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Automating stroke patient evaluation using sensor data and SVM

Title
Automating stroke patient evaluation using sensor data and SVM
Authors
Otten, PaulSon, Sang HyukKim, Jonghyun
DGIST Authors
Otten, Paul; Son, Sang Hyuk; Kim, Jonghyun
Issue Date
2014
Citation
7th IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2014, 223-229
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
Abstract
Evaluation of post-stroke hemiplegic patients is an important aspect of rehabilitation, especially for assessing improvement of a patient's condition from a treatment. It is also commonly used to evaluate stroke patients during theraputic clinical trials [1]. The Fugl-Meyer Assessment is one of the most widely recognized and utilized measures of body function impairment for post-stroke patients [2]. We propose a method for automating the upper-limb portion of the Fugl-Meyer Assessment by gathering data from sensors monitoring the patient. Features are extracted from the data and processed by a Support Vector Machine (SVM). The output from the SVM returns a value that can be used to score a patient's upper limb functionality. This system will enable automatic and inexpensive stroke patient evaluation that can save up to 30 minutes per patient for a doctor, providing a huge time-saving service for doctors and stroke researchers. © 2014 IEEE.
URI
http://hdl.handle.net/20.500.11750/3754
DOI
10.1109/SOCA.2014.29
Publisher
Institute of Electrical and Electronics Engineers Inc.
Related Researcher
  • Author Son, Sang Hyuk RTCPS(Real-Time Cyber-Physical Systems Research) Lab
  • Research Interests
Files:
There are no files associated with this item.
Collection:
ETC2. Conference Papers
Information and Communication EngineeringAdvanced Electronic Devices Research Group(AEDRG)2. Conference Papers


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