Circumstellar water vapour in M-type AGB stars: Constraints from H2O(1_10 - 1_01) lines obtained with Odin

Aims: Spectrally resolved circumstellar H2O(1_10 - 1_01) lines have been obtained towards three M-type AGB stars using the Odin satellite. This provides additional strong constrains on the properties of circumstellar H2O and the circumstellar envelope. Methods: ISO and Odin satellite H2O line data are used as constraints for radiative transfer models. Special consideration is taken to the spectrally resolved Odin line profiles, and the effect of excitation to the first excited vibrational states of the stretching modes (nu1=1 and nu3=1) on the derived abundances is estimated. A non-local, radiative transfer code based on the ALI formalism is used. Results: The H2O abundance estimates are in agreement with previous estimates. The inclusion of the Odin data sets stronger constraints on the size of the H2O envelope. The H2O(1_10 - 1_01) line profiles require a significant reduction in expansion velocity compared to the terminal gas expansion velocity determined in models of CO radio line emission, indicating that the H2O emission lines probe a region where the wind is still being accelerated. Including the nu3=1 state significantly lowers the estimated abundances for the low-mass-loss-rate objects. This shows the importance of detailed modelling, in particular the details of the infrared spectrum in the range 3 to 6 micron, to estimate accurate circumstellar H2O abundances. Conclusions: Spectrally resolved circumstellar H2O emission lines are important probes of the physics and chemistry in the inner regions of circumstellar envelopes around asymptotic giant branch stars. Predictions for H2O emission lines in the spectral range of the upcoming Herschel/HIFI mission indicate that these observations will be very important in this context.Comment: accepted in A&A, 10 pages, 8 figure

Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke

[EN] Background: Virtual and mixed reality systems have been suggested to promote motor recovery after stroke. Basing on the existing evidence on motor learning, we have developed a portable and low-cost mixed reality tabletop system that transforms a conventional table in a virtual environment for upper limb rehabilitation. The system allows intensive and customized training of a wide range of arm, hand, and finger movements and enables interaction with tangible objects, while providing audiovisual feedback of the participants' performance in gamified tasks. This study evaluates the clinical effectiveness and the acceptance of an experimental intervention with the system in chronic stroke survivors. Methods: Thirty individuals with stroke were included in a reversal (A-B-A) study. Phase A consisted of 30 sessions of conventional physical therapy. Phase B consisted of 30 training sessions with the experimental system. Both interventions involved flexion and extension of the elbow, wrist, and fingers, and grasping of different objects. Sessions were 45-min long and were administered three to five days a week. The body structures (Modified Ashworth Scale), functions (Motricity Index, Fugl-Meyer Assessment Scale), activities (Manual Function Test, Wolf Motor Function Test, Box and Blocks Test, Nine Hole Peg Test), and participation (Motor Activity Log) were assessed before and after each phase. Acceptance of the system was also assessed after phase B (System Usability Scale, Intrinsic Motivation Inventory). Results: Significant improvement was detected after the intervention with the system in the activity, both in arm function measured by the Wolf Motor Function Test (p < 0.01) and finger dexterity measured by the Box and Blocks Test (p < 0.01) and the Nine Hole Peg Test (p < 0.01); and participation (p < 0.01), which