(1653):0521Google Scholar Crossref
Di Carlo A2009Human and economic burden of stroke. Age Ageing 38(1):45Google Scholar CrossrefMedline
Dickstein RHocherman SPillar TShaham R. 1986Stroke rehabilitation. Three exercise therapy approaches. Phys Ther 66(8):12338Google Scholar CrossrefMedline
Donati ARShokur SMorya ECampos DSMoioli RCGitti CM, and others. 2016Long-term training with a brain-machine interface-based gait protocol induces partial neurological recovery in paraplegic patients. Sci Rep 6:30383Google Scholar CrossrefMedline
Dromerick AWEdwardson MAEdwards DFGiannetti MLBarth JBrady KP, and others. 2015Critical periods after stroke study: translating animal stroke recovery experiments into a clinical trial. Front Hum Neurosci 9:231Google Scholar CrossrefMedline
Dromerick AWLang CEBirkenmeier RLWagner JMMiller JPVideen TO, and others. 2009Very Early Constraint-Induced Movement during Stroke Rehabilitation (VECTORS): a single-center RCT. Neurology 73(3):195201Google Scholar CrossrefMedline
Duncan PW1997Synthesis of intervention trials to improve motor recovery following stroke. Top Stroke Rehabil 3(4):120Google Scholar CrossrefMedline
Duque JHummel FCelnik PMurase NMazzocchio RCohen LG2005Transcallosal inhibition in chronic subcortical stroke. Neuroimage 28(4):9406Google Scholar CrossrefMedline
Feigin VLNorrving BMensah GA2017Global burden of stroke. Circ Res 120(3):43948Google ScholarCrossrefMedline
Fox MDBuckner RLLiu HChakravarty MMLozano AMPascual-Leone A. 2014Resting-state networks link invasive and noninvasive brain stimulation across diverse psychiatric and neurological diseases. Proc Natl Acad Sci U S A 111(41):E436775Google Scholar CrossrefMedline
Fox MDLiu HPascual-Leone A. 2013Identification of reproducible individualized targets for treatment of depression with TMS based on intrinsic connectivity. Neuroimage 66:15160Google Scholar CrossrefMedline
Friston KJHarrison LPenny W. 2003Dynamic causal modelling. Neuroimage 19(4):1273302Google Scholar CrossrefMedline
Fritz SLLight KEPatterson TSBehrman ALDavis SB2005Active finger extension predicts outcomes after constraint-induced movement therapy for individuals with hemiparesis after stroke. Stroke 36(6):11727Google Scholar CrossrefMedline
Gaggioli AMorganti FWalker RMeneghini AAlcaniz MLozano JA, and others. 2004Training with computer-supported motor imagery in post-stroke rehabilitation. Cyberpsychol Behav 7(3):32732Google Scholar CrossrefMedline
Gamito POliveira JCoelho CMorais DLopes PPacheco J, and others. 2017Cognitive training on stroke patients via virtual reality-based serious games. Disabil Rehabil 39(4):3858Google Scholar CrossrefMedline
Geranmayeh FLeech RWise RJ2016Network dysfunction predicts speech production after left hemisphere stroke. Neurology 86(14):1296305Google Scholar Crossref
Gerardin ESirigu ALehericy SPoline JBGaymard BMarsault C, and others. 2000Partially overlapping neural networks for real and imagined hand movements. Cereb Cortex 10(11):1093104Google Scholar CrossrefMedline
Gharabaghi AKraus DLeao MTSpuler MWalter ABogdan M, and others. 2014a. Coupling brain-machine interfaces with cortical stimulation for brain-state dependent stimulation: enhancing motor cortex excitability for neurorehabilitation. Front Hum Neurosci 8:122Google Scholar CrossrefMedline
Gharabaghi ANaros GWalter AGrimm FSchuermeyer MRoth A and others. 2014b. From assistance towards restoration with epidural brain-computer interfacing. Restor Neurol Neurosci 32(4):51725Google Scholar Medline
Giraux PSirigu A. 2003Illusory movements of the paralyzed limb restore motor cortex activity. Neuroimage 20(Suppl 1):S10711Google Scholar CrossrefMedline
Graef PDadalt MLRodrigues DAStein CPagnussat Ade S. 2016Transcranial magnetic stimulation combined with upper-limb training for improving function after stroke: a systematic review and meta-analysis. J Neurol Sci 369:14958Google Scholar CrossrefMedline
Grefkes CNowak DAEickhoff SBDafotakis MKust JKarbe H, and others. 2008Cortical connectivity after subcortical stroke assessed with functional magnetic resonance imaging. Ann Neurol 63(2):23646Google Scholar CrossrefMedline
Grimm FNaros GGharabaghi A. 2016Closed-loop task difficulty adaptation during virtual reality reach-to-grasp training assisted with an exoskeleton for stroke rehabilitation. Front Neurosci 10:518Google Scholar CrossrefMedline
Groisser BNCopen WASinghal ABHirai KKSchaechter JD2014Corticospinal tract diffusion abnormalities early after stroke predict motor outcome. Neurorehabil Neural Repair 28(8):75160Google Scholar Link
Groppa SOliviero AEisen AQuartarone ACohen LGMall V, and others. 2012A practical guide to diagnostic transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 123(5):85882Google Scholar CrossrefMedline
Hamzei FLiepert JDettmers CWeiller CRijntjes M. 2006Two different reorganization patterns after rehabilitative therapy: an exploratory study with fMRI and TMS. Neuroimage 31(2):71020Google Scholar
Hao ZWang DZeng YLiu M. 2013Repetitive transcranial magnetic stimulation for improving function after stroke. Cochrane Database Syst Rev 5:CD008862Google Scholar
Harris JHebert A. 2015Utilization of motor imagery in upper limb rehabilitation: a systematic scoping review. Clin Rehabil 29(11):1092107Google Scholar Link
Harvey RLWinstein CJ, Everest Trial Group. 2009Design for the everest randomized trial of cortical stimulation and rehabilitation for arm function following stroke. Neurorehabil Neural Repair 23(1):3244Google Scholar Link
Hatem SMSaussez GDella Faille MPrist VZhang XDispa D, and others. 2016Rehabilitation of motor function after stroke: a multiple systematic review focused on techniques to stimulate upper extremity recovery. Front Hum Neurosci 10:442Google Scholar CrossrefMedline
Helfrich RFSchneider TRRach STrautmann-Lengsfeld SAEngel AKHerrmann CS2014Entrainment of brain oscillations by transcranial alternating current stimulation. Curr Biol 24(3):3339Google Scholar CrossrefMedline
Hoffman HBBlakey GL2011New design of dynamic orthoses for neurological conditions. NeuroRehabilitation 28(1):5561Google Scholar Medline
Hoyer EHCelnik PA2011Understanding and enhancing motor recovery after stroke using transcranial magnetic stimulation. Restor Neurol Neurosci 29(6):395409Google Scholar Medline
Huang MHarvey RLStoykov MERuland SWeinand MLowry D, and others. 2008Cortical stimulation for upper limb recovery following ischemic stroke: a small phase II pilot study of a fully implanted stimulator. Top Stroke Rehabil 15(2):16072Google Scholar CrossrefMedline
Hummel FCCelnik PPascual-Leone AFregni FByblow WDBuetefisch CM, and others. 2008Controversy: noninvasive and invasive cortical stimulation show efficacy in treating stroke patients. Brain Stimul 1(4):37082Google Scholar CrossrefMedline
Hummel FCCohen LG2006Non-invasive brain stimulation: a new strategy to improve neurorehabilitation after stroke? Lancet Neurol 5(8):70812Google Scholar CrossrefMedline
Ibrahim IKBerger WTrippel MDietz V. 1993Stretch-induced electromyographic activity and torque in spastic elbow muscles. Differential modulation of reflex activity in passive and active motor tasks. Brain 116(Pt 4):97189Google Scholar CrossrefMedline
Ietswaart MJohnston MDijkerman HCJoice SScott CLMacwalter RS, and others. 2011Mental practice with motor imagery in stroke recovery: randomized controlled trial of efficacy. Brain 134(Pt 5):137386Google Scholar CrossrefMedline
Jackson AMavoori JFetz EE2006Long-term motor cortex plasticity induced by an electronic neural implant. Nature 444(7115):5660Google Scholar CrossrefMedline
Jackson PLLafleur MFMalouin FRichards CDoyon J. 2001Potential role of mental practice using motor imagery in neurologic rehabilitation. Arch Phys Med Rehabil 82(8):113341Google Scholar CrossrefMedline
Jiang RJansen BHSheth BRChen J. 2013Dynamic multi-channel TMS with reconfigurable coil. IEEE Trans Neural Syst Rehabil Eng 21(3):3705Google Scholar CrossrefMedline
Jo JYLee AKim MSPark EChang WHShin YKim YH2016Prediction of motor recovery using quantitative parameters of motor evoked potential in patients with stroke. Ann Rehabil Med 40(5):80615Google Scholar CrossrefMedline
Jongbloed LStacey SBrighton C. 1989Stroke rehabilitation: sensorimotor integrative treatment versus functional treatment. Am J Occup Ther 43(6):3917Google Scholar CrossrefMedline
Kamke MRRyan AESale MVCampbell MERiek SCarroll TJ, and others. 2014Visual spatial attention has opposite effects on bidirectional plasticity in the human motor cortex. J Neurosci 34(4):147580Google Scholar CrossrefMedline
Karabanov AJin SHJoutsen APoston BAizen JEllenstein A, and others. 2012Timing-dependent modulation of the posterior parietal cortex-primary motor cortex pathway by sensorimotor training. J Neurophysiol 107(11):31909Google Scholar CrossrefMedline
Karabanov ASiebner HR2012Unravelling homeostatic interactions in inhibitory and excitatory networks in human motor cortex. J Physiol 590(Pt 22):55578Google Scholar CrossrefMedline
Karabanov AThielscher ASiebner HR2016Transcranial brain stimulation: closing the loop between brain and stimulation. Curr Opin Neurol 29(4):397404Google Scholar CrossrefMedline
Karabanov ANRaffin ESiebner HR2015The resting motor threshold—restless or resting? A repeated threshold hunting technique to track dynamic changes in resting motor threshold. Brain Stimul 8(6):11914Google Scholar CrossrefMedline
