8
Advances in Neural Signal Processing
[1] Wonham W. The internal model
principle of control theory. Automatica.
1976;12(5):457-465
[2] Kawato M, Wolpert D. Internal
models for motor control. In: Sensory
Guidance of Movement; 1998. pp.
291-307
[3] Fransen AMM, van Ede F, Maris E.
Identifying neuronal oscillations using
rhythmicity. NeuroImage. 2015;118:
256-267
[4] Cabral Jr F, Pinna MH, Alves RD,
Malerbi AFDS, Bento RF. Cochlear
implantation and single-sided
deafness: A systematic review of the
literature. International Archives of
Otorhinolaryngology. 2014;20(1):69-75
[5] Hitti FL, Ramayya AG, Mcshane BJ,
Yang AI, Vaughan KA, Baltuch GH.
Long-term outcomes following deep
brain stimulation for Parkinson’s
disease. Journal of Neurosurgery.
2019;132(1):1-6
[6] Monge-Pereira E, Ibañez-Pereda J,
Alguacil-Diego IM, Serrano JI,
Spottorno-Rubio MP, Molina-Rueda F.
Use of electroencephalography braincomputer interface systems as a
rehabilitative approach for upper limb
function after a stroke: A systematic
review. PM & R: The Journal of
Injury, Function, and Rehabilitation.
2017;9(9):918-932
[7] Frolov AA, Mokienko O,
Lyukmanov R, Biryukova E,
Kotov S, Turbina L, et al. Post-stroke
rehabilitation training with a motorimagery-based brain-computer interface
(BCI)-controlled hand exoskeleton: A
randomized controlled multicenter trial.
Frontiers in Neuroscience. 2017;11(JUL)
[8] Burns MK, Pei D, Vinjamuri R.
Myoelectric control of a soft hand
exoskeleton using kinematic synergies.
IEEE Transactions on
Biomedical Circuits and Systems.
2019;13(6):1351-1361
[9] Velliste M, Perel S, Spalding MC,
Whitford AS, Schwartz AB.
Cortical control of a prosthetic
arm for self-feeding. Nature.
2008;453(7198):1098-1101
[10] Yanagisawa TT, Hirata M,
Saitoh Y, Kishima H, Matsushita K,
Goto T, et al. Electrocorticographic
control of a prosthetic arm in paralyzed
patients. Annals of Neurology.
2012;71(3):353-361
[11] Bright D, Nair A, Salvekar D,
Bhisikar S. EEG-based brain controlled
prosthetic arm. Conference on Advances
in Signal Processing (CASP) 2016. 2016.
pp. 479-483
[12] Pei D, Burns M, Chandramouli R,
Vinjamuri R. Decoding asynchronous
reaching in electroencephalography
using stacked autoencoders. IEEE
Access. 2018;6:52889-52898
[13] Pei D, Patel V, Burns M,
Chandramouli R, Vinjamuri R.
Neural decoding of synergybased hand movements using
electroencephalography. IEEE Access.
2019;7:18155-18163
[14] Patel V, Burns M, Pei D,
Vinjamuri R. Decoding synergy-based
hand movements using
electroencephalography. In: 40th
Annual International Conference of
the IEEE Engineering in Medicine and
Biology Society (EMBC). 2018. pp.
4816-4819
[15] Elger CE, Hoppe C. Diagnostic
challenges in epilepsy: Seizure underreporting and seizure detection. Lancet
Neurology. 2018;17(3):279-288
[16] James CJ, Jones RD, Bones PJ,
Carroll GJ. Detection of epileptiform
References
Advances in Neural Signal Processing
[1] Wonham W. The internal model
principle of control theory. Automatica.
1976;12(5):457-465
[2] Kawato M, Wolpert D. Internal
models for motor control. In: Sensory
Guidance of Movement; 1998. pp.
291-307
[3] Fransen AMM, van Ede F, Maris E.
Identifying neuronal oscillations using
rhythmicity. NeuroImage. 2015;118:
256-267
[4] Cabral Jr F, Pinna MH, Alves RD,
Malerbi AFDS, Bento RF. Cochlear
implantation and single-sided
deafness: A systematic review of the
literature. International Archives of
Otorhinolaryngology. 2014;20(1):69-75
[5] Hitti FL, Ramayya AG, Mcshane BJ,
Yang AI, Vaughan KA, Baltuch GH.
Long-term outcomes following deep
brain stimulation for Parkinson’s
disease. Journal of Neurosurgery.
2019;132(1):1-6
[6] Monge-Pereira E, Ibañez-Pereda J,
Alguacil-Diego IM, Serrano JI,
Spottorno-Rubio MP, Molina-Rueda F.
Use of electroencephalography braincomputer interface systems as a
rehabilitative approach for upper limb
function after a stroke: A systematic
review. PM & R: The Journal of
Injury, Function, and Rehabilitation.
2017;9(9):918-932
[7] Frolov AA, Mokienko O,
Lyukmanov R, Biryukova E,
Kotov S, Turbina L, et al. Post-stroke
rehabilitation training with a motorimagery-based brain-computer interface
(BCI)-controlled hand exoskeleton: A
randomized controlled multicenter trial.
Frontiers in Neuroscience. 2017;11(JUL)
[8] Burns MK, Pei D, Vinjamuri R.
Myoelectric control of a soft hand
exoskeleton using kinematic synergies.
IEEE Transactions on
Biomedical Circuits and Systems.
2019;13(6):1351-1361
[9] Velliste M, Perel S, Spalding MC,
Whitford AS, Schwartz AB.
Cortical control of a prosthetic
arm for self-feeding. Nature.
2008;453(7198):1098-1101
[10] Yanagisawa TT, Hirata M,
Saitoh Y, Kishima H, Matsushita K,
Goto T, et al. Electrocorticographic
control of a prosthetic arm in paralyzed
patients. Annals of Neurology.
2012;71(3):353-361
[11] Bright D, Nair A, Salvekar D,
Bhisikar S. EEG-based brain controlled
prosthetic arm. Conference on Advances
in Signal Processing (CASP) 2016. 2016.
pp. 479-483
[12] Pei D, Burns M, Chandramouli R,
Vinjamuri R. Decoding asynchronous
reaching in electroencephalography
using stacked autoencoders. IEEE
Access. 2018;6:52889-52898
[13] Pei D, Patel V, Burns M,
Chandramouli R, Vinjamuri R.
Neural decoding of synergybased hand movements using
electroencephalography. IEEE Access.
2019;7:18155-18163
[14] Patel V, Burns M, Pei D,
Vinjamuri R. Decoding synergy-based
hand movements using
electroencephalography. In: 40th
Annual International Conference of
the IEEE Engineering in Medicine and
Biology Society (EMBC). 2018. pp.
4816-4819
[15] Elger CE, Hoppe C. Diagnostic
challenges in epilepsy: Seizure underreporting and seizure detection. Lancet
Neurology. 2018;17(3):279-288
[16] James CJ, Jones RD, Bones PJ,
Carroll GJ. Detection of epileptiform
References