Study in Novel Peripheral Nerve Interface and Application
| dc.contributor.author | Samra, Amrtpal | |
| dc.date.accessioned | 2020-05-14T15:31:45Z | |
| dc.date.available | 2020-05-14T15:31:45Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Bi-directional exchange of information between the peripheral nervous system (PNS) and a computer interface can be achieved through the use of a peripheral nerve interface (PNI). Sophisticated PNI’s can be used to augment a PNS compromised by injury or disease. In addition to supplementing the PNS, PNI’s enable researchers to study the form and function of the PNS. Deploying effective PNI’s come with a set of challenges not unlike other neural engineering solutions; namely: low signal-to-noise ratio (SNR) from sensitivity limitations current equipment provide, functional resolution deficiencies and managing inadvertent stimulation as the whole field is still in its infancy, and the stability of the interface itself that tends to degrade over time from the body’s inherent nature of attacking foreign objects. There are many prominent figures in the field that are currently developing novel approaches and technologies to interface with the PNS. For example, imagine a system that can track internal biological markers that classify a disease state and automatically stimulate a peripheral nerve to provide non-pharmacological treatment of the medical condition; bringing the body and mind back to a ‘normal’ state, [6]. Imagine applying imaging techniques used in a different field of study in a novel way to increase the received SNR on electrodes, and consequentially the precision and accuracy of stimulation. Or, the ability to re-learn an ‘every-day’ function that has been affected by an injury or disease; for example, learning how to walk again after having a stroke that severs those neural pathways. Of course there is no one-size-fits-all solution and there are many trade-offs between resolution, form, and longevity that vary greatly across applications. However, a successful implementation of a PNI should allow information to be both introduced to, and extracted from the PNS. In this paper, we will briefly introduce select techniques and their applications; and then explore how using the principles of engineering, one might use some easy-to-gather data to quickly derive a meaningful way to control the gait of a Parkinson’s Disease (PD) patient. | |
| dc.identifier.uri | https://hdl.handle.net/1920/11777 | |
| dc.language.iso | en_US | |
| dc.rights | Attribution-ShareAlike 3.0 United States | |
| dc.rights.uri | https://creativecommons.org/licenses/by-sa/3.0/us/ | |
| dc.subject | Nerve cuff | |
| dc.title | Study in Novel Peripheral Nerve Interface and Application | |
| dc.type | Other |