Dissertation > Excellent graduate degree dissertation topics show

Research on the Muscle Electrical Stimulation Instrument Based on the Method of Steady State Visual Evoked Potential

Author: WenQi
Tutor: WangXueMin
School: Tianjin University
Course: Biomedical Engineering
Keywords: Brain-Computer Interface(BCI) Steady State Visual Evoked Potential (SSVEP) electrical stimulation instrument functional recovery of locomotion
CLC: TH772.1
Type: Master's thesis
Year: 2006
Downloads: 206
Quote: 4
Read: Download Dissertation


The dyskinesia is one of the most common clinical symptom on hemiplegy patients. The degree of functional recovery of locomotion and the reactivation is the important criterion of healing.The Brain-Computer Interface(BCI) is the new outward info-interface and advanced control technique which is established between person’s brain and the computer or other electronic equipments. It doesn’t depend on the normal output thoroughfare of brain information but provide a kind of new method in recovering the patients who are damaged in nerve and muscle of limbs. Steady State Visual Evoked Potential(SSVEP) is an important methodology used in brain-computer interface. With high information transmission rate, short training time and non-damage, SSVEP has become a very promising BCI signal inputting application. Functional electrical stimulation can control injured atrophy and build up muscular strength. By using stimulation to let outer nerve transmit information to the centum, it can radically advance the repair of the damaged centum as well as renew the locomotive function in order to improve patients’life quality.A method is suggested in this paper by combine the theories of brain-computer interface technology and functional electrical stimulation. Based on the study of electrical stimulating therapy for the recovery from hemiplegy or other neuropathy, it put controlling signal caused by SSVEP into electrical stimulating equipment by EEG experiment. Through this way, it designed a system to cure hemiplegy by stimulating therapy and the system is controlled by brain electricity. This changed the traditional apparatus into an intellectualized system and realized brain and computer interface in some extent.This apparatus used AT89C58 singlechip and CPLD as the controlling centre to realize parameter setup, LCD display and multi-channel output control. The output stimulate pulse is bidirectional rectangle wave. The parameters of rectangle wave, such as outputting stimulating pulse frequency, width, clearance between pulses of different polarity, interval between bordered output stimulating pulses and therapy time, can be changed by using the keyboard. The circuit is designed in series with computer. Thus the brain electrical information can communicate with singlechip in order to control therapy. Using 40-channels brain electrics amplifier to collect the brain electrical information that people have when they are exposed to flashlight, extract steady state visual evoked potential and analyse power spectrum. The result display can provide the information that can be used by the computer and FES.The experiment was operated on the normal human. The stimulating point and the parameter of the simulation were recorded and the effect of the simulation was told by the subject. The results showed that the equipment was safe and the output can cause the shrinkage of the muscle, so the design achieved the expectant target. The experiment of the communication between the computer and the FES showed that this design had high accuracy and could be easily actualized. But because of the complexity of human body, the further experiment and clinical study are still needed.

Related Dissertations

  1. The Wireless Remote Controlled Car System Based on Real Time Brain-computer Interface,TP872
  2. The Research of Upper Limb Rehabilitation System Based on Bci,TH789
  3. The Design and Implementation of the EEG signal acquisition system for brain-computer interface,TP274.2
  4. Mental Tasks Classification of Hands Imaginery Movement,R319
  5. Study of Experiment and Classing Arithmetic on Brain-computer Interface,R318
  6. Activity of Neural Network in the Hippocampal CA1 Region Encoding Startling Fear Memory,Q42
  7. Recognition Classification and BCI Experiments for Mental EEG of Imaging Left-right Hands Movement,R318
  8. The Extraction of Spontaneous EEG Based on Time, Frequency and Spatial Information,R318
  9. Study on the SSVEP’s Application in Brain-Computer Interface and Cognitive Task,R318
  10. Research on Brain-Computer Interface by Independent Component Analysis,TP334.7
  11. Multi-mode Analysis of Eeg and Application in BCI,TP11
  12. Key Technology and Experiment Research on EEG-Based Brain-Computer Interface,TP334.7
  13. A Study on Brain Computer Interface Based on the Steady-State Visual Evoked Potential Phase,R318.0
  14. The Study on Local Field Potentials of Rats during Pressing Paddle,R318.04
  15. Research on Mental Task Classification for Brain Computer Interface Application,TP18
  16. Research of Brain-Computer Interface Based on Spontaneous EEG (Mu Rhythm),TP334.7
  17. Design of the Alpha-Based Brain-Computer Interface System,R318.0
  18. Brain-Computer Interface System Design and Experiment Research Based on Motor Imagery Potential,TP334.7
  19. EEG acquisition instrument design based on real-time embedded systems,TP274.2
  20. Studying on the Algorithms of Feature Extraction and Classification in Brain-Computer Interface,TP391.41

CLC: > Industrial Technology > Machinery and Instrument Industry > Instruments, meters > Medical and health devices > Medical electrical machinery > Electrotherapy mechanical
© 2012 www.DissertationTopic.Net  Mobile