Many assistive devices are available to help severely paralyzed individuals interact with the world (e.g. wheelchair-mountable robotic arms, neuroprosthetic systems that restore movement to one’s own arm, assistive computer software, etc.).

Severely paralyzed individuals have limited options for telling their assistive devices what movement or actions to make. One of my research areas focuses on developing the technology to allow paralyzed individuals to use their natural thoughts of movement to control their assistive devices.

After paralysis, one’s intended movements can be decoded in real time from recorded brain signals and then used to control various devices, such as an upper limb neuroprosthesis for restoring arm and hand function. In this case, extracting movement commands from the brain would allow paralyzed individuals to move their limbs the same way everyone else does – just by thinking of doing so.

I am investigating ways to extract one’s intended arm and hand movements from brain recordings collected from tiny microelectrode arrays inserted a few millimeters into the cortex. While others and I have been able to decode intended arm position or velocity for decades now, we are looking into decoding additional useful aspects of limb function such as limb stiffness and muscle force to further improve the stability and usefulness of these brain-controlled neuroprosthetic systems.

Additionally, my lab is complementing this research on restoring motor function with additional studies on how to return proprioception—specifically the sense of muscle force—back to the brain. Here we are using stimulation in the sensory cortex to generate perceptions of limb movement and muscle activity.

Reliably recording the tiny electrical signals of the brain is a challenge because of noise artifacts from many sources. My lab is also working on optimizing noise removal algorithms which will make all brain-controlled devices work better.

My lab is also using EEGs on the scalp surface to assess brain function and improve treatments for other diseases such as Parkinson’s disease and stroke. To that end we are working to develop better non-invasive electrodes that are more reliable for people with a range of different hair types.

Research Programs

  • Restoring arm function after paralysis using brain-controlled functional electrical stimulation
  • Restoring proprioception after paralysis via intracortical microstimulation
  • Improving intracortical recording technology through better signal processing methods
  • Using EEGs to understand and refine novel treatments for Parkinson’s disease and stroke
  • Developing more reliable EEG electrodes and recording systems

Publications (Select)

Entire publication list can be found here.

  • Bedell HW, Hermann JK, Ravikumar M, Lin S, Rein A, Li X, Molinich E, Smith PD, Selkirk SM, Miller RH, Sidik S, Taylor DM, Capadona JR. Targeting CD14 on blood derived cells improves intracortical microelectrode performance. Biomaterials. 2018 May;163:163-173. doi: 10.1016/j.biomaterials.2018.02.014. Epub 2018 Feb 13. PubMed PMID: 29471127; PubMed Central PMCID: PMC5841759.
  • Hermann JK, Ravikumar M, Shoffstall AJ, Ereifej ES, Kovach KM, Chang J, Soffer A, Wong C, Srivastava V, Smith P, Protasiewicz G, Jiang J, Selkirk SM, Miller RH, Sidik S, Ziats NP, Taylor DM, Capadona JR. Inhibition of the cluster of differentiation 14 innate immunity pathway with IAXO-101 improves chronic microelectrode performance. J Neural Eng. 2018 Apr;15(2):025002. doi: 10.1088/1741-2552/aaa03e. PubMed PMID: 29219114; PubMed Central PMCID: PMC5818286.
  • Jiang J, Marathe AR, Keene JC, Taylor DMA testbed for optimizing electrodes embedded in the skull or in artificial skull replacement pieces used after injury. J Neurosci Methods. 2017 Feb 1;277:21-29. doi: 10.1016/j.jneumeth.2016.12.005. Epub 2016 Dec 12. PubMed PMID: 27979758; PubMed Central PMCID: PMC5253247.
  • Jiang J, Willett FR, Taylor DM. Relationship between microelectrode array impedance and chronic recording quality of single units and local field potentials. Conf Proc IEEE Eng Med Biol Soc. 2014;2014:3045–3048. doi: 10.1109/EMBC.2014.6944265 Pubmed PMID: 25570633
  • Vadera S, Marathe AR, Gonzalez-Martinez J, Taylor DMStereoelectroencephalography for continuous two-dimensional cursor control in a brain-machine interface. Neurosurg Focus. 2013 Jun;34(6):E3. doi: 10.3171/2013.3.FOCUS1373 Pubmed PMID: 23724837
  • Foldes ST, Taylor DMSpeaking and cognitive distractions during EEG-based brain control of a virtual neuroprosthesis-arm. J Neuroeng Rehabil. 2013;10:116. doi: 10.1186/1743-0003-10-116Pubmed PMID: 24359452
  • Shoffstall AJ, Taylor DM, Lavik EB. Engineering therapies in the CNS: what works and what can be translated. Neurosci Lett. 2012 Jun 25;519(2):147–154. doi: 10.1016/j.neulet.2012.01.058Pubmed PMID: 22330751
  • Chadwick EK, Blana D, Simeral JD, Lambrecht J, Kim SP, Cornwell AS, Taylor DM, Hochberg LR, Donoghue JP, Kirsch RF. Continuous neuronal ensemble control of simulated arm reaching by a human with tetraplegia. J Neural Eng. 2011 Jun;8(3):034003. doi: 10.1088/1741-2560/8/3/034003Pubmed PMID: 21543840
  • Muralidharan A, Chae J, Taylor DMExtracting Attempted Hand Movements from EEGs in People with Complete Hand Paralysis Following Stroke. Front Neurosci. 2011;5:39. doi: 10.3389/fnins.2011.00039 Pubmed PMID: 21472032

PROFESSIONAL AFFILIATIONS

Investigator
Cleveland FES Center

Associate Staff Dept of Neuroscience
Cleveland Clinic

Research Scientist
Louis Stokes Cleveland VA Medical Center

Associate Professor Dept. of Biomedical Engineering
Case Western Reserve University

CONTACT INFORMATION

Program Contact
Dawn Taylor

Contact Number
(216) 636-0140

Contact Email
taylord8@ccf.org