was maintained to the end of the study. The experimental system was reported as highly usable, enjoyable, and motivating. Conclusions: Our results support the clinical effectiveness of mixed reality interventions that satisfy the motor learning principles for upper limb rehabilitation in chronic stroke survivors. This characteristic, together with the low cost of the system, its portability, and its acceptance could promote the integration of these systems in the clinical practice as an alternative to more expensive systems, such as robotic instruments.The authors wish to thank the staff and patients of the Servicio de Neurorrehabilitación y Daño Cerebral de los Hospitales NISA for their involvement in the study. The authors also wish to thank the staff of LabHuman for their support in this project, especially Francisco Toledo and José Roda for their assistance. This study was funded in part by the Project TEREHA (IDI-20110844) and Project NeuroVR (TIN2013-44741-R) of the Ministerio de Economia y Competitividad of Spain, the Project Consolider-C (SEJ2006-14301/PSIC) of the Ministerio de Educacion y Ciencia of Spain, the "CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII", and the Excellence Research Program PROMETEO of the Conselleria de Educacion of Generalitat Valenciana (2008-157).Colomer Font, C.; Llorens Rodríguez, R.; Noé Sebastián, E.; Alcañiz Raya, ML. (2016). Effect of a mixed reality-based intervention on arm, hand, and finger function on chronic stroke. Journal of NeuroEngineering and Rehabilitation. 13:1-10. https://doi.org/10.1186/s12984-016-0153-6S11013Fregni F, Pascual-Leone A. Hand motor recovery after stroke: tuning the orchestra to improve hand motor function. Cogn Behav Neurol. 2006;19(1):21–33.Patten C, Condliffe EG, Dairaghi CA, Lum PS. Concurrent neuromechanical and functional gains following upper-extremity power training post-stroke. J Neuroeng Rehabil. 2013;10:1.Turolla A, Dam M, Ventura L, Tonin P, Agostini M, Zucconi C, et al. Virtual reality for the rehabilitation of the upper limb motor function after stroke: a prospective controlled trial. J Neuroeng Rehabil. 2013;10:85.Dancause N, Nudo RJ. Shaping plasticity to enhance recovery after injury. Prog Brain Res. 2011;192:273–95.Kwakkel G, Kollen B, Lindeman E. Understanding the pattern of functional recovery after stroke: facts and theories. Restor Neurol Neurosci. 2004;22(3–5):281–99.Nielsen JB, Willerslev-Olsen M, Christiansen L, Lundbye-Jensen J, Lorentzen J. Science-based neurorehabilitation: recommendations for neurorehabilitation from basic science. J Mot Behav. 2015;47(1):7–17.Shaughnessy M, Resnick BM. Using theory to develop an exercise intervention for patients post stroke. Top Stroke Rehabil. 2009;16(2):140–6.Subramanian SK, Massie CL, Malcolm MP, Levin MF. Does provision of extrinsic feedback result in improved motor learning in the upper limb poststroke? A systematic review of the evidence. Neurorehabil Neural Repair. 2010;24(2):113–24.Arya KN, Verma R, Garg RK, Sharma VP, Agarwal M, Aggarwal GG. Meaningful task-specific training (MTST) for stroke rehabilitation: a randomized controlled trial. Top Stroke Rehabil. 2012;19(3):193–211.Levin MF, Weiss PL, Keshner EA. Emergence of Virtual Reality as a Tool for Upper Limb Rehabilitation: Incorporation of Motor Control and Motor Learning Principles. Phys Ther. 2015;95(3):415–25.Laver K, George S, Thomas S, Deutsch JE, Crotty M. Cochrane review: virtual reality for stroke rehabilitation. Eur J Phys Rehabil Med. 2012;48(3):523–30.Cameirao MS, Badia SB, Duarte E, Frisoli A, Verschure PF. The combined impact of virtual reality neurorehabilitation and its interfaces on upper extremity functional recovery in patients with chronic stroke. Stroke. 