Human-Robot Interaction: Does Robotic Guidance Force Affect Gait-Related Brain Dynamics during Robot-Assisted Treadmill Walking?

Kristel Knaepen, Andreas Mierau, Eva Swinnen, Helio Fernandez Tellez, Marc Michielsen, Eric Kerckhofs, Dirk Lefeber, Romain Meeusen, Kristel Knaepen, Andreas Mierau, Eva Swinnen, Helio Fernandez Tellez, Marc Michielsen, Eric Kerckhofs, Dirk Lefeber, Romain Meeusen

Abstract

In order to determine optimal training parameters for robot-assisted treadmill walking, it is essential to understand how a robotic device interacts with its wearer, and thus, how parameter settings of the device affect locomotor control. The aim of this study was to assess the effect of different levels of guidance force during robot-assisted treadmill walking on cortical activity. Eighteen healthy subjects walked at 2 km.h-1 on a treadmill with and without assistance of the Lokomat robotic gait orthosis. Event-related spectral perturbations and changes in power spectral density were investigated during unassisted treadmill walking as well as during robot-assisted treadmill walking at 30%, 60% and 100% guidance force (with 0% body weight support). Clustering of independent components revealed three clusters of activity in the sensorimotor cortex during treadmill walking and robot-assisted treadmill walking in healthy subjects. These clusters demonstrated gait-related spectral modulations in the mu, beta and low gamma bands over the sensorimotor cortex related to specific phases of the gait cycle. Moreover, mu and beta rhythms were suppressed in the right primary sensory cortex during treadmill walking compared to robot-assisted treadmill walking with 100% guidance force, indicating significantly larger involvement of the sensorimotor area during treadmill walking compared to robot-assisted treadmill walking. Only marginal differences in the spectral power of the mu, beta and low gamma bands could be identified between robot-assisted treadmill walking with different levels of guidance force. From these results it can be concluded that a high level of guidance force (i.e., 100% guidance force) and thus a less active participation during locomotion should be avoided during robot-assisted treadmill walking. This will optimize the involvement of the sensorimotor cortex which is known to be crucial for motor learning.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Scalp map, PSD, dipole locations…
Fig 1. Scalp map, PSD, dipole locations and ERSPs for cluster 3, located in the midline PMC & SMA.
(A) Cluster average scalp projection; (B) Gait cycle PSD for G, 30% GF, 60% GF and 100% GF; (C) Dipole locations of cluster ICs (blue spheres) and cluster centroids (red sphere) visualized in the MNI brain volume in coronal and sagittal views; (D) average cluster ERSP (3–45 Hz) plots showing significant changes in spectral power relative to the full gait cycle baseline (p<.05 for g gf and gf. non-significant differences relative to the full gait cycle baseline are masked in green db starts ends with r hs vertical line at of marks l hs.>

Fig 2. Scalp map, PSD, dipole locations…

Fig 2. Scalp map, PSD, dipole locations and ERSPs for cluster 6, located in the…

Fig 2. Scalp map, PSD, dipole locations and ERSPs for cluster 6, located in the left SA.
(A) Cluster average scalp projection; (B) Gait cycle PSD for G, 30% GF, 60% GF and 100% GF; (C) Dipole locations of cluster ICs (blue spheres) and cluster centroids (red sphere) visualized in the MNI brain volume in coronal and sagittal views; (D) average cluster ERSP (3–45 Hz) plots showing significant changes in spectral power relative to the full gait cycle baseline (p<.05 for g gf and gf. non-significant differences relative to the full gait cycle baseline are masked in green db starts ends with r hs vertical line at of marks l hs.>

Fig 3. Scalp map, PSD, dipole locations…

Fig 3. Scalp map, PSD, dipole locations and ERSPs for cluster 12, located in the…

