Name
Abstract | ||
|---|---|---|
In this paper, we describe the results of a controlled experiment measuring everyday movement activity through a novel recognition prototype named AIR. AIR measures distance from the feet using infrared (IR) sensors. We tested this approach for recognizing six prevalent activities: standing stationary, walking, running, walking in place, going upstairs, and going downstairs and compared results to other commonly used approaches. Our results show that AIR obtains much higher accuracy in recognizing activity than approaches that rely primarily on accelerometers. Moreover, AIR has good generalization ability when applying recognition model to new users. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2968219.2971447 | UbiComp Adjunct |
Keywords | Field | DocType |
Activity Recognition, Infrared Sensor, Wearable System | Activity recognition,Accelerometer,Computer science,Human–computer interaction,Controlled experiment,Walking in place | Conference |
Citations | PageRank | References |
2 | 0.37 | 9 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinlong Jiang | 1 | 76 | 10.70 |
| Yiqiang Chen | 2 | 1446 | 109.32 |
| Junfa Liu | 3 | 357 | 26.85 |
| Gillian Hayes | 4 | 1852 | 155.64 |
| Lisha Hu | 5 | 103 | 7.45 |
| Jianfei Shen | 6 | 4 | 4.21 |