Name
Title | ||
|---|---|---|
SmartMove: a smartwatch algorithm to distinguish between high- and low-amplitude motions as well as doffed-states by utilizing noise and sleep |
Abstract | ||
|---|---|---|
In this paper, we describe a self adapting algorithm for smart watches to define individual transitions between motion intensities. The algorithm enables for a distinction between high-amplitude motions (e.g. walking, running, or simply moving extremities) low-amplitude motions (e.g. human microvibrations, and heart rate) as well as a general doffed-state. A prototypical implementation for detecting all three motion types was tested with a wrist-worn acceleration sensor. Since the aforementioned motion types are user-specific, SmartMove incorporates a training module based on a novel actigraphy-based sleep detection algorithm, in order to learn the specific motion types. In addition, our proposed sleep algorithm enables for reduced power consumption since it samples at a very low rate. Furthermore, the algorithm can identify suitable timeframes for an inertial sensor-based detection of vital-signs (e.g. seismocardiography or ballistocardiography). |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2948963.2948964 | iWOAR |
Keywords | DocType | ISBN |
Activity Monitoring, Activity Recognition, Wearables, Smartwatch, Microvibration, Sleep, Self Adapting, Seismocardiography, Ballistocardiography, Motion | Conference | 978-1-4503-4245-2 |
Citations | PageRank | References |
1 | 0.35 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marian Haescher | 1 | 45 | 6.75 |
| John Trimpop | 2 | 10 | 2.40 |
| Gerald Bieber | 3 | 56 | 9.63 |
| Bodo Urban | 4 | 1 | 0.69 |