Koch PJSchulz RHummel FC2016Structural connectivity analyses in motor recovery research after stroke. Ann Clin Transl Neurol 3(3):23344Google Scholar CrossrefMedline
Koch PJHummel FC2017Toward precision medicine: tailoring interventional strategies based on noninvasive brain stimulation for motor recovery after stroke. Curr Opin Neurol 30(4):38897Google ScholarCrossrefMedline
Kraus DNaros GBauer RLeao MTZiemann UGharabaghi A. 2016Brain-robot interface driven plasticity: distributed modulation of corticospinal excitability. Neuroimage 125:522–-32Google Scholar CrossrefMedline
Kwakkel Gvan Peppen RWagenaar RCWood Dauphinee SRichards CAshburn A, and others. 2004Effects of augmented exercise therapy time after stroke: a meta-analysis. Stroke 35(11):252939Google Scholar CrossrefMedline
Lang CEBland MDBailey RRSchaefer SYBirkenmeier RL2013Assessment of upper extremity impairment, function, and activity after stroke: foundations for clinical decision making. J Hand Ther 26(2):10414Google Scholar CrossrefMedline
Langhorne PLegg L. 2003Evidence behind stroke rehabilitation. J Neurol Neurosurg Psychiatry 74(Suppl 4):iv1821Google Scholar CrossrefMedline
Lannin NACusick AHills CKinnear BVogel KMatthews K, and others. 2016Upper limb motor training using a Saebo orthosis is feasible for increasing task-specific practice in hospital after stroke. Aust Occup Ther J 63(6):364372Google Scholar CrossrefMedline
Laver BDiwan MNobrega JNHamani C. 2014Augmentative therapies do not potentiate the antidepressant-like effects of deep brain stimulation in rats. J Affect Disord 161:8790Google Scholar CrossrefMedline
Lee KBLim SHKim KHKim KJKim YRChang WN and others. 2015Six-month functional recovery of stroke patients: a multi-time-point study. Int J Rehabil Res 38(2):17380Google Scholar CrossrefMedline
Legg LAQuinn TJMahmood FWeir CJTierney JStott DJ and others. 2011Non-pharmacological interventions for caregivers of stroke survivors. Cochrane Database Syst Rev (10):CD008179Google Scholar Medline
Levy RMHarvey RLKissela BMWinstein CJLutsep HLParrish TB, and others. 2016Epidural electrical stimulation for stroke rehabilitation: results of the prospective, multicenter, randomized, single-blinded Everest Trial. Neurorehabil Neural Repair 30(2):10719Google Scholar Link
Li LMUehara KHanakawa T. 2015The contribution of interindividual factors to variability of response in transcranial direct current stimulation studies. Front Cell Neurosci 9:181Google Scholar CrossrefMedline
Li WLi YZhu WChen X. 2014Changes in brain functional network connectivity after stroke. Neural Regen Res 9(1):5160Google Scholar CrossrefMedline
Liew SLRana MCornelsen SFortunato de Barros Filho MBirbaumer NSitaram R, and others. 2016Improving motor corticothalamic communication after stroke using real-time fMRI connectivity-based neurofeedback. Neurorehabil Neural Repair 30(7):6715Google Scholar Link
Lindenberg RRenga VZhu LLBetzler FAlsop DSchlaug G. 2010a. Structural integrity of corticospinal motor fibers predicts motor impairment in chronic stroke. Neurology 74(4):2807Google Scholar CrossrefMedline
Lindenberg RRenga VZhu LLNair DSchlaug G. 2010b. Bihemispheric brain stimulation facilitates motor recovery in chronic stroke patients. Neurology 75(24):217684Google Scholar CrossrefMedline
Lindenberg RZhu LLRuber TSchlaug G. 2012Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging. Hum Brain Mapp 33(5):104051Google Scholar CrossrefMedline
Liu KPChan CCWong RSKwan IWYau CSLi LS and others. 2009A randomized controlled trial of mental imagery augment generalization of learning in acute poststroke patients. Stroke 40(6):22225Google Scholar CrossrefMedline
Lo ACGuarino PDRichards LGHaselkorn JKWittenberg GFFederman DG, and others. 2010Robot-assisted therapy for long-term upper-limb impairment after stroke. N Engl J Med 362(19):177283Google Scholar CrossrefMedline
Lum PSGodfrey SBBrokaw EBHolley RJNichols D. 2012Robotic approaches for rehabilitation of hand function after stroke. Am J Phys Med Rehabil 91(11 Suppl 3):S24254Google Scholar CrossrefMedline
Masiero SCelia ARosati GArmani M. 2007Robotic-assisted rehabilitation of the upper limb after acute stroke. Arch Phys Med Rehabil 88(2):1429Google Scholar CrossrefMedline
Massie CLWhite CPruit KFreel AStaley KBackes M. 2017Influence of motor cortex stimulation during motor training on neuroplasticity as a potential therapeutic intervention. J Mot Behav 49(1):1116Google Scholar CrossrefMedline
McKeown MJHansen LKSejnowsk TJ2003Independent component analysis of functional MRI: what is signal and what is noise? Curr Opin Neurobiol 13(5):6209Google Scholar CrossrefMedline
Memberg WDPolasek KHHart RLBryden AMKilgore KLNemunaitis GA, and others. 2014Implanted neuroprosthesis for restoring arm and hand function in people with high level tetraplegia. Arch Phys Med Rehabil 95(6):12011211.e1Google Scholar CrossrefMedline
Minjoli SSaturnino GBBlicher JUStagg CJSiebner HRAntunes A, and others. 2017The impact of large structural brain changes in chronic stroke patients on the electric field caused by transcranial brain stimulation. Neuroimage Clin 15:10617Google Scholar CrossrefMedline
Morganti FGaggioli ACastelnuovo GBulla DVettorello MRiva G. 2003The use of technology-supported mental imagery in neurological rehabilitation: a research protocol. Cyberpsychol Behav 6(4):4217Google Scholar CrossrefMedline
Morishita THummel FC2017Non-invasive brain stimulation (NIBS) in motor recovery after stroke: concepts to increase efficacy. Curr Behav Neurosci Rep 4:2809Google Scholar Crossref
Mulder T2007Motor imagery and action observation: cognitive tools for rehabilitation. J Neural Transm (Vienna) 114(10):126578Google Scholar CrossrefMedline
Murase NDuque JMazzocchio RCohen LG2004Influence of interhemispheric interactions on motor function in chronic stroke. Ann Neurol 55(3):4009Google Scholar CrossrefMedline
Muratori LMLamberg EMQuinn LDuff SV2013Applying principles of motor learning and control to upper extremity rehabilitation. J Hand Ther 26(2):94102Google Scholar CrossrefMedline
Nakazono HOgata KKuroda TTobimatsu S. 2016Phase and frequency-dependent effects of transcranial alternating current stimulation on motor cortical excitability. PLoS One 11(9):e0162521Google Scholar CrossrefMedline
Naros GGharabaghi A. 2015Reinforcement learning of self-regulated beta-oscillations for motor restoration in chronic stroke. Front Hum Neurosci 9:391Google Scholar CrossrefMedline
Nitsche MACohen LGWassermann EMPriori ALang NAntal A, and others. 2008Transcranial direct current stimulation: state of the art 2008. Brain Stimul 1(3):20623Google Scholar CrossrefMedline
Nouri SCramer SC2011Anatomy and physiology predict response to motor cortex stimulation after stroke. Neurology 77(11):107683Google Scholar CrossrefMedline
Nudo RJ2003Functional and structural plasticity in motor cortex: implications for stroke recovery. Phys Med Rehabil Clin N Am 14(1 Suppl):S5776Google Scholar CrossrefMedline
O’Doherty JELebedev MAHanson TLFitzsimmons NANicolelis MA2009A brain-machine interface instructed by direct intracortical microstimulation. Front Integr Neurosci 3:20Google Scholar CrossrefMedline
Opitz APaulus WWill SAntunes AThielscher A. 2015Determinants of the electric field during transcranial direct current stimulation. Neuroimage 109:14050Google Scholar CrossrefMedline
Page SJLevine PLeonard A. 2007Mental practice in chronic stroke: results of a randomized, placebo-controlled trial. Stroke 38(4):12937Google Scholar CrossrefMedline
Penny WDStephan KEMechelli AFriston KJ2004Modelling functional integration: a comparison of structural equation and dynamic causal models. Neuroimage 23(Suppl 1):S26474Google Scholar CrossrefMedline
Plow EBCarey JRNudo RJPascual-Leone A. 2009Invasive cortical stimulation to promote recovery of function after stroke: a critical appraisal. Stroke 40(5):192631Google Scholar CrossrefMedline
Pollock ABaer GCampbell PChoo PLForster AMorris J, and others. 2014Physical rehabilitation approaches for the recovery of function and mobility following stroke. Cochrane Database Syst Rev (4):CD001920Google Scholar Medline
Posteraro FMazzoleni SAliboni SCesqui BBattaglia ADario P, and others. 2009Robot-mediated therapy for paretic upper limb of chronic patients following neurological injury. J Rehabil Med 41(12):97680Google Scholar CrossrefMedline
Qiu MDarling WGMorecraft RJNi CCRajendra JButler AJ2011White matter integrity is a stronger predictor of motor function than BOLD response in patients with stroke. Neurorehabil Neural Repair 25(3):27584Google Scholar Link
Ramachandran VSRogers-Ramachandran D. 1996Synaesthesia in phantom limbs induced with mirrors. Proc Biol Sci 263(1369):37786Google Scholar CrossrefMedline
Ramos-Murguialday ABroetz DRea MLaer LYilmaz OBrasil FL, and others. 2013Brain-machine interface in chronic stroke rehabilitation: a controlled study. Ann Neurol 74(1):1008Google ScholarCrossrefMedline
Rebesco JMStevenson IHKörding KPSolla SAMiller LE2010Rewiring neural interactions by micro-stimulation. Front Syst Neurosci 4:39Google Scholar CrossrefMedline
Rossi SHallett MRossini PMPascual-Leone A, Safety of TMS Consensus Group. 2009Safety, ethical considerations, and application guidelines for the use of transcranial magnetic stimulation in clinical practice and research. Clin Neurophysiol 120(12):200839Google Scholar CrossrefMedline
