Name
Abstract | ||
|---|---|---|
Various conditions can result in scratching behavior and severe itching conditions such as atopic dermatitis can significantly impact on one's quality of life. Because the management of many itching conditions is not necessarily about curing the condition but instead about properly maintaining or controlling the condition, a proper understanding of these types of conditions and accurate recognitions of scratching behavior are important. In particular, a clear understanding of scratching behaviors can be difficult for young children or for those who engage in nocturnal itching while sleeping. In this work, we design a prototype system with two smartwatches which recognize scratching motions and validate the results using an infrared camera to provide the ground truth. We classify scratching motions with the C4.5 algorithm and analyze the data to understand the scratch patterns and to validate our system. Our initial results from the sleep data of three healthy participant show that the proposed method can provide accuracy that exceeds 90%. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2702613.2732820 | CHI Extended Abstracts |
Keywords | Field | DocType |
health,signal processing systems,mobile system,scratch recognition,smartwatch | Scratch,Computer science,Systems design,Human–computer interaction,Smartwatch,Scratching | Conference |
Citations | PageRank | References |
2 | 0.38 | 3 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jongin Lee | 1 | 12 | 4.87 |
| cho d k cho daeki | 2 | 1117 | 54.94 |
| Seokwoo Song | 3 | 146 | 10.96 |
| Seungho Kim | 4 | 2 | 0.38 |
| Eunji Im | 5 | 5 | 0.84 |
| John Kim | 6 | 120 | 9.87 |