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Mendeley readers
Attention Score in Context
| Title |
Stream Computing for Biomedical Signal Processing: A QRS Complex Detection Case-Study
|
|---|---|
| Published in |
Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, January 2015
|
| DOI | 10.1109/embc.2015.7319741 |
| Pubmed ID | |
| Authors |
B. M. Murphy, C. O'Driscoll, G. B. Boylan, G. Lightbody, W. P. Marnane |
| Abstract |
Recent developments in "Big Data" have brought significant gains in the ability to process large amounts of data on commodity server hardware. Stream computing is a relatively new paradigm in this area, addressing the need to process data in real time with very low latency. While this approach has been developed for dealing with large scale data from the world of business, security and finance, there is a natural overlap with clinical needs for physiological signal processing. In this work we present a case study of streams processing applied to a typical physiological signal processing problem: QRS detection from ECG data. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Hong Kong | 1 | 8% |
| Unknown | 11 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 17% |
| Student > Ph. D. Student | 2 | 17% |
| Lecturer | 1 | 8% |
| Professor | 1 | 8% |
| Student > Doctoral Student | 1 | 8% |
| Other | 2 | 17% |
| Unknown | 3 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 42% |
| Biochemistry, Genetics and Molecular Biology | 1 | 8% |
| Medicine and Dentistry | 1 | 8% |
| Computer Science | 1 | 8% |
| Unknown | 4 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 January 2016.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#2,857
of 4,376 outputs
Outputs of similar age
#266,662
of 359,549 outputs
Outputs of similar age from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#134
of 234 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,376 research outputs from this source. They receive a mean Attention Score of 2.7. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 234 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.