Rossiter HEBoudrias MHWard NS2014Do movement-related beta oscillations change after stroke? J Neurophysiol 112(9):20538Google Scholar CrossrefMedline
Ruber TSchlaug GLindenberg R. 2012Compensatory role of the cortico-rubro-spinal tract in motor recovery after stroke. Neurology 79(6):51522Google Scholar CrossrefMedline
Ruffini GFox MDRipolles OMiranda PCPascual-Leone A. 2014Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields. Neuroimage 89:21625Google Scholar CrossrefMedline
Rusjan PMBarr MSFarzan FArenovich TMaller JJFitzgerald PB, and others. 2010Optimal transcranial magnetic stimulation coil placement for targeting the dorsolateral prefrontal cortex using novel magnetic resonance image-guided neuronavigation. Hum Brain Mapp 31(11):164352Google Scholar Medline
Saposnik GCohen LGMamdani MPooyania SPloughman MCheung D, and others. 2016Efficacy and safety of non-immersive virtual reality exercising in stroke rehabilitation (EVREST): a randomised, multicentre, single-blind, controlled trial. Lancet Neurol 15(10):101927Google Scholar CrossrefMedline
Saposnik GLevin M, Outcome Research Canada Working G. 2011Virtual reality in stroke rehabilitation: a meta-analysis and implications for clinicians. Stroke 42(5):13806Google Scholar CrossrefMedline
Sato SBergmann TOBorich MR2015Opportunities for concurrent transcranial magnetic stimulation and electroencephalography to characterize cortical activity in stroke. Front Hum Neurosci 9:250Google ScholarCrossrefMedline
Sauseng PKlimesch WGerloff CHummel FC2009Spontaneous locally restricted EEG alpha activity determines cortical excitability in the motor cortex. Neuropsychologia 47(1):2848Google Scholar CrossrefMedline
Schulz RBraass HLiuzzi GHoerniss VLechner PGerloff C, and others. 2015a. White matter integrity of premotor-motor connections is associated with motor output in chronic stroke patients. Neuroimage Clin 7:826Google Scholar CrossrefMedline
Schulz RFrey BMKoch PZimerman MBonstrup MFeldheim J, and others. 2017a. Cortico-cerebellar structural connectivity is related to residual motor output in chronic stroke. Cereb Cortex 27(1):63545Google Scholar Medline
Schulz RKoch PZimerman MWessel MBonstrup MThomalla G, and others. 2015b. Parietofrontal motor pathways and their association with motor function after stroke. Brain 138(Pt 7):194960Google Scholar CrossrefMedline
Schulz RPark CHBoudrias MHGerloff CHummel FCWard NS2012Assessing the integrity of corticospinal pathways from primary and secondary cortical motor areas after stroke. Stroke 43(8):224851Google Scholar CrossrefMedline
Schulz RPark ELee JChang WHLee AKim YH, and others. 2017b. Synergistic but independent: the role of corticospinal and alternate motor fibers for residual motor output after stroke. Neuroimage Clin 15:11824Google Scholar CrossrefMedline
Shafi MMBrandon Westover MOberman LCash SSPascual-Leone A. 2014Modulation of EEG functional connectivity networks in subjects undergoing repetitive transcranial magnetic stimulation. Brain Topogr 27(1):17291Google Scholar CrossrefMedline
Sitaram RVeit RStevens BCaria AGerloff CBirbaumer N, and others. 2012Acquired control of ventral premotor cortex activity by feedback training: an exploratory real-time FMRI and TMS study. Neurorehabil Neural Repair 26(3):25665Google Scholar Link
Smajlovic D2015Strokes in young adults: epidemiology and prevention. Vasc Health Risk Manag 11:15764Google Scholar CrossrefMedline
Small SLBuccino GSolodkin A. 2012The mirror neuron system and treatment of stroke. Dev Psychobiol 54(3):293310Google Scholar CrossrefMedline
Stevens JAStoykov ME2003Using motor imagery in the rehabilitation of hemiparesis. Arch Phys Med Rehabil 84(7):10902Google Scholar CrossrefMedline
Stinear CMBarber PAPetoe MAnwar SByblow WD2012The PREP algorithm predicts potential for upper limb recovery after stroke. Brain 135(Pt 8):252735Google Scholar CrossrefMedline
Stinear CMByblow WD2014Predicting and accelerating motor recovery after stroke. Curr Opin Neurol 27(6):62430Google Scholar Medline
Stinear CMByblow WDAckerley SJBarber PASmith MC2017Predicting recovery potential for individual stroke patients increases rehabilitation efficiency. Stroke 48(4):10119Google Scholar CrossrefMedline
Strens LHAsselman PPogosyan ALoukas CThompson AJBrown P. 2004Corticocortical coupling in chronic stroke: its relevance to recovery. Neurology 63(3):47584Google Scholar CrossrefMedline
Stuck RAMarshall LMSivakumar R. 2014Feasibility of SaeboFlex upper-limb training in acute stroke rehabilitation: a clinical case series. Occup Ther Int 21(3):10814Google Scholar CrossrefMedline
Takeuchi NIzumi S. 2015Combinations of stroke neurorehabilitation to facilitate motor recovery: perspectives on Hebbian plasticity and homeostatic metaplasticity. Front Hum Neurosci 9:349Google Scholar CrossrefMedline
Tang CZhao ZChen CZheng XSun FZhang X and others. 2016Decreased functional connectivity of homotopic brain regions in chronic stroke patients: a resting state fMRI study. PLoS One 11(4):e0152875Google Scholar CrossrefMedline
Taub EMiller NENovack TACook EW3rdFleming WCNepomuceno CS, and others. 1993Technique to improve chronic motor deficit after stroke. Arch Phys Med Rehabil 74(4):34754Google Scholar Medline
Thut GVeniero DRomei VMiniussi CSchyns PGross J. 2011Rhythmic TMS causes local entrainment of natural oscillatory signatures. Curr Biol 21(14):117685Google Scholar CrossrefMedline
Truelsen TPiechowski-Jozwiak BBonita RMathers CBogousslavsky JBoysen G. 2006Stroke incidence and prevalence in Europe: a review of available data. Eur J Neurol 13(6):58198Google Scholar CrossrefMedline
Turolla ADam MVentura LTonin PAgostini MZucconi C, and others. 2013Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J Neuroeng Rehabil 10:85Google Scholar CrossrefMedline
Uswatte GTaub E. 2013Constraint-induced movement therapy: a method for harnessing neuroplasticity to treat motor disorders. Prog Brain Res 207:379401Google Scholar CrossrefMedline
Van Peppen RPKwakkel GWood-Dauphinee SHendriks HJVan der Wees PJDekker J. 2004The impact of physical therapy on functional outcomes after stroke: what’s the evidence? Clin Rehabil 18(8):83362Google Scholar Link
Varkuti BGuan CPan YPhua KSAng KKKuah CW, and others. 2013Resting state changes in functional connectivity correlate with movement recovery for BCI and robot-assisted upper-extremity training after stroke. Neurorehabil Neural Repair 27(1):5362Google Scholar Link
Veerbeek JMKwakkel Gvan Wegen EEKet JCHeymans MW2011Early prediction of outcome of activities of daily living after stroke: a systematic review. Stroke 42(5):14828Google Scholar
Vourvopoulos ABermudez IBS2016Motor priming in virtual reality can augment motor-imagery training efficacy in restorative brain-computer interaction: a within-subject analysis. J Neuroeng Rehabil 13(1):69Google Scholar CrossrefMedline
Wagner TFregni FEden URamos-Estebanez CGrodzinsky AZahn M, and others. 2006Transcranial magnetic stimulation and stroke: a computer-based human model study. Neuroimage 30(3):85770Google Scholar CrossrefMedline
Westlake KPNagarajan SS2011Functional connectivity in relation to motor performance and recovery after stroke. Front Syst Neurosci 5:8Google Scholar CrossrefMedline
Winstein CJStein JArena RBates BCherney LRCramer SC, and others. 2016Guidelines for adult stroke rehabilitation and recovery: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 47(6):e98e169Google Scholar CrossrefMedline
Wolf SLThompson PAWinstein CJMiller JPBlanton SRNichols-Larsen DS, and others. 2010The EXCITE stroke trial: comparing early and delayed constraint-induced movement therapy. Stroke 41(10):230915Google Scholar CrossrefMedline
Wolf SLWinstein CJMiller JPTaub EUswatte GMorris D, and others. 2006Effect of constraint-induced movement therapy on upper extremity function 3 to 9 months after stroke: the EXCITE randomized clinical trial. JAMA 296(17):2095104Google Scholar CrossrefMedline
World Health Organization. 2016World health statisticshttp://www.who.int/gho/publications/world_health_statistics/2016/en/Google Scholar
Wu CYChen YALin KCChao CPChen YT2012Constraint-induced therapy with trunk restraint for improving functional outcomes and trunk-arm control after stroke: a randomized controlled trial. Phys Ther 92(4):48392Google Scholar CrossrefMedline
Wu CYChuang LLLin KCChen HCTsay PK2011Randomized trial of distributed constraint-induced therapy versus bilateral arm training for the rehabilitation of upper-limb motor control and function after stroke. Neurorehabil Neural Repair 25(2):1309Google Scholar Link
Young BMNigogosyan ZRemsik AWalton LMSong JNair VA, and others. 2014Changes in functional connectivity correlate with behavioral gains in stroke patients after therapy using a brain-computer interface device. Front Neuroeng 7:25Google Scholar Medline
Zeiler SRKrakauer JW2013The interaction between training and plasticity in the poststroke brain. Curr Opin Neurol 26(6):60916Google Scholar CrossrefMedline
Zimerman MHeise KFHoppe JCohen LGGerloff CHummel FC2012Modulation of training by single-session transcranial direct current stimulation to the intact motor cortex enhances motor skill acquisition of the paretic hand. Stroke 43(8):218591Google Scholar CrossrefMedline
Zrenner CBelardinelli PMuller-Dahlhaus FZiemann U. 2016Closed-loop neuroscience and non-invasive brain stimulation: a tale of two loops. Front Cell Neurosci 10:92Google Scholar CrossrefMedline

