Abstract
IoT wearable devices are widely expected to reduce the cost and risk of personal healthcare. However, ambulatory data collected from such devices are often corrupted or contaminated with severe noises. Signal Quality Indicators (SQIs) can be used to assess the quality of data obtained from wearable devices, such that transmission/ storage of unusable data can be prevented. This article introduces a novel and generalized SQI which can be implemented on an edge device for detecting the quality of any quasi-periodic signal under observation, regardless of the type of noise present. The application of this SQI on Electrocardiogram (ECG) signals is investigated. From the analysis carried out, it was found that the proposed generalized SQI is suitable for quality assessment of ECG signals and exhibits a linear behavior in the medium to high SNR regions under all noise conditions considered. The proposed SQI was used for acceptability testing of ECG records in CinC Physionet 2011 challenge dataset and found to be accurate for 90.4% of the records while having minimal computational complexity.
| Original language | English |
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| Title of host publication | 2020 IEEE International Symposium on Circuits and Systems (ISCAS) |
| DOIs | |
| Publication status | Published - 28 Sept 2020 |
| Externally published | Yes |
| Event | 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Virtual Conference, Virtual, Online, Spain Duration: 10 Oct 2020 → 21 Oct 2020 Conference number: 52 https://www.iscas2020.org/ |
Conference
| Conference | 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 |
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| Abbreviated title | ISCAS 2020 |
| Country/Territory | Spain |
| City | Virtual, Online |
| Period | 10/10/20 → 21/10/20 |
| Internet address |
Keywords
- n/a OA procedure