Title :
Compression-ratio-based seizure detection
Author :
Chung-Lin Sha ; Taehoon Kim ; Artan, N.S. ; Chao, H. Jonathan
Author_Institution :
Dept. of Electr. & Comput. Eng., New York Univ., Brooklyn, OH, USA
Abstract :
For wireless seizure monitoring devices seizure detection and data compression are two critical tasks that need to be carefully designed against a very tight power budget to maximize the battery life. These two tasks are usually considered separately and algorithms for each are developed separately. In this paper, we consider having a single low-power algorithm for implementing both seizure detection and data compression. Towards that end, we investigated compression ratio (CR) as a seizure marker and show that the seizure detection can be achieved as a by-product of compression with no additional cost, and thus overall system power can be reduced. We show that the proposed method, the CR-based seizure detection has promising performance with 88% seizure detection accuracy, and 5.5 false positives per hour (FPh) without any computation overhead.
Keywords :
data compression; electroencephalography; medical disorders; medical signal detection; patient monitoring; wireless sensor networks; CR-based seizure detection; battery life; compression by-product; compression ratio; compression-ratio-based seizure detection; data compression; seizure detection accuracy; seizure marker; single low-power algorithm; wireless seizure monitoring device; Conferences; Data compression; Electroencephalography; Encoding; Monitoring; Power demand; Wireless communication; Algorithms; Data Compression; Electroencephalography; Humans; Seizures;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6609674