<via Restoring Motor Functions After Stroke: Multiple Approaches and OpportunitiesThe Neuroscientist – Estelle Raffin, Friedhelm C. Hummel, 2017>

Advertisements

, , , , , ,

Leave a comment

[Abstract] Post-stroke spasticity management including a chosen physiotherapeutic methods and improvements in motor control – review of the current scientific evidence.

Abstract

Cerebrovascular diseases based on stroke etiology concern millions of people worldwide, and annual rates of disease are still increasing. In the era of an aging society and suffering from a number of risk factors, in particular those modifiable, strokes and muscles’ spastic paresis, subsequently resulting in damage of upper motor neuron structures will become a serious problem for the entire health care system. Effective management and physiotherapy treatment for post-stroke spasticity persisted, both in the acute and chronic, is still a significant medical problem in the interdisciplinary aspect. Care procedures for this type of patient becomes a kind of challenge for specialists in neurology, internal medicine, cardiology, dermatology or neurosurgery, but also for physiotherapists in their everyday clinical practice. The aim of this paper is to present the issues of cerebral stroke and resulting spastic hypertonia in terms of current pharmacological treatment and surgery, and primarily through the use of effective physiotherapy methods, the use of which was confirmed in the way of reliable scientific research in accordance with the principles of Evidence Based Medicine and Physiotherapy (EBMP).

 

via [Post-stroke spasticity management including a chosen physiotherapeutic methods and improvements in motor control – review of the current scientifi… – PubMed – NCBI

, , , , ,

Leave a comment

[Abstract] Neurotech: Robotic Assist Devices Show Gains in Walking for Crouch Gait in Cerebral Palsy and Post-Stroke Hemiparesis

via Neurotech: Robotic Assist Devices Show Gains in Walking for… : Neurology Today

ARTICLE IN BRIEF

Figure

Developers of robotic devices discuss advances in the technologies to help people improve walking post-stroke and improve couch gait in cerebral palsy. Independent experts in neurorehabilitation review the potential and possible caveats of these devices.

Three novel robotic assistance devices, one for hemiparetic gait following stroke, and two for crouch gait in children with cerebral palsy, have each demonstrated improved walking in preliminary clinical trials.

For stroke patients, a robotic exosuit made of a soft, clothing-like anchor attached to motorized cables was shown to increase the paretic limb’s forward propulsion and the paretic ankle’s swing phase dorsiflexion in both treadmill and over-ground walking.

For children with crouch gait due to cerebral palsy, one trial used a cable-driven robot called a Tethered Pelvic Assist Device, or TPAD. The laboratory-based device is designed to strengthen the extensor muscles, especially the soleus in the calves, by putting downward pressure on them during training. After six weeks of practice with the device, the children’s posture was more upright, with greater step length and toe clearance, when walking without it.

Also for children with crouch gait, the third study examined the use of a wearable exoskeleton that provides a burst of knee extension assistance at just the right moment when a child or adolescent is walking. None of the seven participants, age 5 to 17, fell while using it, and six of the seven showed postural improvements equivalent to those previously reported from surgery.

While promising, the devices will require far more testing in randomized trials before their true value can be known, said a leading specialist in neurological rehabilitation.

“These are foundational studies; they’re just beginning to get started,” said Bruce H. Dobkin, MD, FRCP, distinguished professor of clinical neurology and director of the Neurological Rehabilitation and Research Program at the Geffen School of Medicine at the University of California, Los Angeles. “The cost, safety, user-friendliness, and ability to use at differing levels of disability severity — all those are major challenges.”

Even so, each of the three devices employs a new kind of robotic assistance unlike any existing on the market.

“Most robotics for neurological injuries are heavy, power-hungry exosuits for people with spinal cord injuries who can’t walk at all,” said a coauthor of the study for stroke patients, Terry D. Ellis, PT, PhD, NCS, director of the Center for Neurorehabilitation at Boston University. “But there’s a whole bunch of people who have disabilities, who can walk, but don’t walk well. They need facilitation or augmentation to restore some of the normal components of walking.”

A ROBOT POST-STROKE

Published in the July 26 edition of Science Translational Medicine, the study of a robotic exosuit tested in nine post-stroke patients used what it called “garment-like, functional textile anchors” rather than a hard, metallic exterior. Worn on only the paretic limb, the suit was designed to be as unobtrusive as possible.

“It’s much more compatible with the real world than a rigid device would be,” said the first author of the paper, Louis N. Awad, PT, DPT, PhD, an assistant professor of physical therapy at Boston University, and a research faculty member at Spaulding Rehabilitation Hospital. “Ordinary clothes are made of soft material. We don’t don a metallic pair of pants and walk out the door. That’s our goal — robotic clothing that helps people with difficulty walking.”

Attached to cables tethered to a belt worn around the hips, the exosuit functioned in synchrony with a wearer’s paretic limb to facilitate an immediate increase in the paretic ankle’s swing phase dorsiflexion and forward propulsion (p< 0.05), according to the paper.

The improved movements resulted in a 20 percent reduction in forward propulsion interlimb asymmetry and a 10 percent reduction in the energy cost of walking, which together were equivalent to a nearly one-third lower metabolic burden — a 32 percent reduction — while walking.

Although the study did include some over-ground walking, it was not designed to test whether the exosuit had any therapeutic effects that might carry over to when patients are not wearing it.

“This is a proof of concept paper,” said Dr. Ellis. “Down the road we need to conduct trials in more ecologically valid environments, and to see if it has therapeutic value. For now we wanted to demonstrate that the device can facilitate more normal walking.”

While applauding the study as “clever,” Dr. Dobkin said it remained to be seen whether the robotic exosuit would prove to have significant therapeutic effects that would stand up in randomized trials in natural environments. He pointed to randomized trials published in recent years showing that peroneal nerve functional electrical stimulators have no greater therapeutic effect than do standard ankle-foot orthoses.

“It’s similar to all the work that was done using the electrical stimulation of the ankle,” Dr. Dobkin said. “The real question is whether it will lead to improved function when you walk over-ground. Walking on a treadmill is not terribly natural.”

He also pointed out that the nine patients in the study were able to walk on average at about two miles per hour. “That’s already pretty fast,” he said. In addition, he said, the 20 percent reduction in interlimb asymmetry is relatively modest.

But, said Dr. Dobkin, people can improve their gait by 20 percent just by sustained practice. “When you see modest changes like this with the device, you wonder if the same changes couldn’t have been achieved without it,” he said.

Steven L. Wolf, PhD, PT, FAPTA, FAHA, professor in the department of rehabilitation medicine at Emory University School of Medicine, pointed out that existing robotic devices to help people who are completely unable to walk can cost patients up to $250,000. Perhaps the exosuit might become an improvement over what presently exists both in terms of function and cost, he said.

“Most existing devices are beautiful but incredibly expensive,” Dr. Wolf said. “Is the bang in the buck? Not as yet, in my opinion. The evidence for persistent benefit from these device is just not there.”

IMPROVING CROUCH GAIT IN CP

The first of the two studies using robotic devices to improve crouch gait in children with cerebral palsy was published on July 26 in Science Robotics, led by senior author Sunil K. Agrawal, PhD, professor of mechanical engineering and rehabilitation medicine at Columbia University.

Rather than directly straighten the children’s posture, Dr. Agrawal’s seemingly contradictory approach was to increase the downward force on their pelvis as they attempted to walk on a treadmill. The tension in each wire, attached to a belt on the pelvis, is modulated in real time by a motor placed around the treadmill in response to motion capture data from cameras. Unlike other robotic devices that have been tested for treating crouch gait, the TPAD has no rigid links to the body, permitting free movement of the legs.

After training in the device for 15 sessions of 16 minutes each over the course of six weeks, the six participants showed enhanced upright posture, improved muscle coordination, increased step length, range of motion of the lower limb angles, toe clearance, and heel-to-toe pattern.

“You can see a marked difference before and after,” Dr. Agrawal said. “We heard from families and the children themselves that they were walking faster, with better posture. Now we have to see if we should use a higher magnitude of downward pull, how long each training session should be, and for how many sessions.”

Commenting on the TPAD study, Dr. Dobkin said, “The kids who were selected for inclusion were not necessarily the kind who get surgery. They had less of a crouch, a little bit more of a push-off. The question is whether training like this will lead to good over-ground walking. They got a hint of that.”

The second crouch-gait study, published on August 23 in Science Translational Medicine, involved a wearable exoskeleton designed for over-land use, and was described by the authors as the first robotic device designed specifically to treat a gait disorder in children and adolescents. Rather than force the lower limb to move in a particular way, “the exoskeleton dynamically changed the posture by introducing bursts of knee extension assistance during discrete portions of the walking cycle, a perturbation that resulted in maintained or increase knee extensor muscle activity during exoskeleton use,” the paper stated.

