18285433. INFORMATION PROCESSING APPARATUS, FEATURE QUANTITY EXTRACTION METHOD, TRAINING DATA GENERATION METHOD, ESTIMATION MODEL GENERATION METHOD, STRESS LEVEL ESTIMATION METHOD, AND STORAGE MEDIUM simplified abstract (NEC Corporation)
Contents
- 1 INFORMATION PROCESSING APPARATUS, FEATURE QUANTITY EXTRACTION METHOD, TRAINING DATA GENERATION METHOD, ESTIMATION MODEL GENERATION METHOD, STRESS LEVEL ESTIMATION METHOD, AND STORAGE MEDIUM
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 INFORMATION PROCESSING APPARATUS, FEATURE QUANTITY EXTRACTION METHOD, TRAINING DATA GENERATION METHOD, ESTIMATION MODEL GENERATION METHOD, STRESS LEVEL ESTIMATION METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract
- 1.4 Original Abstract Submitted
INFORMATION PROCESSING APPARATUS, FEATURE QUANTITY EXTRACTION METHOD, TRAINING DATA GENERATION METHOD, ESTIMATION MODEL GENERATION METHOD, STRESS LEVEL ESTIMATION METHOD, AND STORAGE MEDIUM
Organization Name
Inventor(s)
Yoshiki Nakashima of Tokyo (JP)
Masanori Tsujikawa of Tokyo (JP)
INFORMATION PROCESSING APPARATUS, FEATURE QUANTITY EXTRACTION METHOD, TRAINING DATA GENERATION METHOD, ESTIMATION MODEL GENERATION METHOD, STRESS LEVEL ESTIMATION METHOD, AND STORAGE MEDIUM - A simplified explanation of the abstract
This abstract first appeared for US patent application 18285433 titled 'INFORMATION PROCESSING APPARATUS, FEATURE QUANTITY EXTRACTION METHOD, TRAINING DATA GENERATION METHOD, ESTIMATION MODEL GENERATION METHOD, STRESS LEVEL ESTIMATION METHOD, AND STORAGE MEDIUM
The patent application describes an information processing apparatus that can extract feature quantities from biological signals to estimate a subject's stress level.
- Identification means to identify a time zone where chronic stress tendencies are evident in biological signals.
- Extraction means to extract feature quantities from signals in the identified time zone for stress level estimation.
- Feature quantities can be used in machine learning models or direct stress level estimation.
Potential Applications: - Healthcare: Monitoring stress levels in patients for better treatment plans. - Wearable Technology: Integrating stress level monitoring in smart devices for personal health tracking.
Problems Solved: - Efficient extraction of feature quantities for stress level estimation. - Improved understanding of stress patterns in biological signals.
Benefits: - Enhanced accuracy in stress level estimation. - Personalized stress management strategies based on individual data.
Commercial Applications: - Health and wellness apps incorporating stress monitoring features. - Medical devices for stress-related conditions.
Prior Art: No specific prior art information provided in the abstract.
Frequently Updated Research: Stay updated on advancements in stress level estimation techniques and machine learning models for health monitoring.
Questions about the technology: 1. How does the identification means determine the time zone of interest for stress level estimation? 2. What are the potential limitations of using feature quantities extracted from biological signals for stress level estimation?
Original Abstract Submitted
In order to appropriately extract feature quantities for use in machine learning or estimation of a stress level, an information processing apparatus () includes: an identification means () of identifying, as a time zone of interest, a time zone in which a chronic stress tendency is notably shown in biological signals which have been acquired from a subject over a predetermined time period; and an extraction means () of extracting one or more feature quantities from biological signals acquired in the time zone of interest which has been identified, the one or more feature quantities being used in machine learning of an estimation model for estimating a stress level or used in estimation of a stress level using the estimation model.
