Motor execution detection based on autonomic nervous system responses

Physiological Measurement

Volumn 34, Issue 1, 2013, Pages 35-51

  Marchal Crespo, Laura ^a,b   Zimmermann, Raphael ^a,c   Lambercy, Olivier ^a   Edelmann, Janis ^a   Fluet, Marie Christine ^a   Wolf, Martin ^c   Gassert, Roger ^a   Riener, Robert ^a,b  

^a ETH ZURICH   (Switzerland)

^b BALGRIST UNIVERSITY HOSPITAL   (Switzerland)

^c UNIVERSITY HOSPITAL ZURICH   (Switzerland)

Author keywords

autonomic nervous system; body machine interface; hidden Markov model; physiological measurements; robot assisted rehabilitation

Indexed keywords

BLOOD PRESSURE; PHYSIOLOGICAL MODELS; ROBOTICS;

AUTONOMIC NERVOUS; AUTONOMIC NERVOUS SYSTEM; BODY-MACHINE INTERFACE; HIDDEN-MARKOV MODELS; MACHINE INTERFACES; MOTOR CONTROL; PHYSIOLOGICAL MEASUREMENT; ROBOT-ASSISTED REHABILITATION; ROBOTIC DEVICES; SYSTEM RESPONSE;

HIDDEN MARKOV MODELS;

EID: 84871412839     PISSN: 09673334     EISSN: 13616579     Source Type: Journal    
DOI: 10.1088/0967-3334/34/1/35     Document Type: Article

References (41)