“In the last decade, there’s been a groundswell of work on exoskeletons, but a majority of them are designed to permit mobility after spinal injury in adults who have lost the ability to walk,” said senior author Thomas Bulea, PhD, a staff scientist in the functional and applied biomechanics section of the rehabilitation medicine department at the National Institutes of Health Clinical Center in Bethesda, MD. “There hasn’t been much done for the pediatric population who just need to improve their walking.”

A coauthor of the paper, Diane L. Damiano, PT, PhD, chief of the section in which Dr. Bulea works, said the purpose of the wearable exoskeleton is different than that of the TPAD device developed by Dr. Agrawal.

“His device is designed to strengthen the calf muscles by increasing the resistance on them,” she said. “His results were good, but this is very different from what we are doing. We have a wearable device. It’s not meant to be used in a lab for training. We’re not necessarily trying to strengthen them, although that would be a desired outcome; we are instead trying to assist their abilities to help them practice being more upright while they walk. This is something that they would wear throughout the day for several months with the goal that their posture will ultimately be improved without the device.”

A surprising observation, she added, was that some children saw it as something cool to wear.

LINK UP FOR MORE INFORMATION:

•. Awad LN, Bae J, O’Donnell K, et al A soft robotic exosuit improves walking in patients after stroke http://stm.sciencemag.org/content/9/400/eaai9084. Sci Transl Med 2017; 9 (400). pii: eaai9084.

•. Video of the soft robotic exosuit for stroke patients: http://www.sciencetranslationalmedicine.org/cgi/content/full/9/400/eaai9084/DC1

•. Kang J, Martelli D, Vashista V, et al Robot-driven downward pelvic pull to improve crouch gait in children with cerebral palsy http://robotics.sciencemag.org/content/2/8/eaan2634. Sci Robot 2017;2(8): eaan2634.

•. Video of the robot-driven downward pelvic pull device can be seen at http://engineering.columbia.edu/news/sunil-agrawal-cerebral-palsy-crouch-gait

•. Lerner ZF, Damiano DL, Bulea TC. A lower-extremity exoskeleton improves knee extension in children with crouch gait from cerebral palsy http://stm.sciencemag.org/content/9/404/eaam9145. Sci Transl Med 2017; 9 (404). pii: eaam9145.

, , , ,

Leave a comment

[WEB SITE] The Relationship Between Epilepsy and Sleep

The Thomas Haydn Trust in an aid to understanding Epilepsy and Sleep has published this mobile article. This article is not extensive and should not be used as medical advice; it’s intended for information purposes only. This dictionary is also available for download from http://www.thomashaydntrust.com/publications.htm in .pdf format. [Please note that this is version 1 and further updates may be availalbe]
 Written by M C Walker, S M Sisodiya

Institute of Neurology, University College London, National Hospital for Neurology and Neurosurgery, Queen Square, London, and National Society for Epilepsy, Chalfont St Peter, Bucks. London, and National Society for Epilepsy, Chalfont St Peter, Bucks. September 2005. This article can be reproduced for educational purposes.

Introduction

Epilepsy has a complex association with sleep. Certain seizures are more common during sleep, and may show prominent diurnal variation. Rarely, nocturnal seizures are the only manifestation of an epileptic disorder and these can be confused with a parasomnia. Conversely, certain sleep disorders are not uncommonly misdiagnosed as epilepsy. Lastly, sleep disorders can exacerbate epilepsy and epilepsy can exacerbate certain sleep disorders. This chapter is thus divided into four sections: normal sleep physiology and the relationship to seizures; the interaction of sleep disorders and epilepsy; and the importance of sleep disorders in diagnosis.

Normal sleep physiology and the relationship to seizures

Adults require on average 7 – 8 hours sleep a night. This sleep is divided into two distinct states – rapid eye movement (REM) sleep and non-REM sleep. These two sleep states cycle over approximately 90 minutes throughout the night with the REM periods becoming progressively longer as sleep continues. Thus there is a greater proportion of REM sleep late on in the sleep cycles. REM sleep accounts for about a quarter of sleep time. During REM sleep, dreams occur; hypotonia or atonia of major muscles prevents dream enactment. REM sleep is also associated with irregular breathing and increased variability in blood pressure and heart rate. Non-REM sleep is divided into four stages (stages I – IV) defined by specific EEG criteria. Stages I/II represent light sleep, while stages III/IV represent deep, slow-wave sleep.

Gowers noted that in some patients, epileptic seizures occurred mainly in sleep. Sleep influences cortical excitability and neuronal synchrony. Surveys have suggested that 10 – 45% of patients have seizures that occur predominantly or exclusively during sleep or occur with sleep deprivation. EEG activation in epilepsy commonly occurs during sleep, so that sleep recordings are much more likely to demonstrate epileptiform abnormalities. These are usually most frequent during non-REM sleep and often have a propensity to spread so that the epileptiform discharges are frequently observed over a wider field than is seen during the wake state. Sleep deprivation (especially in generalised epilepsies) can also ‘activate’ the EEG, but can induce seizures in some patients. Thus many units perform sleep EEGs with only moderate sleep deprivation (late night, early morning), avoidance of stimulants (e.g. caffeine-containing drinks) and EEG recording in the afternoon. Sleep-induced EEGs in which the patient is given a mild sedative (e.g. chloral hydrate) are also useful.

Sleep and generalised seizures

Thalamocortical rhythms are activated during non-REM sleep giving rise to sleep spindles. Since similar circuits are involved in the generation of spike-wave discharges in primary generalised epilepsy, it is perhaps not surprising that non-REM sleep often promotes spike-wave discharges. Epileptiform discharges and seizures in primary generalised epilepsies are both commonly promoted by sleep deprivation. Furthermore, primary generalised seizures often occur within a couple of hours of waking, whether from overnight sleep or daytime naps. This is most notable with juvenile myoclonic epilepsy in which both myoclonus and tonic-clonic seizures occur shortly after waking, and the

Διαφήμιση

syndrome of tonic-clonic seizures on awakening described by Janz. Seizure onset in this syndrome is from 6 – 35 years and the prognosis for eventual remission is good.

Certain epileptic encephalopathies show marked diurnal variation in seizure manifestation and electrographic activity. An example is the generalised repetitive fast discharge during slow-wave sleep occurring in Lennox-Gastaut syndrome. Another example is electrical status epilepticus during sleep (ESES). This is characterised by spike and wave discharges in 85 – 100% of non-REM sleep. This phenomenon is associated with certain epilepsy syndromes, including Landau-Kleffner, Lennox-Gastaut syndrome, continuous spikes and waves during sleep and benign epilepsy of childhood with rolandic spikes. ESES can thus be a component of a number of different epilepsy syndromes with agedependent onset, many seizure types, and varying degrees of neuropsychological deterioration. Indeed, ESES has been described in the setting of an autistic syndrome alone with no other

manifestation of epilepsy.

Sleep and partial epilepsies

Inter-ictal epileptiform abnormalities on the EEG occur more frequently during sleep, especially stage III/IV sleep (slow-wave sleep). The discharges have a greater propensity to spread during sleep, and thus are often seen over a wider field than discharges occurring during wakefulness. Temporal lobe seizures are relatively uncommon during sleep, while frontal lobe seizures occur often predominantly (sometimes exclusively) during sleep. Nocturnal frontal lobe seizures can be manifest as: brief stereotypical, abrupt arousals; complex stereotypical, nocturnal movements; or episodic nocturnal wanderings with confusion. Inherited frontal lobe epilepsies can manifest with only nocturnal events that can be confused with parasomnias (see below). Autosomal dominant nocturnal frontal lobe epilepsy is such an epilepsy. This has been associated with mutations in alpha-4 and beta-2 subunits of the neuronal nicotinic acetylcholine receptor. Onset is usually in adolescence with seizures occurring frequently, sometimes every night. The seizures are provoked by stress, sleep deprivation and menstruation, and often respond well to carbamazepine.

The interaction of sleep disorders and epilepsy

Seizures can disrupt sleep architecture. Complex partial seizures at night disrupt normal sleep patterns, decrease REM sleep and increase daytime drowsiness. Daytime complex partial seizures can also decrease subsequent REM sleep, which may contribute to impaired function. Antiepileptic drugs (AEDs) can also disrupt normal sleep patterns, although there are conflicting data (this is partially due to drugs having different short-term and long-term effects). Carbamazepine, for example, given acutely reduces and fragments REM sleep, but these effects are reversed after a month of treatment. The GABAergic drugs can have a profound effect on sleep; phenobarbitone and benzodiazepines prolong non-REM sleep and shorten REM sleep, while tiagabine increases slow-wave sleep and sleep efficiency. Gabapentin and lamotrigine may both increase REM sleep.

Certain sleep disorders are more common in patients with epilepsy. This is particularly so with obstructive sleep apnoea which is more common in patients with epilepsy and can also exacerbate seizures. Indeed, sleep apnoea is approximately twice as common in those with refractory epilepsy than in the general population. The reasons why this is so are unknown, but may relate to increased body weight, use of AEDs, underlying seizure aetiology or the epilepsy syndrome itself.

Patients with obstructive sleep apnoea often find that seizure control improves with treatment of the sleep apnoea. Topiramate may also be a particularly useful drug in these cases.

The importance of sleep disorders in differential diagnosis

On occasions nocturnal seizures can be misdiagnosed as a primary sleep disorder (see above). Conversely, certain sleep disorders can be misdiagnosed as epilepsy and the more common of these will be discussed below. Sleep disorders tend to occur during specific sleep phases and thus usually occur at specific times during the night, while seizures usually occur at any time during the night. There may also be other clues in the history, including age of onset, association with other symptoms (see below) and the stereotypy of the episodes (seizures are usually stereotypical).