Fig 3. Scalp map, PSD, dipole locations and ERSPs for cluster 12, located in the right S1.
(A) Cluster average scalp projection; (B) Gait cycle PSD for G, 30% GF, 60% GF and 100% GF; (C) Dipole locations of cluster ICs (blue spheres) and cluster centroids (red sphere) visualized in the MNI brain volume in coronal and sagittal views; (D) average cluster ERSP (3–45 Hz) plots showing significant changes in spectral power relative to the full gait cycle baseline (p<.05 for g gf and gf. non-significant differences relative to the full gait cycle baseline are masked in green db starts ends with r hs vertical line at of marks l hs.>
Similar articles
Cited by
References
    1. Mehrholz J, Elsner B, Werner C, Kugler J, Pohl M. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. 2013;7:CD006185 Epub 2013/07/28. 10.1002/14651858.CD006185.pub3 . - DOI - PMC - PubMed
    1. Sale P, Franceschini M, Waldner A, Hesse S. Use of the robot assisted gait therapy in rehabilitation of patients with stroke and spinal cord injury. Eur J Phys Rehabil Med. 2012;48(1):111–21. Epub 2012/05/01. doi: R33122769 [pii]. . - PubMed
    1. Ada L, Dean CM, Vargas J, Ennis S. Mechanically assisted walking with body weight support results in more independent walking than assisted overground walking in non-ambulatory patients early after stroke: a systematic review. J Physiother. 2010;56(3):153–61. Epub 2010/08/28. . - PubMed
    1. Shin JC, Kim JY, Park HK, Kim NY. Effect of robotic-assisted gait training in patients with incomplete spinal cord injury. Ann Rehabil Med. 2014;38(6):719–25. Epub 2015/01/08. 10.5535/arm.2014.38.6.719 - DOI - PMC - PubMed
    1. Swinnen E, Beckwee D, Pinte D, Meeusen R, Baeyens JP, Kerckhofs E. Treadmill training in multiple sclerosis: can body weight support or robot assistance provide added value? A systematic review. Mult Scler Int. 2012;2012:240274 Epub 2012/06/16. 10.1155/2012/240274 - DOI - PMC - PubMed
Show all 79 references
Publication types
Grant support
The preparation of this paper was funded by the Vrije Universiteit Brussel (i.e., GOA 59 and the Strategic Research Program ‘Exercise and the Brain in Health & Disease: the Added Value of Human-Centered Robotics’). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
[x]
Cite
Copy Download .nbib
Format: AMA APA MLA NLM

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Follow NCBI
Fig 2. Scalp map, PSD, dipole locations…
Fig 2. Scalp map, PSD, dipole locations and ERSPs for cluster 6, located in the left SA.
(A) Cluster average scalp projection; (B) Gait cycle PSD for G, 30% GF, 60% GF and 100% GF; (C) Dipole locations of cluster ICs (blue spheres) and cluster centroids (red sphere) visualized in the MNI brain volume in coronal and sagittal views; (D) average cluster ERSP (3–45 Hz) plots showing significant changes in spectral power relative to the full gait cycle baseline (p<.05 for g gf and gf. non-significant differences relative to the full gait cycle baseline are masked in green db starts ends with r hs vertical line at of marks l hs.>

Fig 3. Scalp map, PSD, dipole locations…

Fig 3. Scalp map, PSD, dipole locations and ERSPs for cluster 12, located in the…

