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|Title:||Bipedal locomotion modeled as the central pattern generator (CPG) and regulated by self organizing map for model of cortex||Authors:||Mishra, A.
|Issue Date:||2013||Citation:||Mishra, A.,Sunan, H.,Yu, H.,Thakor, N.V. (2013). Bipedal locomotion modeled as the central pattern generator (CPG) and regulated by self organizing map for model of cortex. IEEE EMBS Special Topic Conference on Point-of-Care (POC) Healthcare Technologies: Synergy Towards Better Global Healthcare, PHT 2013 : 50-53. ScholarBank@NUS Repository. https://doi.org/10.1109/PHT.2013.6461282||Abstract:||This paper describes a biologically inspired algorithm mimicking locomotion, and associated brain inspired software architecture to model bipedal gait. The central pattern generator (CPG) neural network is first modeled and next, self-organizing maps of gait for running and walking are created. This biological or brain inspired neural network model is finally assimilated to account for cortical control or modulation of gait. This work demonstrates the utility of using the CPG neural networks and self-organizing maps as the controller to mimic normal and abnormal gait patterns. The work presented here is our first step towards developing a biologically inspired neuroprosthetic device to help stroke patients regain normal gait at a faster pace. © 2013 IEEE.||Source Title:||IEEE EMBS Special Topic Conference on Point-of-Care (POC) Healthcare Technologies: Synergy Towards Better Global Healthcare, PHT 2013||URI:||http://scholarbank.nus.edu.sg/handle/10635/69509||ISBN:||9781467327664||DOI:||10.1109/PHT.2013.6461282|
|Appears in Collections:||Staff Publications|
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