A Probabilistic Model of Human Activity Recognition with Loose Clothing.

ABSTRACT: Human activity recognition has become an attractive research area with the development of on-body wearable sensing technology. Textiles-based sensors have recently been used for activity recognition. With the latest electronic textile technology, sensors can be incorporated into garments so that users can enjoy long-term human motion recording worn comfortably. However, recent empirical findings suggest, surprisingly, that clothing-attached sensors can actually achieve higher activity recognition accuracy than rigid-attached sensors, particularly when predicting from short time windows. This work presents a probabilistic model that explains improved responsiveness and accuracy with fabric sensing from the increased statistical distance between movements recorded. The accuracy of the

SUBMITTER: Shen T 

PROVIDER: S-EPMC10220539 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature