Name
Abstract | ||
|---|---|---|
Human-centered computing is rapidly becoming a major research direction in human-computer interaction research. Among the various research issues, we believe that affective computing, or the ability of computers to react according to what a user feels, is very important. In order to recognize the human affect (feeling), one can rely on the analysis of signal inputs captured by a multitude of means. In this paper, we propose to make use of human physiological signals as a new form of modality in determining human affects, in a non-intrusive manner. This is achieved via the physiological mouse, as a first step towards affective computing. We augment the mouse with a small optical component for capturing user photoplethysmographic (PPG) signal. With the PPG signal, we are able to compute and derive human physiological signals. We built a prototype of the physiological mouse and measured raw PPG readings. We performed experiments to study the accuracy of our approach in determining human physiological signals from the mouse PPG data. We believe that our research will provide a new dimension for multimodal affective computing research. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/s10209-016-0469-9 | Universal Access in the Information Society |
Keywords | Field | DocType |
mouse controllers (computers),photoplethysmography,user photoplethysmographic signal,optical component,human computer interaction,human physiological signals,signal input analysis,human affect recogniion,medical signal processing,physiological mouse,human feeling recogniion,gadget prototype,affective computing, physiological signals, non-intrusive measurement, gadget prototype,emotion recognition,ppg readings,affective computing,user ppg signal,physiological signals,emotion-aware mouse,non-intrusive measurement,multimodal affective computing research,human-centered computing,mouse ppg data,human-computer interaction,prototypes,physiology,human centered computing | Computer vision,Heart beat,Computer science,Real-time computing,Human–computer interaction,Artificial intelligence,Affective computing | Conference |
Volume | Issue | ISSN |
16 | 2 | 1615-5297 |
Citations | PageRank | References |
3 | 0.39 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yujun Fu | 1 | 3 | 0.39 |
| Hong Va Leong | 2 | 1099 | 173.04 |
| Grace Ngai | 3 | 882 | 89.27 |
| Michael Xuelin Huang | 4 | 64 | 9.59 |
| Stephen C. F. Chan | 5 | 168 | 15.78 |