Fig 3. Scalp map, PSD, dipole locations and ERSPs for cluster 12, located in the right S1.
(A) Cluster average scalp projection; (B) Gait cycle PSD for G, 30% GF, 60% GF and 100% GF; (C) Dipole locations of cluster ICs (blue spheres) and cluster centroids (red sphere) visualized in the MNI brain volume in coronal and sagittal views; (D) average cluster ERSP (3–45 Hz) plots showing significant changes in spectral power relative to the full gait cycle baseline (p<.05 for g gf and gf. non-significant differences relative to the full gait cycle baseline are masked in green db starts ends with r hs vertical line at of marks l hs.>
Similar articles
Cited by
References
    1. Mehrholz J, Elsner B, Werner C, Kugler J, Pohl M. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. 2013;7:CD006185 Epub 2013/07/28. 10.1002/14651858.CD006185.pub3 . - DOI - PMC - PubMed
    1. Sale P, Franceschini M, Waldner A, Hesse S. Use of the robot assisted gait therapy in rehabilitation of patients with stroke and spinal cord injury. Eur J Phys Rehabil Med. 2012;48(1):111–21. Epub 2012/05/01. doi: R33122769 [pii]. . - PubMed
    1. Ada L, Dean CM, Vargas J, Ennis S. Mechanically assisted walking with body weight support results in more independent walking than assisted overground walking in non-ambulatory patients early after stroke: a systematic review. J Physiother. 2010;56(3):153–61. Epub 2010/08/28. . - PubMed
    1. Shin JC, Kim JY, Park HK, Kim NY. Effect of robotic-assisted gait training in patients with incomplete spinal cord injury. Ann Rehabil Med. 2014;38(6):719–25. Epub 2015/01/08. 10.5535/arm.2014.38.6.719 - DOI - PMC - PubMed
    1. Swinnen E, Beckwee D, Pinte D, Meeusen R, Baeyens JP, Kerckhofs E. Treadmill training in multiple sclerosis: can body weight support or robot assistance provide added value? A systematic review. Mult Scler Int. 2012;2012:240274 Epub 2012/06/16. 10.1155/2012/240274 - DOI - PMC - PubMed
Show all 79 references
Publication types
Grant support
The preparation of this paper was funded by the Vrije Universiteit Brussel (i.e., GOA 59 and the Strategic Research Program ‘Exercise and the Brain in Health & Disease: the Added Value of Human-Centered Robotics’). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
[x]
Cite
Copy Download .nbib
Format: AMA APA MLA NLM
Fig 3. Scalp map, PSD, dipole locations…
Fig 3. Scalp map, PSD, dipole locations and ERSPs for cluster 12, located in the right S1.
(A) Cluster average scalp projection; (B) Gait cycle PSD for G, 30% GF, 60% GF and 100% GF; (C) Dipole locations of cluster ICs (blue spheres) and cluster centroids (red sphere) visualized in the MNI brain volume in coronal and sagittal views; (D) average cluster ERSP (3–45 Hz) plots showing significant changes in spectral power relative to the full gait cycle baseline (p<.05 for g gf and gf. non-significant differences relative to the full gait cycle baseline are masked in green db starts ends with r hs vertical line at of marks l hs.>

