18557768. PREDICTING MENTAL STATE CHARACTERISTICS OF USERS OF WEARABLE DEVICES simplified abstract (Hewlett-Packard Development Company, L.P.)
Contents
PREDICTING MENTAL STATE CHARACTERISTICS OF USERS OF WEARABLE DEVICES
Organization Name
Hewlett-Packard Development Company, L.P.
Inventor(s)
Jishang Wei of Guilford CT (US)
Rafael Antonio Ballagas of Palo Alto CA (US)
Erika H. Siegel of Palo Alto CA (US)
PREDICTING MENTAL STATE CHARACTERISTICS OF USERS OF WEARABLE DEVICES - A simplified explanation of the abstract
This abstract first appeared for US patent application 18557768 titled 'PREDICTING MENTAL STATE CHARACTERISTICS OF USERS OF WEARABLE DEVICES
The abstract of this patent application describes a method that involves generating physiological measures of a user using sensors in a wearable device while the user is performing a task. An inference engine processes these measures to predict task difficulty class, residual estimation, and the user's current mental state characteristic.
- Wearable device with sensors generates physiological measures of a user during a task
- Inference engine processes these measures to predict task difficulty class and residual estimation
- Predicts user's current mental state characteristic based on the processed physiological measures
Potential Applications: - Personalized task difficulty assessment for users in various fields such as sports, healthcare, and education - Mental state monitoring for individuals in high-stress environments like emergency responders or military personnel
Problems Solved: - Provides real-time feedback on task difficulty and mental state to improve performance and well-being - Enables personalized interventions based on individual physiological responses
Benefits: - Enhances user performance by adjusting task difficulty levels accordingly - Improves user well-being by providing insights into mental state during tasks
Commercial Applications: Title: Personalized Task Difficulty Assessment Technology This technology can be utilized in industries such as sports training, healthcare monitoring, and educational settings to optimize performance and well-being. The market implications include improved training programs, enhanced healthcare monitoring, and personalized educational approaches.
Questions about Personalized Task Difficulty Assessment Technology: 1. How does this technology benefit users in high-stress environments? - This technology benefits users in high-stress environments by providing real-time feedback on task difficulty and mental state, allowing for personalized interventions to improve performance and well-being. 2. How can this technology be integrated into existing wearable devices for seamless user experience? - This technology can be integrated into existing wearable devices through software updates or hardware modifications to enhance the user experience and provide valuable insights into task performance and mental state.
Original Abstract Submitted
An example method includes generating. with sensors of a wearable device. a plurality of physiological measures of a user of the wearable device while the user is performing a task. The method includes processing. with an inference engine of the wearable device. the plurality of physiological measures. The method includes generating. with the inference engine. a task difficulty class prediction and a residual estimation based on the processed physiological measures. The method includes generating, with the inference engine. a predicted value of a current mental state characteristic of the user based on the task difficulty class prediction and the residual estimation.