In cases where there is some uncertainty, video-EEG polysomnography is the investigation of choice. There are, however, instances in which the diagnosis can be difficult even after overnight video-EEG telemetry as frontal lobe seizures can be brief with any EEG change obscured by movement artefact, and it is often the stereotypy of the episodes that confirms the diagnosis.

Abnormalities of sleep are divided into three main categories: 1) dysomnias or disorders of the sleepwake cycle; 2) parasomnias or disordered behaviour that intrudes into sleep, and 3) sleep disorders associated with medical or psychiatric conditions. Although there is an extensive list of conditions within each of these categories, we will confine ourselves to the clinical features of the more common conditions that can be confused with epilepsy.

Narcolepsy

Narcolepsy is a specific, well-defined disorder with a prevalence of approximately one in 2000. It is a life-long condition usually presenting in late teens or early 20s. Narcolepsy is a disorder of REM sleep and has as its main symptom excessive daytime sleepiness. This is manifest as uncontrollable urges to sleep, not only at times of relaxation (e.g. reading a book, watching television), but also at inappropriate times (e.g. eating a meal or while talking). The sleep is itself usually refreshing. The other typical symptoms are cataplexy, sleep paralysis and hypnagogic/hypnopompic hallucinations. These represent REM sleep phenomena such as hypotonia/atonia, and dreams occurring at inappropriate times. Cataplexy is a sudden decrease in voluntary muscle tone (especially jaw, neck and limbs) that occurs with sudden emotion like laughter, elation, surprise or anger. This can manifest as jaw dropping, head nods or a feeling of weakness or, in more extreme cases, as falls with ‘paralysis’ lasting sometimes minutes. Consciousness is preserved. Cataplexy is a specific symptom of narcolepsy, although narcolepsy can occur without cataplexy. Sleep paralysis and hypnagogic hallucinations are not particularly specific and can occur in other sleep disorders and with sleep deprivation (especially in the young). Both these phenomena occur shortly after going to sleep or on waking.

Sleep paralysis is a feeling of being awake, but unable to move. This can last minutes and is often very frightening, so can be associated with a feeling of panic. Hypnagogic/hypnopompic hallucinations are visual or auditory hallucinations occurring while dozing/falling asleep or on waking; often the hallucinations are frightening, especially if associated with sleep paralysis.

Narcolepsy is associated with HLA type. Approximately 90% of all narcoleptic patients with definite cataplexy have the HLA allele HLA DQB1*0602 (often in combination with HLA DR2), compared with approximately 25% of the general population. The sensitivity of this test is decreased to 70% if cataplexy is not present. The strong association with HLA type has raised the possibility that narcolepsy is an autoimmune disorder. Recently loss of hypocretin-containing neurons in the hypothalamus has been associated with narcolepsy, and it is likely that narcolepsy is due to deficiency in hypocretin (orexin).

Since narcolepsy is a life-long condition with possibly addictive treatment, the diagnosis should always be confirmed with multiple sleep latency tests (MSLT). During this test five episodes of sleep are permitted during a day; rapid onset of sleep and REM sleep within 15 minutes in the absence of sleep deprivation are indicative of narcolepsy.

The excessive sleepiness of narcolepsy can be treated with modafinil, methylphenidate or dexamphetamine and regulated daytime naps. The cataplexy, sleep paralysis and hypnagogic/hypnopompic hallucinations respond to antidepressants (fluoxetine or clomipramine are the most frequently prescribed). People with narcolepsy often have fragmented, poor sleep at night, and good sleep hygiene can be helpful.

Sleep apnoea

Sleep apnoea can be divided into the relatively common obstructive sleep apnoea and the rarer central sleep apnoea. Obstructive sleep apnoea is more common in men than women and is associated with obesity, micrognathia and large neck size. The prevalence may be as high as 4% in men, and 2% in women. The symptoms suggestive of obstructive sleep apnoea are loud snoring, observed nocturnal apnoeic spells, waking at night fighting for breath or with a feeling of choking, morning headache, daytime somnolence, personality change and decreased libido. Although the daytime somnolence can be as severe as narcolepsy, the naps are not usually refreshing and are longer. Obstructive sleep apnoea and central sleep apnoea can be associated with neurological disease, but central sleep apnoea can also occur as an idiopathic syndrome. The correct diagnosis requires polysomnography with measures of oxygen saturations and nasal airflow or chest movements. To be pathological a sleep apnoea or hypopnoea (a 50% reduction in airflow) has to last ten seconds and there need to be more than five apnoeas/hypopnoeas per hour (the precise number to make a diagnosis varies from sleep laboratory to sleep laboratory).

Uncontrolled sleep apnoea can lead to hypertension, cardiac failure, pulmonary hypertension and stroke. In addition, sleep apnoea has been reported to worsen other sleep conditions, such as narcolepsy, and to worsen seizure control.

Treatment of sleep apnoea should include avoidance of alcohol and sedatives and weight reduction. Pharmacological treatment is not particularly effective, although REM suppressants such as protriptyline can be helpful. The mainstays of treatment are surgical and include tonsillectomies, adenoidectomy and procedures to widen the airway, and the use of mechanical devices. Dental appliances to pull the bottom jaw forward can be effective in mild cases, but continuous positive airway pressure administered by a nasal mask has become largely the treatment of choice for moderate/severe obstructive sleep apnoea. In cases associated with neuromuscular weakness intermittent positive pressure ventilation is often necessary.

Restless legs syndrome/periodic limb movements in sleep

Restless legs syndrome (RLS) and periodic limb movements in sleep (PLMS) can occur in association or separately. Most people with RLS also have PLMS, but the converse is not true and most people with PLMS do not have RLS. RLS is characterised by an unpleasant sensation in the legs, often described as tingling, cramping or crawling, and an associated overwhelming urge to move the legs. These sensations are usually worse in the evening, and movement only provides temporary relief. RLS affects about 5% of the population. Periodic limb movements in sleep are brief, repetitive jerking of usually the legs that occur every 20 – 40 seconds. These occur in non-REM sleep and can cause frequent arousals. PLMS occurs in about 50% of people over 65 years. These conditions can also be associated with daytime jerks. Both RLS and PLMS can be familial, but can be secondary to peripheral neuropathy (especially diabetic, uraemic and alcoholic neuropathies), iron deficiency, pregnancy and rarely spinal cord lesions.

Symptomatic relief can be achieved with benzodiazepines, gabapentin and opioids, but L-DOPA and dopamine agonists are the mainstay of treatment.

Sleep-wake transition disorders

The most common of these are hypnic jerks or myoclonic jerks that occur on going to sleep or on waking. They are entirely benign in nature, and require no treatment. They can occur in association with other sleep disorders. Rhythmic movement disorder is a collection of conditions occurring in infancy and childhood characterised by repetitive movements occurring immediately prior to sleep onset that can continue into light sleep. One of the most dramatic is headbanging or jactatio capitis nocturna. Persistence of these rhythmic movements beyond the age of ten years is often associated with learning difficulties, autism or emotional disturbance. Sleep-talking can occur during non-REM and REM sleep, but is often seen with wake-sleep transition and is a common and entirely benign phenomenon.

Nocturnal enuresis

Nocturnal enuresis is a common disorder that can occur throughout the night. Although diagnosis is straightforward, it can recur in childhood, and also occurs in the elderly, with approximately 3% of women and 1% of men over the age of 65 years having the disorder. Thus, on occasions, it can be misdiagnosed as nocturnal epilepsy.

Non-REM parasomnias

Non-REM parasomnias usually occur in slow-wave (stage III/IV) sleep. These conditions are often termed arousal disorders and indeed can be induced by forced arousal from slow-wave sleep. There are three main non-REM parasomnias – sleepwalking, night terrors and confusional arousal. These disorders often have a familial basis, but can be brought on by sleep deprivation, alcohol and some drugs. They can also be triggered by other sleep disorders such as sleep apnoea, medical and psychiatric illness. Patients are invariably confused during the event, and are also amnesic for the event. These conditions are most common in children, but do occur in adults.

Sleepwalking may occur in up to 25% of children, with the peak incidence occurring from age 11 – 12 years. The condition is characterised by wanderings often with associated complex behaviours such as carrying objects, and eating. Although speech does occur, communication is usually impossible. The episode usually lasts a matter of minutes. Aggressive and injurious behaviour is uncommon, and should it occur then polysomnography may be indicated to exclude an REM sleep parasomnia (see below), and to confirm the diagnosis. Night terrors are less common and are characterised by screaming, and prominent sympathetic nervous system activity – tachycardia, mydriasis and excessive sweating. Both these conditions are usually benign and rarely need treatment. If dangerous behaviour occurs, then treatment may be indicated. Benzodiazepines, especially clonazepam, are usually very effective.

REM parasomnias

Nightmares are REM phenomena that can occur following sleep deprivation, with certain drugs (e.g. L-DOPA) and in association with psychological and neurological disease. Sleep paralysis (see narcolepsy) is also an REM parasomnia, and may be familial.

Of more concern are REM sleep behaviour disorders. These consist of dream enactment. They are often violent, and tend to occur later in sleep when there is more REM sleep. These are rare and tend to occur in the elderly. In over one-third of cases, REM sleep behaviour disorders are symptomatic of an underlying neurological disease such as dementia, multisystem atrophy, Parkinson’s disease, brainstem tumours, multiple sclerosis, subarachnoid haemorrhage and cerebrovascular disease. In view of this, a history of possible REM sleep behaviour disorder needs to be investigated by polysomnography, and if confirmed, then possible aetiologies need to be investigated. REM sleep behaviour disorders respond very well to clonazepam.

Further reading

• BAZIL CW (2002) Sleep and epilepsy. Semin Neurol 22(3) , 321-327.

• FOLDVARY-SCHAEFER NJ (2002) Sleep complaints and epilepsy: the role of seizures,

antiepileptic drugs and sleep disorders. Clin Neurophysiol 19(6) , 514-521.

• MALOW BA (2002) Paroxysmal events in sleep. J Clin Neurophysiol 19(6) , 522-534.

