Name
Abstract | ||
|---|---|---|
Enabled by recent sensing and wireless chips, small wireless sensors can now be attached to various wearable devices such as finger rings and wrist bands. In this paper, we describe a compressive sensing based approach to such wireless devices that exploits sparsity of signal to reduce power consumption for both sensing and transmission. Using subsampling methods, we can lower sensor wake-up frequency and data transmission rate. We use a trained dictionary to recover the signal from the subsampled measurements. The same dictionary can also help recover from possible outliers in sensor measurements. In addition, to protect against burst packet loss over wireless channels, we rearrange packets and randomize their send orders. In order to demonstrate these concepts, we have built a prototype wearable system and report performance results from this experimental system. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CTS.2015.7210388 | 2015 International Conference on Collaboration Technologies and Systems (CTS) |
Keywords | Field | DocType |
Compressive sensing,Sparse coding,Pulse sensing,Internet of things,Subsampling,Wireless wearable | Key distribution in wireless sensor networks,Wireless,Data transmission,Wearable computer,Computer science,Network packet,Packet loss,Wi-Fi array,Computer hardware,Compressed sensing,Embedded system,Distributed computing | Conference |
ISBN | Citations | PageRank |
978-1-4673-7647-1 | 1 | 0.36 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hsieh-Chung Chen | 1 | 36 | 4.85 |
| Harnek Gulati | 2 | 1 | 0.36 |
| H. T. Kung | 3 | 368 | 68.24 |
| Surat Teerapittayanon | 4 | 67 | 5.63 |