Name
Abstract | ||
|---|---|---|
Continuous heart rate variability (HRV) monitoring in cars can allow ambient health monitoring and help track driver stress and fatigue. Current approaches that involve wearable or externally mounted sensors are accurate but inconvenient for the user. In particular, prior approaches often fail when noise from human motion or car noise are present.
In this paper, we present VVRRM, an ambient heartbeat monitoring system in an automobile which uses a set of accelerometers in a car seat to monitor a subject's heart RR-intervals. The system removes high energy motion noise and periodic noise using a combination of peak detection with extracted wavelet coefficients. Furthermore, it tracks human heart locations through sensor selection to maximize the heart signal energy. We tested the system with both a manufactured heartbeat signal and experiments with human subjects. Overall our mean absolute error for RR-interval estimation was 54 ms across all human subjects, and 3 ms with our manufactured heartbeat signal.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3177102.3177110 | HotMobile |
Keywords | Field | DocType |
vibration, heart rate variability (HRV), vehicular sensing, human condition monitoring | Car seat,Heartbeat,Accelerometer,Heart rate variability,Wearable computer,Computer science,Real-time computing,Energy (signal processing),Vibration,Wavelet | Conference |
ISBN | Citations | PageRank |
978-1-4503-5630-5 | 3 | 0.40 |
References | Authors | |
4 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amelie Bonde | 1 | 18 | 4.32 |
| Shijia Pan | 2 | 72 | 12.02 |
| Zhenhua Jia | 3 | 30 | 5.33 |
| Yanyong Zhang | 4 | 3116 | 184.08 |
| Hae Young Noh | 5 | 106 | 30.54 |
| Pei Zhang | 6 | 346 | 54.10 |