User:Dimitri Yatsenko
I am a new member of OpenWetWare!
Contact Info
Dimitri Yatsenko Baylor College of Medicine Dept. of Neuroscience, S553 One Baylor Plaza Houston, TX 77030
Education
- 2012 (in progress), PhD, Neuroscience, Baylor College of Medicine
- 2005, MS, Computational Engineering and Science, University of Utah
- 2003, MS, Computer Science, Utah State University
- 1999, BS, Computer Science, Utah State University
Research interests
- Two-photon microscopy
- In-vivo microscopy
- Laser-scanning microscopy
- Cortical organization
- Cortical intrinsic activity
- Cortical microcolumns
- Neural computation
- Neural code
Publications
- Baker JJ, Yatsenko D, Schorsch JF, DeMichele GA, Troyk PR, Hutchinson DT, Weir RF, Clark G, and Greger B. Decoding individuated finger flexions with Implantable MyoElectric Sensors. Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:193-6. DOI:10.1109/IEMBS.2008.4649123 |
We trained a rhesus monkey to perform randomly cued, individuated finger flexions of the thumb, index, and middle finger. Nine Implantable MyoElectric Sensors (IMES) were then surgically implanted into the finger muscles of the monkey's forearm, without any observable adverse chronic effects. Using an inductive link, we wirelessly recorded EMG from the IMES as the monkey performed a finger flexion task. A principal components analysis (PCA) based algorithm was used to decode which finger switch was pressed based on the recorded EMG. This algorithm correctly decoded which finger was moved 89% of the time. These results demonstrate that IMES offer a safe and highly promising approach for providing intuitive, dexterous control of artificial limbs and hands after amputation.
- Yatsenko D, McDonnall D, and Guillory KS. Simultaneous, proportional, multi-axis prosthesis control using multichannel surface EMG. Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:6134-7. DOI:10.1109/IEMBS.2007.4353749 |
Most upper limb prosthesis controllers only allow the individual selection and control of single joints of the limb. The main limiting factor for simultaneous multi-joint control is usually the availability of reliable independent control signals that can intuitively be used. In this paper, a novel method is presented for extraction of individual muscle source signals from surface EMG array recordings, based on EMG energy orthonormalization along principle movement vectors. In cases where independently-controllable muscles are present in residual limbs, this method can be used to provide simultaneous, multi-axis, proportional control of prosthetic systems. Initial results are presented for simultaneous control of wrist rotation, wrist flexion/extension, and grip open/close for two intact subjects under both isometric and non-isometric conditions and for one subject with transradial amputation.
-
Yatsenko DV, Anderton RL, Sikorski K, Kirby RM, Regional exposure management with spatial x-ray gating, Proc. SPIE, Vol. 6142, 614218 (2006); DOI:10.1117/12.654066
Regional x-ray exposure management is a class of techniques for x-ray dose reduction and image quality improvement in radiography and fluoroscopy. X-ray intensity is modulated spatially prior to the beam's interaction with the imaged objects for optimal dose efficiency. The optimal intensity field may be determined from the imaged objects' morphology, local dose sensitivities, regions of clinical interest, and expected information. We present the derivation and simulation results for a method for automated feedback-controlled real-time spatial modulation of the x-ray intensity field. The method employs spatial x-ray gating, a technique in which various beam regions are blocked for controlled portions of the frame integration period while the beam intensity is modulated in time. The method promises to provide controllable smooth x-ray intensity fields with precise and sensitive controls operating, if desired, automatically in a feedback loop.
