Redundancy cancellation of compressed measurements by QRS complex alignment.
The demand for long-term continuous care has led healthcare experts to focus on development challenges. On-chip energy consumption as a key challenge can be addressed by data reduction techniques. In this paper, the pseudo periodic nature of ElectroCardioGram(ECG) signals has been used to completely...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0262219 |
| _version_ | 1819118896197664768 |
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| author | Fahimeh Nasimi Mohammad Reza Khayyambashi Naser Movahhedinia |
| author_facet | Fahimeh Nasimi Mohammad Reza Khayyambashi Naser Movahhedinia |
| author_sort | Fahimeh Nasimi |
| collection | DOAJ |
| description | The demand for long-term continuous care has led healthcare experts to focus on development challenges. On-chip energy consumption as a key challenge can be addressed by data reduction techniques. In this paper, the pseudo periodic nature of ElectroCardioGram(ECG) signals has been used to completely remove redundancy from frames. Compressing aligned QRS complexes by Compressed Sensing (CS), result in highly redundant measurement vectors. By removing this redundancy, a high cluster of near zero samples is gained. The efficiency of the proposed algorithm is assessed using the standard MIT-BIH database. The results indicate that by aligning ECG frames, the proposed technique can achieve superior reconstruction quality compared to state-of-the-art techniques for all compression ratios. This study proves that by aligning ECG frames with a 0.05% unaligned frame rate(R-peak detection error), more compression could be gained for PRD > 5% when 5-bit non-uniform quantizer is used. Furthermore, analysis done on power consumption of the proposed technique, indicates that a very good recovery performance can be gained by only consuming 4.9μW more energy per frame compared to traditional CS. |
| first_indexed | 2024-12-22T05:56:09Z |
| format | Article |
| id | doaj.art-07f72971065248af983b4d4cb998315b |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-22T05:56:09Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-07f72971065248af983b4d4cb998315b2022-12-21T18:36:42ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01172e026221910.1371/journal.pone.0262219Redundancy cancellation of compressed measurements by QRS complex alignment.Fahimeh NasimiMohammad Reza KhayyambashiNaser MovahhediniaThe demand for long-term continuous care has led healthcare experts to focus on development challenges. On-chip energy consumption as a key challenge can be addressed by data reduction techniques. In this paper, the pseudo periodic nature of ElectroCardioGram(ECG) signals has been used to completely remove redundancy from frames. Compressing aligned QRS complexes by Compressed Sensing (CS), result in highly redundant measurement vectors. By removing this redundancy, a high cluster of near zero samples is gained. The efficiency of the proposed algorithm is assessed using the standard MIT-BIH database. The results indicate that by aligning ECG frames, the proposed technique can achieve superior reconstruction quality compared to state-of-the-art techniques for all compression ratios. This study proves that by aligning ECG frames with a 0.05% unaligned frame rate(R-peak detection error), more compression could be gained for PRD > 5% when 5-bit non-uniform quantizer is used. Furthermore, analysis done on power consumption of the proposed technique, indicates that a very good recovery performance can be gained by only consuming 4.9μW more energy per frame compared to traditional CS.https://doi.org/10.1371/journal.pone.0262219 |
| spellingShingle | Fahimeh Nasimi Mohammad Reza Khayyambashi Naser Movahhedinia Redundancy cancellation of compressed measurements by QRS complex alignment. PLoS ONE |
| title | Redundancy cancellation of compressed measurements by QRS complex alignment. |
| title_full | Redundancy cancellation of compressed measurements by QRS complex alignment. |
| title_fullStr | Redundancy cancellation of compressed measurements by QRS complex alignment. |
| title_full_unstemmed | Redundancy cancellation of compressed measurements by QRS complex alignment. |
| title_short | Redundancy cancellation of compressed measurements by QRS complex alignment. |
| title_sort | redundancy cancellation of compressed measurements by qrs complex alignment |
| url | https://doi.org/10.1371/journal.pone.0262219 |
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