References

    1. Mehrholz J, Elsner B, Werner C, Kugler J, Pohl M. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. 2013;7:CD006185 Epub 2013/07/28. 10.1002/14651858.CD006185.pub3 .
    1. Sale P, Franceschini M, Waldner A, Hesse S. Use of the robot assisted gait therapy in rehabilitation of patients with stroke and spinal cord injury. Eur J Phys Rehabil Med. 2012;48(1):111–21. Epub 2012/05/01. doi: R33122769 [pii]. .
    1. Ada L, Dean CM, Vargas J, Ennis S. Mechanically assisted walking with body weight support results in more independent walking than assisted overground walking in non-ambulatory patients early after stroke: a systematic review. J Physiother. 2010;56(3):153–61. Epub 2010/08/28. .
    1. Shin JC, Kim JY, Park HK, Kim NY. Effect of robotic-assisted gait training in patients with incomplete spinal cord injury. Ann Rehabil Med. 2014;38(6):719–25. Epub 2015/01/08. 10.5535/arm.2014.38.6.719
    1. Swinnen E, Beckwee D, Pinte D, Meeusen R, Baeyens JP, Kerckhofs E. Treadmill training in multiple sclerosis: can body weight support or robot assistance provide added value? A systematic review. Mult Scler Int. 2012;2012:240274 Epub 2012/06/16. 10.1155/2012/240274
    1. Poli P, Morone G, Rosati G, Masiero S. Robotic technologies and rehabilitation: new tools for stroke patients' therapy. Biomed Res Int. 2013;2013:153872 Epub 2013/12/19. 10.1155/2013/153872
    1. Tefertiller C, Pharo B, Evans N, Winchester P. Efficacy of rehabilitation robotics for walking training in neurological disorders: a review. J Rehabil Res Dev. 2011;48(4):387–416. Epub 2011/06/16. .
    1. Swinnen E, Duerinck S, Baeyens JP, Meeusen R, Kerckhofs E. Effectiveness of robot-assisted gait training in persons with spinal cord injury: a systematic review. J Rehabil Med. 2010;42(6):520–6. Epub 2010/06/16. 10.2340/16501977-0538 .
    1. Carpino G, Accoto D, Tagliamonte NL, Ghilardi G, Guglielmelli E. Lower limb wearable robots for physiological gait restoration: state of the art and motivations. Medic. 2013;21(2):72–80.
    1. Tucker MR, Olivier J, Pagel A, Bleuler H, Bouri M, Lambercy O, et al. Control strategies for active lower extremity prosthetics and orthotics: a review. J Neuroeng Rehabil. 2015;12(1):1 Epub 2015/01/06. 10.1186/1743-0003-12-1 1743-0003-12-1 [pii]. .
    1. Pons JL. Wearable robots: biomechatronic exoskeletons. Chichester, UK: Wiley; 2008.
    1. Knaepen K, Beyl P, Duerinck S, Hagman F, Lefeber D, Meeusen R. Human-Robot Interaction: Kinematics and Muscle Activity inside a Powered Compliant Knee Exoskeleton. IEEE Trans Neural Syst Rehabil Eng. 2014. Epub 2014/05/23. 10.1109/TNSRE.2014.2324153 .
    1. Swinnen E, Baeyens JP, Knaepen K, Michielsen M, Hens G, Clijsen R, et al. Walking with robot assistance: the influence of body weight support on the trunk and pelvis kinematics. Disabil Rehabil Assist Technol. 2014. Epub 2014/02/12. 10.3109/17483107.2014.888487 .
    1. Knaepen K, Marusic U, Crea S, Rodriguez Guerrero CD, Vitiello N, Pattyn N, et al. Psychophysiological response to cognitive workload during symmetrical, asymmetrical and dual-task walking. Hum Mov Sci. 2015;40C:248–63. Epub 2015/01/27. doi: S0167-9457(15)00002-0 [pii] 10.1016/j.humov.2015.01.001 .
    1. Hornby TG, Kinnaird CR, Holleran CL, Rafferty MR, Rodriguez KS, Cain JB. Kinematic, muscular, and metabolic responses during exoskeletal-, elliptical-, or therapist-assisted stepping in people with incomplete spinal cord injury. Phys Ther. 2012;92(10):1278–91. Epub 2012/06/16. 10.2522/ptj.20110310 ptj.20110310 [pii].
