Automated hand-forearm ergometer data acquisition and analysis system

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dc.contributor.author Gude, Dana Maxine
dc.date.accessioned 2013-08-16T17:11:42Z
dc.date.available 2013-08-16T17:11:42Z
dc.date.issued 2013-08-16
dc.identifier.uri http://hdl.handle.net/2097/16278
dc.description.abstract Handgrip contractions are a standard exercise modality to evaluate muscular system performance. Most conventional ergometer systems that collect handgrip contraction data are manually controlled, placing a burden on the researcher to guide subject activity while recording the resultant data. Further, post-processing tools for this type of experiment are not standardized within the domain, which requires investigators to process their data with multiple tool sets and often create custom tool sets for that purpose. This can make experimental data difficult to compare and correlate, even within the same research group. This thesis presents updates to a hand-forearm ergometer system that automate the control and data-acquisition processes as well as provide a tool set to post process hand contraction data. The automated system utilizes a LabVIEW virtual instrument as the system centerpiece; it provides the subject/researcher interfaces and coordinates data acquisition from both traditional and new sensors. The tool set also incorporates a collection of MATLAB scripts that allow the investigator to post process these data in a standard way, such as automating the processes of noise floor removal, burst start/stop time identification, and mean/median frequency calculation in electromyograms (EMGs). The tool set has proven to be a viable support resource for experimental studies performed by the Kansas State University Human Exercise Physiology lab that target muscle fatigue in human forearms. Initial data acquired during these tests indicate the viability of the system to acquire consistent and physiologically meaningful data while providing a usable tool set for follow-on data analyses. en_US
dc.description.sponsorship NASA Human Research Program en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Hand-forearm ergometer en_US
dc.subject Handgrip ergometer en_US
dc.subject Muscle fatigue en_US
dc.subject LabVIEW en_US
dc.subject Data acquisition en_US
dc.subject Automated data collection en_US
dc.title Automated hand-forearm ergometer data acquisition and analysis system en_US
dc.type Thesis en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Electrical & Computer Engineering en_US
dc.description.advisor Steve Warren en_US
dc.subject.umi Biomedical Engineering (0541) en_US
dc.subject.umi Electrical Engineering (0544) en_US
dc.subject.umi Kinesiology (0575) en_US
dc.date.published 2013 en_US
dc.date.graduationmonth August en_US


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