|Title:||Electrical Stimulation of the Spinal Cord to Decrease Pain||Language:||English||Authors:||Tafvizi, Pegah||Qualification level:||Diploma||Keywords:||pain; electrical stimulation; spinal cord||Advisor:||Rattay, Frank||Issue Date:||2020||Number of Pages:||95||Qualification level:||Diploma||Abstract:||
Pain is a global health issue that can prevent a human being from doing their essential daily tasks and is significant suffering for anybody who has it. Conventionally, drugs and medication have been used to decrease or relieve pain. However, with increased technological advancements in the medical field, electrical neural stimulation has been adopted, especially in first world countries. This emerging technology has been proven to be very helpful. One of the FDA approvals for electrical neural stimulation technology is the Electrical Stimulation of the Spinal Cord (SCS to reduce human pain. The mechanisms of SCS and other factors influencing SCS are explained in this thesis. The three waveforms which are currently used clinically for SCS are (i) conventional/tonic SCS (typically in the range of 20-120Hz), (ii) burst SCS (five consecutive 500Hz waves at 40Hz burst frequency), and (iii) high-frequency SCS (HF10 SCS is 10kHz frequency). Several studies have shown that high-frequency SCS and burst SCS do not cause paresthesia and are the most effective waveforms for pain SCS. In chapter 6, I used the Hodgkin Huxley for a single-compartment neuron model in MATLAB. I modeled the three SCS waveforms using MATLAB and checked the effects of these waveform stimulations separately in the single-compartment neuron model. For future study, one good idea is to check the impact of a new pattern of the waveform on a single neuron model or multi-compartment neuron model or check the effect using the voltage-clamp technique in a laboratory. Brain images could also be used in this recommendation for future study as well as to observe different waveform pattern effects and find the most pain relief waveform pattern for SCS.It is hoped that this thesis study would give a good overview of SCS and provide helpful hints to other fellow researchers as well as general medical healthcare personnel in various ways to improve the technology.
|DOI:||10.34726/hss.2020.81363||Library ID:||AC16066875||Organisation:||E101 - Institut für Analysis und Scientific Computing||Publication Type:||Thesis
|Appears in Collections:||Thesis|
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