    1. Moreno JC, Barroso F, Farina D, Gizzi L, Santos C, Molinari M, et al. Effects of robotic guidance on the coordination of locomotion. J Neuroeng Rehabil. 2013;10:79 Epub 2013/07/23. 10.1186/1743-0003-10-79 1743-0003-10-79 [pii].
    1. Lunenburger L, Colombo G, Riener R. Biofeedback for robotic gait rehabilitation. J Neuroeng Rehabil. 2007;4:1. Epub 2007/01/25. doi: 1743-0003-4-1 [pii] 10.1186/1743-0003-4-1 .
    1. Yuste R, MacLean JN, Smith J, Lansner A. The cortex as a central pattern generator. Nat Rev Neurosci. 2005;6(6):477–83. Epub 2005/06/02. doi: nrn1686 [pii] 10.1038/nrn1686 .
    1. Duysens J, Van de Crommert HW. Neural control of locomotion; The central pattern generator from cats to humans. Gait Posture. 1998;7(2):131–41. Epub 1999/04/14. doi: S0966636297000428 [pii]. .
    1. Pons JL, Moreno JC, Torricelli D, Taylor JS. Principles of human locomotion: a review. Conf Proc IEEE Eng Med Biol Soc. 2013;2013:6941–4. Epub 2013/10/11. 10.1109/EMBC.2013.6611154 .
    1. Wieser M, Haefeli J, Butler L, Jancke L, Riener R, Koeneke S. Temporal and spatial patterns of cortical activation during assisted lower limb movement. Exp Brain Res. 2010;203(1):181–91. Epub 2010/04/07. 10.1007/s00221-010-2223-5 .
    1. Jain S, Gourab K, Schindler-Ivens S, Schmit BD. EEG during pedaling: evidence for cortical control of locomotor tasks. Clin Neurophysiol. 2013;124(2):379–90. Epub 2012/10/06. 10.1016/j.clinph.2012.08.021 S1388-2457(12)00619-0 [pii].
    1. Gwin JT, Gramann K, Makeig S, Ferris DP. Electrocortical activity is coupled to gait cycle phase during treadmill walking. Neuroimage. 2011;54(2):1289–96. Epub 2010/09/14. doi: S1053-8119(10)01163-8 [pii] 10.1016/j.neuroimage.2010.08.066 .
    1. Castermans T, Duvinage M, Cheron G, Dutoit T. About the cortical origin of the low-delta and high-gamma rhythms observed in EEG signals during treadmill walking. Neurosci Lett. 2014;561:166–70. Epub 2014/01/15. 10.1016/j.neulet.2013.12.059 S0304-3940(13)01140-3 [pii]. .
    1. Severens M, Nienhuis B, Desain P, Duysens J. Feasibility of measuring ERD with EEG during walking. Conf Proc IEEE Eng Med Biol Soc. 2012;2012:2764–7. Epub 2013/02/01. 10.1109/EMBC.2012.6346537 .
    1. Kline JE, Poggensee K, Ferris DP. Your brain on speed: cognitive performance of a spatial working memory task is not affected by walking speed. Front Hum Neurosci. 2014;8:288 Epub 2014/05/23. 10.3389/fnhum.2014.00288
    1. Bulea TC, Kim J, Damiano DL, Stanley CJ, Park H, editors. User-Driven Control Increases Cortical Activity during Treadmill Walking: An EEG Study. Conference of the IEEE 36th Annual International Engineering in Medicine and Biology Society (EMBC); 2014; Chicago, USA.
    1. Severens M, Perusquia-Hernandez M, Nienhuis B, Farquhar J, Duysens J. Using actual and imagined walking related desynchronisation features in a BCI. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2014;PP(99):1.
    1. Snyder KL, Vindiola M, Vettel JM, Ferris DP, editors. Cortical Connectivity During Uneven Terrain Walking. 6th Annual International IEEE EMBS Conference on Neural Engineering; 2013 6–8 November 2013; San Diego, California.
    1. Wagner J, Solis-Escalante T, Grieshofer P, Neuper C, Muller-Putz G, Scherer R. Level of participation in robotic-assisted treadmill walking modulates midline sensorimotor EEG rhythms in able-bodied subjects. Neuroimage. 2012;63(3):1203–11. Epub 2012/08/22. 10.1016/j.neuroimage.2012.08.019 S1053-8119(12)00812-9 [pii]. .
