Low-energy formulations of support vector machine kernel functions for biomedical sensor applications
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SVM, Markov models, and Wavelet analysis are used in health monitoring systems for anomaly detection.
“For example, support vector machines [27], Markov models [28] and Wavelet analysis [29] are used in health monitoring systems for anomaly detection.”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [27]
An SVM method was developed for detecting arrhythmia and seizure episodes in ECG signals.
“Similarly, [27] developed an SVM method for detecting the arrhythmia and seizure episodes while ECG signals.”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [27]
The SVM method with polynomial kernel leads to better results than other kernels for detecting arrhythmia and seizure episodes in ECG signals.
“This research showed that the SVM method with polynomial kernel leads to better result rather than other kernels.”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [27]
Another group of papers focused on small scale of subjects (maybe one or at most 10 persons) to investigate the accuracy and correctness of results in the proposed model.
“Due to the type of data mining tools, another group of papers focused on small scale of subjects (maybe one or at most 10 persons) in order to investigate the accuracy and correctness of results in proposed model [27,53].”
From Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges (2013) · cites this paper as [27]
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Banaee, H., Ahmed, M., & Loutfi, A. (2013) · Sensors · doi:10.3390/s131217472 · Cited by 452 · see citing works
- Authors
- Lee, K. H., Kung, S.-Y., & Verma, N.
- Affiliations
- Princeton University (US)
- Corresponding author
- Lee, Kyong Ho
- Venue
- Journal of Signal Processing Systems
- Published
- 2012-04-22
- Volume
- 69
- Issue
- 3
- Pages
- 339-349
- ISSN
- 1939-8018 (ISSN-L)
- 1939-8115
- OpenAlex
- W2023453288
- Cited by
- 35
- References
- 29
- Citations by year
- 2025: 1 · 2023: 1 · 2021: 4 · 2019: 4 · 2018: 5 · 2017: 6 · 2016: 3 · 2015: 6 · 2014: 1 · 2013: 4
- FWCI
- 2.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Signal Processing Systems (publishedVersion)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Physical Sciences › Computer Science › Artificial Intelligence › Machine Learning and ELM
- Physical Sciences › Engineering › Biomedical Engineering › Wireless Body Area Networks
- Keywords
- support vector machine, kernel functions, polynomial kernel, EEG seizure detection, ECG arrhythmia detection, real-time classification, energy efficiency
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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