• SCHNEERSON J. Handbook of Sleep Medicine . Blackwell Science, Oxford.

[END]

ABOUT THE THOMAS HAYDN TRUST

The Thomas Haydn Trust is The Paediatric Epilepsy Charity that aims to serve the needs of Young People, Parents, Carers and Medical Professionals. But to know who we are you need to know why we are.

Providing local services and sharing the rewards globally is the core of THT’s work, weather newly diagnosed or not, you will find THT a valuable source of support, knowledge and news for the epilepsies.

The Thomas Haydn Trust was set up in the wake of Thomas Haydn Smith’s diagnosis of Lennox-Gastaut Syndrome – One of the Most severe forms of Childhood Onset Epilepsies, affecting 1 in 1,000,000 epilepsy sufferer’s worldwide.

In setting up THT our aim was to combat many of the hurdles that Thomas and his family come across while living with LGS. THT strives to ‘Give Something Back’ to organisations that help families and children with severe epilepsies.

We work towards our goals in the following manner:

Research

Raising the need profile for both basic and clinical research into Lennox-Gastaut Syndrome and other childhood Epilepsies.

Support

By providing a free and open forum for sufferers, family and carers’, allowing them to share experiences, build relationships and facilitate peer learning. THT also provides details of leading specialist support organisations of specific Epilepsy conditions – Supporting the specific needs of the child.

Education

Developing an ever-expending resource of research findings and educational materials for the public and medical professionals.

Funding

Where possible, fund individuals and organisations involved in support, development and care of families with sick children.

Awareness

Raising awareness of childhood Epilepsies through various mediums including the internet, press, radio and television. Highlighting the effects of LGS and other childhood onset Epilepsies through our live events – Raising awareness is the key principle on which THT works.

Empowerment

Promoting the advancement of individuals with Epilepsy to speak out against ignorance, predjudice and bigotry that still surrounds conditions of Epilepsy.

Networking

Developing links with other national and international organisations to create a coalition of information sharing networks.

via The Relationship Between Epilepsy and Sleep – Wattpad

, , , ,

Leave a comment

[WEB SITE] 10 Neurotechnologies About to Transform Brain Enhancement and Brain Health

BrainComputerInterface.

30,000+ scientists and professionals gathered for the annual Society for Neuroscience conference in Chicago last month, proving the growing interest and activities to better understand the inner workings of the human brain, and to discover ways and technologies to enhance its health and performance.

Now, which of all those ongoing efforts are closer to touching our lives, to empower consumers, patients and health professionals?

To answer that question, we recently examined the worldwide landscape of Pervasive Neurotechnology patents, given that investment in intellectual property is a crucial signal in the life-cycle of technology commercialization. We paid extra attention to neurotech­nolo­gies which, being dig­i­tal, are scal­able and rel­a­tively inex­pen­sive, and that, being non-invasive, pose few if any neg­a­tive side-effects (the main exception to this rule being #10 below, which is why we place it last).

Through our year-long analysis of thousands of patents, we uncovered ten innovative brain health and brain enhancement systems on the cutting edge, that, in our estimation, are likely to go mainstream over the next few years.

10 Neurotechnologies About to Transform Brain Health and Brain Enhancement

1. Big Data-enhanced diagnostics and treatments

As the costs of computing power, cloud accessibility and hardware sensors dwindle, brain health systems can leverage measurements taken from a far broader swath of the population than ever before possible. And this analysis CNSResphelps understand precisely where an individual’s readings lie on the distribution curve of health to disease, drives the ability to understand with nuance how one’s readings changes over time, and allows better discernment of proper diagnoses and treatments based on the efficacy of treatments with others having similar brain signatures.

Companies like CNS Response and Advanced Brain Monitoring are already deploying systems that harness the power of big data, exemplified by neurometrics-driven report systems such as in the image to the right.

–> Patent Image: Data Illustrating Patient Stimulant Responsiveness Spectrum, by CNS Response

Emotiv1

2. Brain-Computer Interfaces for device control

Brain Computer Interfaces (BCIs) link the commands of our thoughts to the devices of the world. The global BCI market is expected to reach 1.5 billion by 2020, of which 85% is estimated to be non-invasive.

Companies like Emotiv and NeuroSky are advancing the state of BCI technology, while other organizations are developing the external systems and ecosystems to interact with BCIs. Phillips has patents describing home medical systems that remotely monitor health via EEG, helping patients suffering from ALS (commonly known as Lou Gehrig’s disease), for example, to control home appliances via BCIs.

Emotiv4–> Example: Philips-Accenture Project to Control Home Devices via the Mind

  • User sends brain commands
  • Wearable display shows navigation interface
  • Digital app reads commands, connects devices
  • Smart products are activated

 

 3. Real-time neuromonitoring (plus robotic aids)

AdvNeuroA good number of companies, including Medtronic, Neuropace and St. Jude Medical, are developing systems to actively monitor brain activity and respond in real-time with appropriate treatments.

These systems can discern symptoms leading up to an undesirable brain event (such as a seizure), and provide pre-emptive treatments to mitigate or altogether thwart epileptic activity. Some monitoring systems are coupled with other assistive devices, such as robotic aids to enable patients suffering from neurological disorders (such as ALS) to regain lost motor control.

–> Patent Image: Coupling Neural Stimulation with Robotic Assistance.

 

4. Neurosensor-based vehicle operator systems

Systems employing neural detection devices to monitor vehicle operator alertness (or a lackthereof) and take preventative measures with driver stimulation or vehicle autopilot/ shutdown systems are described by multiple patents.

Whether due to inattentiveness (for example texting while driving) or drowsiness, new vehicle-integrated systems can assess real-time operator fitness. The US Army, automotive companies like Toyota, start-ups like Freer Logic, medical device makers and insurers are all patenting inventions addressing this concern.

Safety

–> Patent Image: Vehicle Operator Systems Augmented with EEG Signal Processing 

 

 

 5. Cognitive training videogames

Software applications accessible online and via mobile devices include gaming systems that target specific cognitive and/or emotional systems of the brain.

Companies like Posit Science and Lumos Labs have secured patent protection (and significant market traction) on products in this area. A patent recently issued to Lumos Labs for enhancing fluid intelligence and working memory through mental manipulation of memorized objects is illustrative.

Lumosity

–> Patent Image: Can you determine the pinball path after bumpers (818) disappear?

 

6. Brain-responsive computing systems

As Microsoft CEO Sataya Nadella states:

We are moving from a world where computing power was scarce to a place where it now is most limitless, and where the true scarce commodity is increasingly human attention.

A recent study by Microsoft finds that 68% of early tech adopters and 67% of heavy social media users really have to concentrate hard to stay focused on tasks. So large tech companies are patenting systems to improve productivity and worker output, for example by using EEG signals to recognize user’s mental state and tailor the computing experience.
Microsoft

–> Patent Image: Classifying user-tasks based on brainwave data

 

7. Virtual Reality treatments, especially in conjunction with EEG and/ or tDCS

Whether for treating PTSD and phobias through exposure therapy, or assisting surgeons in the operating room, virtual-reality is quickly gaining momentum.

Medical tech companies such as Medtronic and Brainlab, and consumer research firms such as Nielsen are building significant IP portfolios in the area. The following patent by Evoke Neuroscience shows the interplay between virtual reality, EEG and transcranial direct current stimulation (tDCS).

VR

–> Patent Image: Virtual Reality (VR) Neurotechnology

 

8. “Mindful” wearables

Wearables are being designed to improve not just physical health but mental Musewell-being as well. Meditation apps in tandem with consumer EEGs like InteraXon’s Muse  aim to help users build concentration and self-regulation skills.

Even general-purpose fitness wearables are starting to include mental health and training applications. Jawbone (through its subsidiary BodyMedia) has secured patents that consider physiological and contextual factors.

–> Patent Image: Mental Health Applications of Wearable Devices

 

 9. Collaborative cognitive simulations

These are systems that focus on improving learning and skill acquisition across the extended workforce through online interactive platforms and cognitive simulation models. Human capital-intensive organizations such as AT&T and Accenture, and start-ups such as Applied Cognitive Engineering, are developing multiple applications in the area, and securing relevant intellectual property rights.

–> Patent example: System method and article of manufacture for creating collaborative application sharing

 

10. Electrical and magnetic brain stimulation

These are technologies that can influence brain Thync activity via magnetic fields or electrical impulses, and they are becoming increasingly common. Multiple hospitals and clinics already offer treatments based on brain stimulation, DARPA has awarded contracts to develop systems to augment memory with targeted electrical stimulation techniques, and consumers can buy wearable devices claiming to induce an array of brain states from calming to energizing.

–> Patent Image: Wearable Transdermal Electrical Stimulation Device

This patent comes via Thync, an early-stage company backed by Khosla Ventures. Other companies pushing the boundaries of brain stimulation technology include St. Jude Medical, Brainlab and Neuronetics.

 

Now that we have reviewed some of the exciting neurotechnologies ahead, we need to step back for a second. Which of these technologies will deliver the most value, and in what context? How will innovative assessments and therapies be validated, adopted, regulated and commercialized? How do we maximize the benefits and minimize the risks?

2015SharpBrainsVirtualSummit_webThose questions constitute, in essence,  the Agenda for the 2015 SharpBrains Virtual Summit taking place next week, where over 200 pioneers and experts will gather around a virtual table to discuss the latest, the next, and how to harness it all to improve work and life.

Please consider joining us!

 

— Alvaro Fer­nan­dez, named a Young Global Leader by the World Eco­nomic Forum, runs Sharp­Brains, an inde­pen­dent mar­ket research firm track­ing health and well­ness appli­ca­tions of brain sci­ence. He is an internationally-known speaker and expert, and has been quoted by The New York Times, The Wall Street Jour­nal, New Sci­en­tist, CNN, and more.