2012;43(10):2720–8.Saposnik G, Levin M, G. Outcome Research Canada Working. Virtual reality in stroke rehabilitation: a meta-analysis and implications for clinicians. Stroke. 2011;42(5):1380–6.Viau A, Feldman AG, McFadyen BJ, Levin MF. Reaching in reality and virtual reality: a comparison of movement kinematics in healthy subjects and in adults with hemiparesis. J Neuroeng Rehabil. 2004;1(1):11.Thornton M, Marshall S, McComas J, Finestone H, McCormick A, Sveistrup H. Benefits of activity and virtual reality based balance exercise programmes for adults with traumatic brain injury: perceptions of participants and their caregivers. Brain Inj. 2005;19(12):989–1000.Mazzoleni S, Puzzolante L, Zollo L, Dario P, Posteraro F. Mechanisms of motor recovery in chronic and subacute stroke patients following a robot-aided training. IEEE Trans Haptics. 2014;7(2):175–80.Duff M, Chen Y, Cheng L, Liu SM, Blake P, Wolf SL, et al. Adaptive mixed reality rehabilitation improves quality of reaching movements more than traditional reaching therapy following stroke. Neurorehabil Neural Repair. 2013;27(4):306–15.Mousavi Hondori, H., M. Khademi, L. Dodakian, A. McKenzie, C.V. Lopes, and S.C. Cramer, Choice of Human-Computer Interaction Mode in Stroke Rehabilitation. Neurorehabil Neural Repair, 2015.Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67(2):206–7.Paternostro-Sluga T, Grim-Stieger M, Posch M, Schuhfried O, Vacariu G, Mittermaier C, et al. Reliability and validity of the Medical Research Council (MRC) scale and a modified scale for testing muscle strength in patients with radial palsy. J Rehabil Med. 2008;40(8):665–71.Kopp B, Kunkel A, Flor H, Platz T, Rose U, Mauritz KH, et al. The Arm Motor Ability Test: reliability, validity, and sensitivity to change of an instrument for assessing disabilities in activities of daily living. Arch Phys Med Rehabil. 1997;78(6):615–20.Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189–98.Romero M, Sanchez A, Marin C, Navarro MD, Ferri J, Noe E. Clinical usefulness of the Spanish version of the Mississippi Aphasia Screening Test (MASTsp): validation in stroke patients. Neurologia. 2012;27(4):216–24.Llorens R, Marín C, Ortega M, Alcaniz M, Colomer C, Navarro MD, et al. Upper limb tracking using depth information for rehabilitative tangible tabletop systems, in 9th International Conference on Disability, Virtual Reality & Associated Technologies. Laval, France: The University of Reading; 2012. p. 463–466.Alt Murphy M, Resteghini C, Feys P, Lamers I. An overview of systematic reviews on upper extremity outcome measures after stroke. BMC Neurol. 2015;15:29.Sloan RL, Sinclair E, Thompson J, Taylor S, Pentland B. Inter-rater reliability of the modified Ashworth Scale for spasticity in hemiplegic patients. Int J Rehabil Res. 1992;15(2):158–61.van der Ploeg RJ, Fidler V, Oosterhuis HJ. Hand-held myometry: reference values. J Neurol Neurosurg Psychiatry. 1991;54(3):244–7.Duncan PW, Propst M, Nelson SG. Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther. 1983;63(10):1606–10.Miyamoto S, Kondo T, Suzukamo Y, Michimata A, Izumi S. Reliability and validity of the Manual Function Test in patients with stroke. Am J Phys Med Rehabil. 2009;88(3):247–55.Woodbury M, Velozo CA, Thompson PA, Light K, Uswatte G, Taub E, et al. Measurement structure of the Wolf Motor Function Test: implications for motor control theory. Neurorehabil Neural Repair. 2010;24(9):791–801.Mathiowetz V, Volland G, Kashman N, Weber K. Adult norms for the Box and Block Test of manual dexterity. Am J Occup Ther. 1985;39(6):386–91.Oxford Grice K, Vogel KA, Le V, Mitchell A, Muniz S, Vollmer MA. Adult norms for a commercially available Nine Hole Peg Test for finger dexterity. Am J Occup Ther. 2003;57(5):570–3.Hammer AM, Lindmark B. Responsiveness and validity of the Motor Activity Log in patients during the subacute phase after stroke. Disabil Rehabil. 