PalmGrid, an artificial intelligence approach to automate cylinder task detection
department or school: Medicine, Faculty of
data provider: DSpace
degree campus: UBCV
creator: Cheng, Sze-Ming David
issued: 2019-04-25T23:26:18Z
issued: 2019
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Stroke is a common cause of permanent disability accompanied by devastating impairments. Motor, sensory and cognitive deficits are common following stroke, yet treatment is limited. Along with histological measures, functional outcome in animal models has provided valuable insight to the biological basis and potential rehabilitation efforts of experimental stroke. Developing and using tests that identify behavioral deficits is essential to expanding the development of translational therapies. Forelimb Asymmetry Task experiments – often called Cylinder Tests – are used to study the impact of ischemic stroke and its subsequent rehabilitation to contralateral limb movements of studying rodents. Through assessments on qualitative and quantitative aspects of vertical exploration to the Cylinder Wall, extent of locomotor asymmetry is evaluated [25-27]. Traditionally wall rearing assessments are evaluated through manual, stop-watch based measurements that require laborious observations. Methods that automate the process were attempted such as the use of hardware-based sensor detections that passively probes of touches on the sensor grid. In its various implementations, the sensor-based methods fail to specify the limb that rears the wall nor depict the ways forelimbs are coordinated during the rearing. Advent of artificial intelligence (AI) algorithms, notably Deep Neural Networks (DNN), helps to extract posture and coordinates of forelimbs [21]. PalmGrid is the first attempt to exploit AI posture extraction algorithms – based on 50 layers depth in ResNet Deep Neural Networks [29] together with posture extraction algorithm DeepLabCut [24] – to automate the assessment process with 70% detection accuracy using robust, open-source software. Further improvements in deep neural networks precisions, such as increasing its depth or incorporating advanced posture extraction algorithms, will further enhance detection precisions. In this way, we will have viable alternatives to cond…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/69959
note: PalmGrid, an artificial intelligence approach to automate cylinder task detection by David Sze-Ming Cheng CEng MHKIE PMP MEng, University of Birmingham, UK (2001) MBA, University of Warwick, UK (1990) A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Neuroscience) The University of British Columbia (Vancouver) April 2019 ©David Sze-Ming Cheng, 2019 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: PalmGrid, an artificial intelligence approach to automate cylinder task detection submitted by Cheng, Sze-Ming David in partial fulfillment of the requirements for the degree of Master of Science in Neuroscience Examining Committee: Tim Murphy, Department of Neuroscience Supervisor Nicholas Swindale, Department of Neurosceince Supervisory Committee Member Lawrence Ward, Department of Neuroscience Supervisory Committee Member Tim O’Connor, Department of Neuroscience External Examiner iii Abstract Stroke is a common cause of permanent disability accompanied by devastating impairments. Motor, sensory and cognitive deficits are common following stroke, yet treatment is limited. Along with histological measures, functional outcome in animal models has provided valuable insight to the biological basis and potential rehabilitation efforts of experimental stroke. Developing and using tests that identify behavioral deficits is essential to expanding the development of translational therapies. Forelimb Asymmetry Task experiments – often called Cylinder Tests – are used to study the impact of ischemic stroke and its subsequent rehabilitation to contralateral limb movements of studying rodents. Through assessments on qualitative and quantitative aspects of vertical exploration to the Cylinder Wall, extent of locomotor asymmetry is evaluated [25-27]. Traditionally wall rearing …
has type: Thesis/Dissertation
date issued: 2019-05
is shown at: 10.14288/1.0378469
language: eng
degree discipline: Neuroscience
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
type: Text
identifier URI: http://hdl.handle.net/2429/69959