©The Author(s) 2022.
World J Clin Cases. Sep 16, 2022; 10(26): 9207-9218
Published online Sep 16, 2022. doi: 10.12998/wjcc.v10.i26.9207
Published online Sep 16, 2022. doi: 10.12998/wjcc.v10.i26.9207
Table 1 The most important features of electrocardiogram signals in the UCI dataset
| Features | Values |
| Age | Yr |
| Sex | Male = 0, female = 1 |
| Height | cm |
| Weight | Kg |
| QRS length | Average QRS length in milliseconds |
| Distance P-R | Average time interval between the start of waves P and Q in milliseconds |
| Distance Q-T | Average time interval between start of wave Q and end of wave T in milliseconds |
| Distance T | Average time interval of wave T in milliseconds |
| Distance P | Average P wave distance in milliseconds |
| QRS | Degree vector angles on the screen |
| T | Degree vector angles on the screen |
| P | Degree vector angles on the screen |
| QRST | Degree vector angles on the screen |
| J | Degree vector angles on the screen |
| Heart rate | Heart rate per minute |
- Citation: Dami S. Internet of things-based health monitoring system for early detection of cardiovascular events during COVID-19 pandemic. World J Clin Cases 2022; 10(26): 9207-9218
- URL: https://www.wjgnet.com/2307-8960/full/v10/i26/9207.htm
- DOI: https://dx.doi.org/10.12998/wjcc.v10.i26.9207