High performance biomedical time series indexes using salient segmentation Conference Paper

abstract

• The advent of remote and wearable medical sensing has created a dire need for efficient medical time series databases. Wearable medical sensing devices provide continuous patient monitoring by various types of sensors and have the potential to create massive amounts of data. Therefore, time series databases must utilize highly optimized indexes in order to efficiently search and analyze stored data. This paper presents a highly efficient technique for indexing medical time series signals using Locality Sensitive Hashing (LSH). Unlike previous work, only salient (or interesting) segments are inserted into the index. This technique reduces search times by up to 95% while yielding near identical search results. 2012 IEEE.

authors

• Mortazavi, Bobak

published proceedings

• Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

author list (cited authors)

• Woodbridge, J., Mortazavi, B., Bui, A., & Sarrafzadeh, M.

citation count

• 3

complete list of authors

• Woodbridge, J||Mortazavi, B||Bui, AAT||Sarrafzadeh, M

publication date

• December 2012

published in

• Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference  Journal

Digital Object Identifier (DOI)

• 10.1109/EMBC.2012.6347137

International Standard Book Number (ISBN) 13

• 9781424441198

start page

• 5086

end page

• 5089