Name
Abstract | ||
|---|---|---|
Although most of the medical and healthcare monitoring systems generate multi-dimensional time series (via multiple sensors), most of the work by research community has been focused on defining distance metrics and matching algorithms to improve accuracy and optimize performance of search in single dimensional time series. In this work we motivate the need for multidimensional time series matching and propose a scalable technique that has high accuracy in presence of noise, uncertainty, and lack of synchronization between dimensions. We focus on two medical monitoring devices and their applications to showcase the advantages, performance, and accuracy of our multi-dimensional time series search technique. We demonstrate effectiveness of our signal search technique by using precision and recall metrics. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/BSN.2013.6575494 | BSN |
Keywords | DocType | ISSN |
time series analysis,accuracy,decision support systems,sensors,pattern matching,noise | Conference | 2325-1425 |
ISBN | Citations | PageRank |
978-1-4799-0331-3 | 3 | 0.40 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Moazeni | 1 | 40 | 3.81 |
| Bobak Mortazavi | 2 | 45 | 8.38 |
| Majid Sarrafzadeh | 3 | 3103 | 317.63 |