1. Birbaumer N 2006 Brain-computer interface research: coming of age Clin. Neurophysiol. 117 479-83 (Pubitemid 43343979)
2. Blain S, Chau T and Mihailidis A 2008 Peripheral autonomic signals as access pathways for individuals with severe disabilities: a literature appraisal Open Rehabil. J. 1 27-37
3. Boye A T, Kristiansen U Q, Billinger M, do Nascimento O F and Farina D 2008 Identification of movement-related cortical potentials with optimized spatial filtering and principal component analysis Biomed. Signal Process. Control 3 300-4
4. Cariga P, Catley M, Mathias C J, Savic G, Frankel H L and Ellaway P H 2002 Organisation of the sympathetic skin response in spinal cord injury J. Neurol. Neurosurg. Psychiatry 72 356-60 (Pubitemid 34185206)
5. Christov I 2004 Real time electrocardiogram QRS detection using combined adaptive threshold Biomed. Eng. Online 3 28 (Pubitemid 40180331)
6. Collet C, Averty P and Dittmar A 2009 Autonomic nervous system and subjective ratings of strain in air-traffic control Appl. Ergon. 40 23-32
7. Coyle S, Ward T, Markham C and McDarby G 2004 On the suitability of near-infrared (NIR) systems for next-generation brain-computer interfaces Physiol. Meas. 25 815-22 (Pubitemid 39121166)
8. del R Millan J et al 2010 Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges Front. Neurosci. 4 161
9. Falk T H, Guirgis M, Power S, Blain S and Chau T 2010 On the use of peripheral autonomic signals for binary control of body-machine interfaces Physiol. Meas. 31 1411
10. Falk T, Guirgis M, Power S and Chau T 2011 Taking NIRS-BCIs outside the lab: towards achieving robustness against environment noise IEEE Trans. Neural Syst. Rehabil. Eng. 19 136-46
11. Kim J and Andre E 2008 Emotion recognition based on physiological changes in music listening IEEE Trans. Pattern Anal. Mach. Intell. 30 2067-83
12. Koenig A, Novak D, Omlin X, Pulfer M, Perreault E, Zimmerli L, Mihelj M and Riener R 2011 Real-time closed-loop control of cognitive load in neurological patients during robot-assisted gait training IEEE Trans. Neural Syst. Rehabil. Eng. 19 453-64
13. Korpelainen J, Sotaniemi K and Myllylä V 1999 Autonomic nervous system disorders in stroke Clin. Auton. Res. 9 325-33
14. Korpelainen J, Tolonen U, Sotaniemi K and Myllyla V 1993 Suppressed sympathetic skin response in brain infarction Stroke 24 1389-92 (Pubitemid 23254645)
15. Kulic D and Croft E 2007 Affective state estimation for human-robot interaction IEEE Trans. Robot. 23 991-1000 (Pubitemid 47577975)
16. Kushki A, Andrews A J, Power S D, King G and Chau T 2012 Classification of activity engagement in individuals with severe physical disabilities using signals of the peripheral nervous system PLoS One 7 e30373
17. Lee S, Halder S, Kübler A, Birbaumer N and Sitaram R 2010 Effective functional mapping of fMRI data with support-vector machines Human Brain Mapp. 31 1502-11
18. Lotze M, Braun C, Birbaumer N, Anders S and Cohen L G 2003 Motor learning elicited by voluntary drive Brain 126 866-72 (Pubitemid 36372985)
19. Malmivuo J and Plonsey R 1995 The Electrodermal Response (New York: Oxford University Press)
20. Marchal-Crespo L and Reinkensmeyer D 2009 Review of control strategies for robotic movement training after neurologic injury J. Neuroeng. Rehabil. 6 20
21. Muller-Putz G, Scherer R, Brunner C, Leeb R and Pfurtscheller G 2008 Better than random? a closer look on BCI results Int. J. Bioelectromagn. 10 52-5
22. Murphy K 1998 Hidden Markov model (HMM) toolbox for Matlab, version 3 (PMTK3) http://www.cs.ubc.ca/ murphyk/Software/HMM/hmm.html
23. Novak D, Mihelj M, Ziherl J, Olensek A and Munih M 2011 Psychophysiological measurements in a biocooperative feedback loop for upper extremity rehabilitation IEEE Trans. Neural Syst. Rehabil. Eng. 19 400-10
24. Obermaier B, Guger C, Neuper C and Pfurtscheller G 2001 Hidden Markov models for online classification of single trial eeg data Pattern Recognit. Lett. RECPAD2000: Proc. 11th Portuguese Conf. on Pattern Recognition 1299-309 (selected paper) (Pubitemid 32784363)
25. Perez M A, Lungholt B K, Nyborg K and Nielsen J B 2004 Motor skill training induces changes in the excitability of the leg cortical area in healthy humans Exp. Brain Res. 159 197-205 (Pubitemid 40022234)
26. Pfurtscheller G, Allison B Z, Bauernfeind G, Brunner C, Escalante T S, Scherer R, Zander T O, Mueller-Putz G, Neuper C and Birbaumer N 2010 The hybrid BCI Front. Neurosci. 4 42
27. Power S D, Falk T H and Chau T 2010 Classification of prefrontal activity due to mental arithmetic and music imagery using hidden Markov models and frequency domain near-infrared spectroscopy J. Neural Eng. 7 026002
28. Rabiner L 1989 A tutorial on hidden Markov models and selected applications in speech recognition Proc. IEEE 77 257-86
29. Rossini P M and Dal Forno G 2004 Integrated technology for evaluation of brain function and neural plasticity Phys. Med. Rehabil. Clin. North Am. 15 263-306 (Pubitemid 38210043)
30. Scheirer J, Fernandez R, Klein J and P R W 2002 Frustrating the user on purpose: a step toward building an affective computer Interact. Comput. 14 93-118 (Pubitemid 34199154)
31. Sharma N, Pomeroy V M and Baron J-C 2006 Motor imagery Stroke 37 1941-52 (Pubitemid 44297755)
32. Sitaram R, Zhang H, Guan C, Thulasidas M, Hoshi Y, Ishikawa A, Shimizu K and Birbaumer N 2007 Temporal classification of multichannel near-infrared spectroscopy signals of motor imagery for developing a brain-computer interface Neuroimage 34 1416-27 (Pubitemid 46187084)
33. Task Force of the European Society of Cardiology the North American Society of Pacing Electrophysiology 1996 Heart rate variability: standards of measurement, physiological interpretation, and clinical use Circulation 93 1043-65
34. Tsui C, Gan J and Roberts S 2009 A self-paced brain-computer interface for controlling a robot simulator: an online event labelling paradigm and an extended Kalman filter based algorithm for online training Med. Biol. Eng. Comput. 47 257-65
35. van Gerven M et al 2009 The brain-computer interface cycle J. Neural Eng. 6 041001
36. Wagner J, Kim J and Andre E 2005 From physiological signals to emotions: implementing and comparing selected methods for feature extraction and classification Multimedia and Expo 2005: IEEE Conf. Proc. on (ICME 2005) pp 940-3 (Pubitemid 44669023)
37. Wilson G and Russell C 2003 Real-time assessment of mental workload using psychophysiological measures and artificial neural networks Hum. Factors 45 635-43 (Pubitemid 38280613)
38. Yokota T, Matsunaga T, Okiyama R, Hirose K, Tanabe H, Furukawa T and Tsukagoshi H 1991 Sympathetic skin response in patients with multiple sclerosis compared with patients with spinal cord transection and normal controls Brain 114 1381-94
39. Zimmerli L, Krewer C, Gassert R, Muller F, Riener R and Lunenburger L 2012 Validation of a mechanism to balance exercise difficulty in robot-assisted upper-extremity rehabilitation after stroke J. Neuroeng. Rehabil. 9 6
40. Zimmermann R, Marchal-Crespo L, Edelmann J, Lambercy O, Fluet M, Riener R, Wolf M and Gassert R 2012 Detection of motor execution using a hybrid fNIRS-biosignal BCI: a feasibility study J. Neuroeng. Rehabil. at press
41. Zimmermann R, Marchal-Crespo L, Lambercy O, Fluet M, Riener R, Wolf M and Gassert R 2011 Towards a BCI for sensorimotor training: initial results from simultaneous fNIRS and biosignal recordings EMBC'11: Proc. 33rd Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. pp 6339-43