Abstract
Techniques for monitoring user hand health and safety, estimating risks associated with user hand activity, and generation of suitable user alerts based on the estimated risk are described. With user permission, wearable devices such as AR headsets are utilized to determine a state of health of a user’s hands based on user activities and the user’s interactions with their environment. Actions such as hand washing, disinfecting, cleansing, etc. are identified. Machine learning models are utilized to identify the user practices based on observed user behavior. Protective hand wear use is identified, and surfaces, objects, and/or people touched by a user during the course of the user’s activities are monitored. A hand contamination index for the user is generated based on monitored parameters. Based on the determined hand contamination index and an analysis of a user’s potential activity, suitable alerts are generated and provided to the user.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Anonymous, "Personal Hand Safety Monitoring System", Technical Disclosure Commons, (August 13, 2020)
https://www.tdcommons.org/dpubs_series/3519