2010;32(14):1184–93.Bullinger HJ, F.-I.f.A.u. Organisation, and U.S.I.f.A.u. Technologiemanagement. Human Aspects in Computing: Design and use of interactive systems and work with terminals. Elsevier; 1991.McAuley E, Duncan T, Tammen VV. Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis. Res Q Exerc Sport. 1989;60(1):48–58.Mazzoleni S, Sale P, Tiboni M, Franceschini M, Carrozza MC, Posteraro F. Upper limb robot-assisted therapy in chronic and subacute stroke patients: a kinematic analysis. Am J Phys Med Rehabil. 2013;92(10 Suppl 2):e26–37.Lin KC, Hsieh YW, Wu CY, Chen CL, Jang Y, Liu JS. Minimal detectable change and clinically important difference of the Wolf Motor Function Test in stroke patients. Neurorehabil Neural Repair. 2009;23(5):429–34.Fu TS, Wu CY, Lin KC, Hsieh CJ, Liu JS, Wang TN, et al. Psychometric comparison of the shortened Fugl-Meyer Assessment and the streamlined Wolf Motor Function Test in stroke rehabilitation. Clin Rehabil. 2012;26(11):1043–7.Hsieh YW, Wu CY, Lin KC, Chang YF, Chen CL, Liu JS. Responsiveness and validity of three outcome measures of motor function after stroke rehabilitation. Stroke. 2009;40(4):1386–91.van der Lee JH, Beckerman H, Lankhorst GJ, Bouter LM. The responsiveness of the Action Research Arm test and the Fugl-Meyer Assessment scale in chronic stroke patients. J Rehabil Med. 2001;33(3):110–3.Wolf SL, Catlin PA, Ellis M, Archer AL, Morgan B, Piacentino A. Assessing Wolf Motor Function Test as Outcome Measure for Research in Patients After Stroke. Stroke. 2001;32(7):1635–9.Reinkensmeyer DJ, Wolbrecht ET, Chan V, Chou C, Cramer SC, Bobrow JE. Comparison of three-dimensional, assist-as-needed robotic arm/hand movement training provided with Pneu-WREX to conventional tabletop therapy after chronic stroke. Am J Phys Med Rehabil. 2012;91(11 Suppl 3):S232–41.Takahashi CD, Der-Yeghiaian L, Le V, Motiwala RR, Cramer SC. Robot-based hand motor therapy after stroke. Brain. 2008;131(Pt 2):425–37.Sale P, Mazzoleni S, Lombardi V, Galafate D, Massimiani MP, Posteraro F, et al. Recovery of hand function with robot-assisted therapy in acute stroke patients: a randomized-controlled trial. Int J Rehabil Res. 2014;37(3):236–42.Hwang CH, Seong JW, Son DS. Individual finger synchronized robot-assisted hand rehabilitation in subacute to chronic stroke: a prospective randomized clinical trial of efficacy. Clin Rehabil. 2012;26(8):696–704.Timmermans AA, Seelen HA, Willmann RD, Kingma H. Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design. J Neuroeng Rehabil. 2009;6:1.Levin MF, Kleim JA, Wolf SL. What do motor “recovery” and “compensation” mean in patients following stroke? Neurorehabil Neural Repair. 2009;23(4):313–9.Rosati G, Oscari F, Spagnol S, Avanzini F, Masiero S. Effect of task-related continuous auditory feedback during learning of tracking motion exercises. J Neuroeng Rehabil. 2012;9:79.Imam B, Jarus T. Virtual reality rehabilitation from social cognitive and motor learning theoretical perspectives in stroke population. Rehabil Res Pract. 2014;2014:594540.Schuster-Amft C, Henneke A, Hartog-Keisker B, Holper L, Siekierka E, Chevrier E, et al. Intensive virtual reality-based training for upper limb motor function in chronic stroke: a feasibility study using a single case experimental design and fMRI. Disabil Rehabil Assist Technol. 2015;10(5):385–92.Llorens R, Noe E, Colomer C, Alcaniz M. Effectiveness, usability, and cost-benefit of a virtual reality-based telerehabilitation program for balance recovery after stroke: a randomized controlled trial. Arch Phys Med Rehabil. 2015;96(3):418–25. e2.Llorens R, Gil-Gomez JA, Alcaniz M, Colomer C, Noe E. Improvement in balance using a virtual reality-based stepping exercise: a randomized controlled trial involving individuals with chronic stroke. Clin Rehabil. 2015;29(3):7