| Autor: |
Ratnani, Grisha R., Chaudhari, Sahil, Nathani, Harsh, Vardhan, Vishnu |
| Předmět: |
|
| Zdroj: |
AIP Conference Proceedings; 2024, Vol. 3188 Issue 1, p1-8, 8p |
| Abstrakt: |
This article thoroughly overviews how RGB-D (Red green blue and Depth) cameras are used in home-schooling physical therapy. These cameras have become essential instruments for boosting training regimens, tracking advancement, and permitting customized workout experiences as technology continues to evolve. Physical exercises play an essential role in physiotherapy, and RGB-D devices can be utilized to recognize them to make interactive computer healthcare applications in the future. One of the advances in using extensible recognition models is detecting other human behaviours using noisy sensors without collecting much data. The studies reveal adequate detection without any part division, body part tracing, joint observation, or temporal subdivision approaches. There are numerous advantages to computerized home monitoring of physiotherapy activities. They integrate three essential components of a physiotherapy exercise into our system: movement patterns, stance information, and the exercise object. Machine learning approaches are used to collect lower-level information about each component. To estimate the repeat counts, a novel post-processing technique is used. This article summarizes the available research and explores RGB-D cameras' advantages, drawbacks, and potential applications for at-home physical activity. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