    1. Seeber M, Scherer R, Wagner J, Solis-Escalante T, Muller-Putz GR. EEG beta suppression and low gamma modulation are different elements of human upright walking. Front Hum Neurosci. 2014;8:485 Epub 2014/07/30. 10.3389/fnhum.2014.00485
    1. Nakanishi Y, Wada F, Saeki S, Hachisuka K. Rapid changes in arousal states of healthy volunteers during robot-assisted gait training: a quantitative time-series electroencephalography study. J Neuroeng Rehabil. 2014;11:59 Epub 2014/04/15. 10.1186/1743-0003-11-59 1743-0003-11-59 [pii].
    1. Wagner J, Solis-Escalante T, Scherer R, Neuper C, Muller-Putz G. It's how you get there: walking down a virtual alley activates premotor and parietal areas. Front Hum Neurosci. 2014;8:93 Epub 2014/03/13. 10.3389/fnhum.2014.00093
    1. Solis-Escalante T, Wagner J, Scherer R, Grieshofer P, Müller-Putz GR, editors. Assessing participation during robotic assisted gait training based on EEG: feasibility study. Proceedings of the 3rd Tools for Brain-Computer Interaction Workshop; 2012; Würzburg, Germany.
    1. Youssofzadeh V, Zanotto D, Stegall P, Naeem M, Wong-Lin K, Agrawal SK, et al. Directed neural connectivity changes in robot-assisted gait training: a partial Granger causality analysis. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:6361–4. Epub 2015/01/09. 10.1109/EMBC.2014.6945083 .
    1. Castermans T, Duvinage M, Cheron G, Dutoit T, editors. EEG and Human Locomotion: Descending Commands and Sensory Feedback Should be Disentangled From Artifacts Thanks to New Experimental Protocols Position Paper. Proceedings of the BIOSIGNALS 2012 International Conference; 2012; Vilamoura, Portugal.
    1. Castermans T, Duvinage M, Cheron G, Dutoit T. Towards Effective Non-Invasive BCI Dedicated to Gait Rehabilitation Systems. Brain Sci. 2014;4:1–48.
    1. Makeig S. Auditory event-related dynamics of the EEG spectrum and effects of exposure to tones. Electroencephalogr Clin Neurophysiol. 1993;86(4):283–93. Epub 1993/04/01. .
    1. Severens M, Perusquia-Hernandez M, Nienhuis B, Farquhar J, Duysens J. Using actual and imagined walking related desynchronisation features in a BCI. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2014;PP(99):1534–4320.
    1. Bernhardt M, Frey M, Colombo G, Riener R, editors. Force-Position Control Yields Cooperative Behaviour of the Rehabilitation Robot LOKOMAT. Proceedings of IEEE 9th International Conference on Rehabilitation Robotics; 2005; Chicago, IL, USA.
    1. Schuck A, Labruyere R, Vallery H, Riener R, Duschau-Wicke A. Feasibility and effects of patient-cooperative robot-aided gait training applied in a 4-week pilot trial. J Neuroeng Rehabil. 2012;9(1):31. Epub 2012/06/02. doi: 1743-0003-9-31 [pii] 10.1186/1743-0003-9-31 .
    1. Krewer C, Muller F, Husemann B, Heller S, Quintern J, Koenig E. The influence of different Lokomat walking conditions on the energy expenditure of hemiparetic patients and healthy subjects. Gait Posture. 2007;26(3):372–7. Epub 2006/11/23. doi: S0966-6362(06)00309-2 [pii] 10.1016/j.gaitpost.2006.10.003 .
    1. Swinnen E, Baeyens JP, Knaepen K, Michielsen M, Clijsen R, Beckwee D, et al. Robot-assisted walking with the Lokomat: The influence of different levels of guidance force on thorax and pelvis kinematics. Clin Biomech. 2015;In press. 10.1016/j.clinbiomech.2015.01.006
    1. Colombo G, Wirz M, Dietz V. Driven gait orthosis for improvement of locomotor training in paraplegic patients. Spinal Cord. 2001;39(5):252–5. Epub 2001/07/05. 10.1038/sj.sc.3101154 .
    1. Riener R, Lünenburger L, Maier I, Colombo G, Dietz EV. Locomotor Training in Subjects with Sensori-Motor Deficits: An Overview of the Robotic Gait Orthosis Lokomat. Journal of Healthcare Engineering. 2010;2:197–216.