— Nikhil Sriraman is a patent attorney admitted to practice before the United States Patent and Trademark Office (USPTO). Nikhil has held positions at the USPTO, IP law firms and in-house at Fortune 500 companies. He currently serves as Primal’s Vice President of Intellectual Property, as well as SharpBrains’ Intellectual Property Analyst.

via 10 Neurotechnologies About to Transform Brain Enhancement and Brain Health | SharpBrains

Leave a comment

[BOOK] Serious Games in Physical Rehabilitation: From Theory to Practice – Google Books

Front Cover
SpringerOct 30, 2017 – Medical – 146 pages

Marketing text: This innovative book explores how games can be serious, even though most people generally associate them with entertainment and fun. It demonstrates how videogames can be a valuable tool in clinics and demonstrates how clinicians can use them in physical rehabilitation for various pathologies. It also describes step by step their integration in rehabilitation, from the (gaming) technology used to its application in clinics. Further, drawing on an extensive literature review, it discusses the pros and cons of videogames and how they can help overcome certain obstacles to rehabilitation.

The last part of the book examines the main challenges and barriers that still need to be addressed to increase and improve the use and efficacy of this new technology for patients. The book is intended for physiotherapists and clinicians alike, providing a useful tool for all those seeking a comprehensive overview of the field of serious games and considering adding it to conventional rehabilitation treatment.

via Serious Games in Physical Rehabilitation: From Theory to Practice – Bruno Bonnechère – Google Books

, , ,

Leave a comment

[WEB SITE] ISU Engineering continues work on Augmented Reality Device to Aid Arm Rehabilitation

Photo 1

Alba Perez-Gracia and student Omid Heidari demonstrating the virtual reality system.
Photo courtesy of Idaho State University

 

“We have accomplished half of the work, which is creating the engineering systems to test this work and now we have to develop the protocol for using it for rehabilitation to see how well it works,” said Alba Perez-Gracia, ISU chair and associate professor of mechanical engineering, and a lead researcher on the project.

The ISU researchers, who are working on this collaborative project with Texas A&M and California State University, Fullerton, first mapped arm motions and digitalized them and then have created a virtual world where people wearing a portable virtual-reality device can use the system as a therapeutic intervention. The researchers will soon be testing the new tool with human subjects.

Subjects wear a virtual reality headset and use it to complete tasks created for the virtual world. The virtual reality system picks up the actual movements of their own arm and displays it as a cartoon figure within the virtual world. The subject may then participate in the virtual world task that include picking up balls and throwing them at a target or stacking cubes using their right or left hand. In addition, the system has been developed to reflect the image of the arm being used.

For example, if a person is using the right arm to complete the task, the virtual reality system reflects the image so that the cartoon arm actions being portrayed look as if it is the left arm performing the task. This reflected image of arm function has the potential to be used as a therapeutic intervention because previous research has shown that observing an action activates the same area of the brain as performing the action.

“It is called the mirror neuron system,” said Nancy Devine, associate dean of the ISU School of Rehabilitation and Communications Sciences, who is a co-researcher on the project. “When you observe body movements, the cells in the brain that would produce that movement are active even though that arm isn’t being used.”

She said if you just look at brain activity, in some areas of the brain you can’t distinguish an active movement from an observed movement.

“So, if you take someone who has had a stroke and can’t use one arm, you can take their arm that is still working and reflect it to the other arm by putting them in this engaging virtual environment and we can be providing an exercise that is effective in helping rehabilitate the damaged areas,” Devine added.

Although the work on this specific project ends at the end of the academic year, ISU’s work on this type of project may continue.

“We have created the portable virtual-reality device that the patient can wear, which projects the motion happening for the patients,” Perez-Gracia said. “We hope it will be a starting point for future projects on using virtual reality and robotics for helping in rehabilitation and training of human motion.”

This research has been taking place at the ISU Robotics Laboratory and the Bioengineering laboratory at the Engineering Research Complex. On this project, Perez-Gracia and Devine have been working with the third researcher of the team, Marco P. Schoen, professor of mechanical engineering, Omid Heidari, a doctoral student in mechanical engineering, master of science students A.J. Alriyadh, Asib Mahmud, Vahid Pourgharibshahi and John Roylance, and undergraduate students Dillan Hoy, Madhuri Aryal and Merat Rezai. Eydie Kendall, assistant professor of physical and occupational therapy, also collaborated on the project.

“We have very good equipment here that we can do experiments with and that is very appealing,” said Heidari, who said the laboratory has become his second home. “Instead of just writing code on computers and stuff, we are actually doing something here that is very practical and very interesting. We did the motion capture, the kinematic part, and now we are working on finishing the virtual reality part of the project. We are getting closer to having a good model of what we want.”

via ISU Engineering continues work on Augmented Reality Device to Aid Arm Rehabilitation | Community | idahostatejournal.com

, , , , , , , , , ,

Leave a comment

[VIDEO] Henry Hoffman Q&A Video Series: Can Patients Years Following Stroke Actually Make Progress? – YouTube

Saebo, Inc. is a medical device company primarily engaged in the discovery, development and commercialization of affordable and novel clinical solutions designed to improve mobility and function in individuals suffering from neurological and orthopedic conditions. With a vast network of Saebo-trained clinicians spanning six continents, Saebo has helped over 100,000 clients around the globe achieve a new level of independence. In 2001, two occupational therapists had one simple, but powerful goal – to provide neurological clients access to transformative and life changing products. At the time, treatment options for improving arm and hand function were limited. The technology that did exist was expensive and inaccessible for home use. With inadequate therapy options often leading to unfavorable outcomes, health professionals routinely told their clients that they have “reached a plateau” or “no further gains can be made”. The founders believed that it was not the clients who had plateaued, but rather their treatment options had plateaued. Saebo’s commitment – “No Plateau in Sight” – was inspired by this mentality; and the accessible, revolutionary solutions began. Saebo’s revolutionary product offering was based on the latest advances in rehabilitation research. From the SaeboFlex which allows clients to incorporate their hand functionally in therapy or at home, to the SaeboMAS, an unweighting device used to assist the arm during daily living tasks and exercise training, “innovation” and “affordability” can now be used in the same sentence. Over the last ten years, Saebo has grown into a leading global provider of rehabilitative products created through the unrelenting leadership and the strong network of clinicians around the world. As we celebrate our history and helping more than 100,000 clients regain function, we are growing this commitment to affordability and accessibility even further by making our newest, most innovative products more accessible than ever.

via Henry Hoffman Q&A Video Series: Can Patients Years Following Stroke Actually Make Progress? – YouTube

 

, , , , ,

Leave a comment

[BLOG POST] SaeboFlex Helps Client Regain Hand Function 23 Years After Stroke

SaeboFlexStroke survivor exhibits remarkable improvement in hand function more than two decades after stroke, disproving theories that recovery window is limited to 6 months. 

Charlotte, N.C. – Tuesday, July 25, 2017 – Until recently, researchers believed that if a stroke survivor exhibited no improvement within the first 6 months, then he or she would have little to no chance of regaining motor function in the future. This assumed end of recovery is called a plateau. However, a groundbreaking new article published in the Journal of Neurophysiology discusses a stroke patient’s remarkable improvement decades after suffering a stroke at the age of 15. Doctors Peter Sörös, Robert Teasell, Daniel F. Hanley, and J. David Spence formally dismiss previous theories that stroke recovery occurs within 6 months, reporting that the patient experienced “recovery of hand function that began 23 years after the stroke.”

The patient’s stroke resulted in paralysis on the left side of his body, rendering his left hand completely nonfunctional, despite regular physical therapy. More than twenty years after his stroke, the patient took up swimming when his doctor recommended he lose weight. A year later, he began to show signs of movement on his affected side and returned to physical therapy. Therapists fitted the patient with the SaeboFlex, a mechanical device shown to improve hand function and speed up recoveryand, after only a few months of therapy, he began picking up coins with his previously nonfunctional hand. He also saw notable improvement in hand strength and control with the SaeboGlove, a low-profile hand device recently patented by Saebo.

Functional MRI studies showed the reorganization of sensorimotor neurons in both sides of the patient’s brain more than two decades after his stroke, resulting in a noticeable recovery in both hemispheres and improved motor function. “The marked delayed recovery in our patient and the widespread recruitment of bilateral areas of the brain indicate the potential for much greater stroke recovery than is generally assumed,” the doctors reported. “Physiotherapy and new modalities in development might be indicated long after a stroke.”

“This article highlights what we have seen for the last 15 years with many of our clients,” states Saebo co-founder, Henry Hoffman. “Oftentimes, stroke survivors are told that they have plateaued and no further progress is possible. We believe it is not the client that has plateaued but failed treatment options have plateaued them. In other words, traditional therapy interventions that lack scientific evidence can be ineffective and can actually facilitate the plateau.”

“The SaeboFlex device is a life-changing treatment designed for clients that lack motor recovery and function,” Hoffman continues. “Whether the client recently suffered a stroke or decades later, they can immediately begin using their hand with this device and potentially make significant progress over time. I agree with the authors that the neurorehabilitation community needs to take a hard look at traditional beliefs with respect to the window of recovery following stroke. It is my hope that this article will spark more interest by researchers to investigate upper limb function with clients at the chronic stage using Saebo’s hand technology.”

The abstract and article in its entirety can be viewed at the Journal of Neurophysiology’s website, jn.physiology.org.

If you are suffering from limited hand function or have been told you have plateaued, then schedule a call with a Saebo Specialist or click here to get started on the road to recovery.

via SaeboFlex Helps Client Regain Hand Function 23 Years After Stroke | Saebo

, , , , , , , ,

Leave a comment

[VIDEO] Can functional electrical stimulation restore function? – YouTube

Daniel Becker, MD | The Johns Hopkins University School of Medicine and INI October 21, 2017

via Can functional electrical stimulation restore function? – YouTube

, ,

Leave a comment

%d bloggers like this: