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Reflex sensors for telemedicine applications

Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2008.

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Main Author: Busch, Alexander Carlo
Other Authors: Scheffer, C.
Format: Thesis
Language:English
Published: Stellenbosch : University of Stellenbosch 2008
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access_status_str Open Access
author Busch, Alexander Carlo
author2 Scheffer, C.
author_browse Busch, Alexander Carlo
Scheffer, C.
author_facet Scheffer, C.
Busch, Alexander Carlo
author_sort Busch, Alexander Carlo
collection Thesis
dc_rights_str_mv University of Stellenbosch
description Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2008.
format Thesis
id oai:scholar.sun.ac.za:10019.1/2507
institution Stellenbosch University (South Africa)
language English
last_indexed 2026-06-10T12:44:27.789Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2008
publishDateRange 2008
publishDateSort 2008
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/2507 Reflex sensors for telemedicine applications Busch, Alexander Carlo Scheffer, C. Basson, A. H. University of Stellenbosch. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering. Reflex Telemedicine Neural network Dissertations -- Mechanical engineering Theses -- Mechanical engineering Tendon reflex -- Testing Biomechanics Mechanical and Mechatronic Engineering Thesis (MScEng (Mechanical and Mechatronic Engineering))--University of Stellenbosch, 2008. A solution is sought for the measurement of human deep tendon reflexes as part of a comprehensive patient condition monitoring system for use in a telemedicine context. This study focused on the development, testing and performance evaluation of a prototype compact patellar tendon reflex measurement system that is able to provide a quantitative reflex evaluation for use by medical practitioners and in a telemedicine environment. A prototype system was developed that makes use of Xsens MTx orientation sensors, force-sensing resistors and an electromyogram (EMG) to measure the reflex response. Suitable parameters identified for analysis included the change in pitch, angular velocity and acceleration of the lower leg, the EMG response, the tendon impact, and various latencies associated with these measurements. Other information considered included the age, mass, and physical dimensions of the test subject. Clinical testing was performed to collect data to evaluate the system performance. Subjective reflex evaluations were conducted by three doctors according to a standard reflex grading scale using video recordings of the tests. Self-organizing maps and multi-layer feed-forward (MLFF) artificial neural networks (ANNs) were used to analyze the collected data with the aim of pattern identification, data classification and reflex grading prediction. It was found that the MLFF network delivered the correct reflex grading with an accuracy of 85%, which was of the same order as the rate of differences between the subjective reflex evaluations performed by the doctors (80%). Furthermore, analysis of the data suggested that certain parameters were not necessary for the autonomous evaluation, such as EMG data and the tendon impact. The use of ANNs to analyze a reflex measurement as proposed by this study offers an accurate, repeatable and concise representation of the reflex that is familiar to doctors and suitable for use in a general clinical setting or for telemedicine purposes. 2008-06-11T13:45:33Z 2010-06-01T08:50:46Z 2008-06-11T13:45:33Z 2010-06-01T08:50:46Z 2008-03 Thesis http://hdl.handle.net/10019.1/2507 en University of Stellenbosch application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Reflex
Telemedicine
Neural network
Dissertations -- Mechanical engineering
Theses -- Mechanical engineering
Tendon reflex -- Testing
Biomechanics
Mechanical and Mechatronic Engineering
Busch, Alexander Carlo
Reflex sensors for telemedicine applications
title Reflex sensors for telemedicine applications
title_full Reflex sensors for telemedicine applications
title_fullStr Reflex sensors for telemedicine applications
title_full_unstemmed Reflex sensors for telemedicine applications
title_short Reflex sensors for telemedicine applications
title_sort reflex sensors for telemedicine applications
topic Reflex
Telemedicine
Neural network
Dissertations -- Mechanical engineering
Theses -- Mechanical engineering
Tendon reflex -- Testing
Biomechanics
Mechanical and Mechatronic Engineering
url http://hdl.handle.net/10019.1/2507
work_keys_str_mv AT buschalexandercarlo reflexsensorsfortelemedicineapplications