    1. Jasper HH. The ten-twenty electrode system of the International Federation. Electroencephalogr Clin Neurophysiol. 1958;10(2):371–5.
    1. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including ICA. J Neurosci Methods. 2004;134(1):9–21. Epub 2004/04/23. 10.1016/j.jneumeth.2003.10.009 S0165027003003479 [pii]. .
    1. Makeig S, Bell AJ, Jung TP, Sejnowski TJ. Independent component analysis fof electroencephalographic data. Adv Neural Inf Process Syst. 1996;8:145–51.
    1. Oostenveld R, Oostendorp TF. Validating the boundary element method for forward and inverse EEG computations. Hum Brain Mapp. 2002;17(3):179–92. Epub 2002/10/23. 10.1002/hbm.10061 .
    1. McMenamin BW, Shackman AJ, Maxwell JS, Bachhuber DRW, Koppenhaver AM, Greischar LL, et al. Validation of ICA-based myogenic artifact correction for scalp and source-localized EEG. Neuroimage. 2010;49:2416–32. 10.1016/j.neuroimage.2009.10.010
    1. Jung TP, Makeig S, Humphries C, Lee TW, McKeown MJ, Iragui V, et al. Removing EEG artifacts by blind source separation. Psychophysiology. 2000;37(2):163–78. Epub 2000/03/25. .
    1. Kline JE, Huang HJ, Snyder KL, Ferris DP. Isolating gait-related movement artifacts in electroencephalography during human walking. J Neural Eng. 2015;12(4):046022 Epub 2015/06/18. 10.1088/1741-2560/12/4/046022 .
    1. Gramann K, Onton J, Riccobon D, Mueller HJ, Bardins S, Makeig S. Human brain dynamics accompanying use of egocentric and allocentric reference frames during navigation. J Cogn Neurosci. 2009;22:2836–49.
    1. Jung TP, Makeig S, Westerfield M, Townsend J, Courchesne E, Sejnowski TJ. Analysis and visualization of single-trial event-related potentials. Hum Brain Mapp. 2001;14(3):166–85. Epub 2001/09/18. 10.1002/hbm.1050 [pii]. .
    1. Wilcox RR. Introduction to Robust Estimation and Hypothesis Testing. New York: Academic Press; 2005.
    1. Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Ann Stat. 2001;29:1165–88.
    1. Sahyoun C, Floyer-Lea A, Johansen-Berg H, Matthews PM. Towards an understanding of gait control. Neuroimage. 2004;21(2):568–75. Epub 2004/02/26. 10.1016/j.neuroimage.2003.09.065 S105381190300644X [pii]. .
    1. Lajoie K, Andujar JE, Pearson K, Drew T. Neurons in area 5 of the posterior parietal cortex in the cat contribute to interlimb coordination during visually guided locomotion: a role in working memory. J Neurophysiol. 2010;103(4):2234–54. Epub 2010/04/14. 10.1152/jn.01100.2009 103/4/2234 [pii]. .
    1. Neuper C, Wortz M, Pfurtscheller G. ERD/ERS patterns reflecting sensorimotor activation and deactivation. Prog Brain Res. 2006;159:211–22. Epub 2006/10/31. doi: S0079-6123(06)59014-4 [pii] 10.1016/S0079-6123(06)59014-4 .
    1. Pfurtscheller G, Lopes da Silva FH. Event-related EEG/MEG synchronization and desynchronization: basic principles. Clin Neurophysiol. 1999;110(11):1842–57. Epub 1999/11/27. doi: S1388245799001418 [pii]. .
    1. Hummel F, Andres F, Altenmuller E, Dichgans J, Gerloff C. Inhibitory control of acquired motor programmes in the human brain. Brain. 2002;125(Pt 2):404–20. Epub 2002/02/15. .
    1. Van Kammen K, Boonstra A, Reinders-Messelink H, den Otter R. The Combined Effects of Body Weight Support and Gait Speed on Gait Related Muscle Activity: A Comparison between Walking in the Lokomat Exoskeleton and Regular Treadmill Walking. PLoS One. 2014;9(9):e107323 10.1371/journal.pone.0107323
