Name
Title | ||
|---|---|---|
Analyzing Muscle Activity and Force with Skin Shape Captured by Non-contact Visual Sensor. |
Abstract | ||
|---|---|---|
Estimating physical information by vision as humans do is useful for the applications with physical interaction in the real world. For example, observing muscle bulging infers how much force a person puts on the muscle to interact with an object or environment. Since the human skin deforms due to muscle activity, it is expected that skin deformation gives information to analyze human motion. This paper demonstrates that biomechanical information can be derived from skin shape by analyzing the relationship between skin deformation, force produced by muscles, and muscle activity. We first obtained the dataset simultaneously acquired by a range sensor, a force sensor, and electromyograph EMG sensors. Since recent range sensors based on non-contact visual measurement acquires accurate and dense shape of an object at high frame rate, the deforming skin can be observed. The deformation is calculated by finding the correspondence between a template shape and each range scan. The relationship between skin deformation and other data is learned. In this paper, the following problems are considered: 1 estimating force from skin shape, 2 estimating muscle activity from skin shape, 3 synthesizing skin shape from muscle activity. In the experiments, the database learned from the sensor data can be used for the above problems, and the skin shape gives useful information to explain the muscle activity. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/978-3-319-29451-3_39 | PSIVT |
Field | DocType | Volume |
Force sensor,Muscle activity,Computer vision,Feature vector,Physical interaction,Pattern recognition,Computer science,Physical information,Human skin,Artificial intelligence,Frame rate,Deformation (mechanics) | Conference | 9431 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
20 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ryusuke Sagawa | 1 | 631 | 52.61 |
| Yoshiyasu, Y. | 2 | 16 | 5.64 |
| Alexander Alspach | 3 | 11 | 2.34 |
| Ko Ayusawa | 4 | 90 | 12.69 |
| katsu yamane | 5 | 734 | 71.12 |
| Adrian Hilton | 6 | 2379 | 151.27 |