    1. Petersen TH, Willerslev-Olsen M, Conway BA, Nielsen JB. The motor cortex drives the muscles during walking in human subjects. J Physiol. 2012;590(Pt 10):2443–52. Epub 2012/03/07. 10.1113/jphysiol.2012.227397 jphysiol.2012.227397 [pii].
    1. Feige B, Aertsen A, Kristeva-Feige R. Dynamic synchronization between multiple cortical motor areas and muscle activity in phasic voluntary movements. J Neurophysiol. 2000;84(5):2622–9. Epub 2000/11/09. .
    1. Presacco A, Goodman R, Forrester L, Contreras-Vidal JL. Neural decoding of treadmill walking from noninvasive electroencephalographic signals. J Neurophysiol. 2011;106(4):1875–87. Epub 2011/07/20. 10.1152/jn.00104.2011 jn.00104.2011 [pii].
    1. Jasper H, Penfield W. Electrocorticograms in man: effect of voluntary movement upon the electrical activity of the precentral gyrus. Arch Psychiatr Zeitschr Neurol. 1949;83:163–74.
    1. Steriade M, Llinas RR. The functional states of the thalamus and the associated neuronal interplay. Physiological reviews. 1988;68(3):649–742. Epub 1988/07/01. .
    1. Pfurtscheller G. Event-related synchronization (ERS): an electrophysiological correlate of cortical areas at rest. Electroencephalogr Clin Neurophysiol. 1992;83(1):62–9. Epub 1992/07/01. .
    1. Lotze M, Braun C, Birbaumer N, Anders S, Cohen LG. Motor learning elicited by voluntary drive. Brain. 2003;126(Pt 4):866–72. Epub 2003/03/05. .
    1. Brinkman L, Stolk A, Dijkerman HC, de Lange FP, Toni I. Distinct roles for alpha- and beta-band oscillations during mental simulation of goal-directed actions. J Neurosci. 2014;34(44):14783–92. Epub 2014/10/31. 10.1523/JNEUROSCI.2039-14.2014 34/44/14783 [pii].
    1. Brown P. Abnormal oscillatory synchronisation in the motor system leads to impaired movement. Curr Opin Neurobiol. 2007;17(6):656–64. Epub 2008/01/29. 10.1016/j.conb.2007.12.001 S0959-4388(07)00136-5 [pii]. .
    1. Crone NE, Miglioretti DL, Gordon B, Lesser RP. Functional mapping of human sensorimotor cortex with electrocorticographic spectral analysis. II. Event-related synchronization in the gamma band. Brain. 1998;121 (Pt 12):2301–15. Epub 1999/01/05. .
    1. Nobre AC, Sebestyen GN, Gitelman DR, Mesulam MM, Frackowiak RS, Frith CD. Functional localization of the system for visuospatial attention using positron emission tomography. Brain. 1997;120 (Pt 3):515–33. Epub 1997/03/01. .
    1. Mesulam MM. A cortical network for directed attention and unilateral neglect. Ann Neurol. 1981;10(4):309–25. Epub 1981/10/01. 10.1002/ana.410100402 .
    1. Coghill RC, Gilron I, Iadarola MJ. Hemispheric lateralization of somatosensory processing. J Neurophysiol. 2001;85(6):2602–12. Epub 2001/06/02. .
    1. Serrien DJ, Ivry RB, Swinnen SP. Dynamics of hemispheric specialization and integration in the context of motor control. Nat Rev Neurosci. 2006;7(2):160–6. Epub 2006/01/24. doi: nrn1849 [pii] 10.1038/nrn1849 .
    1. Nymark JR, Balmer SJ, Melis EH, Lemaire ED, Millar S. Electromyographic and kinematic nondisabled gait differences at extremely slow overground and treadmill walking speeds. J Rehabil Res Dev. 2005;42(4):523–34. Epub 2005/12/02. .
    1. Aguirre-Ollinger G, Colgate JE, Peshkin MA, Goswami A. A one-degree-of-freedom assistive exoskeleton with inertia compensation: the effects on the agility of leg swing motion. Proc Inst Mech Eng H. 2011;225(3):228–45. Epub 2011/04/13. .
    1. Lau TM, Gwin JT, Ferris DP. How Many Electrodes Are Really Needed for EEG-Based Mobile Brain Imaging? Journal of Behavioral and Brain Science. 2012;2:387–93.

Source: PubMed

スポンサーと協力者

医学的状態

薬物療法

3
購読する