Artificial Intelligence - Multimodal Emotion Detection System - (AI, ML, and Human)

Abstract

System for multimodal recording of human emotions, comprising an EEG-like cap, at least one sensor for sensory impressions, and an integrated AI unit for human evaluation.

Description

Hardware components • EEG-like cap with electrodes for measuring brain waves • Sensors for visual signals (AR glasses / camera), sense of touch (haptic interfaces), speech / acoustics (microphones), smell / taste (chemical sensors) • Interfaces to standard devices (smartphones, tablets, PCs)

[0001] The portable data acquisition unit, in the form of an EEG-like cap, includes electrodes for measuring electrical brain activity. Additional sensors for visual, auditory, haptic, olfactory, and gustatory stimuli can be connected via standardized interfaces. External devices such as smartphones, tablets, or AR glasses can be integrated via wireless or wired connections.

[0002] The collected data is aggregated in a data processing platform equipped with an AI architecture. This architecture utilizes neural networks and sensor fusion, enabling the synchronization and real-time analysis of multimodal data streams.

[0003] The system creates both individual profiles (e.g., joy, stress, concentration) and collective profiles when the data is used by multiple users. These group profiles reveal shared emotional patterns that can be used for teamwork or decision-making processes.

[0004] A database stores positive emotional patterns that can later be used in training situations. If a user displays negative emotions, a positive pattern is automatically activated and offered as a learning aid. Additionally, the system allows for real-time speech translation and the automated assignment of tasks.

[0005] The security concept prevents manipulation through multi-stage controls, encryption, audit trails and a level system where only users with proven behavior are granted access to higher functions. Software / AI • Multimodal learning system (deep learning + sensor fusion) • Real-time analysis and classification of states • Individual customization per user (personalization)

[0006] The invention relates to a system in the field of artificial intelligence (AI) and machine learning that is capable of capturing, processing and interpreting human emotions, sensory impressions and cognitive states in real time.

[0007] While current technology allows the use of EEG systems to record brainwaves and individual sensors for visual, auditory, or haptic signals, no system currently exists that combines these diverse data sources and integrates them into a machine-learning AI to derive both individual and collective emotional states. Furthermore, approaches for systematically storing positive patterns and making them usable for learning, therapy, education, and work processes are lacking.

[0008] The purpose of the invention is to provide a system that closes the gap between pure data collection and genuine emotional interpretation, actively integrates the user into education and work, overcomes language barriers, and at the same time prevents misuse through security mechanisms.

[0009] To solve this problem, a wearable system is proposed that includes an EEG-like cap with electrodes for real-time brainwave recording. This cap can be combined with additional sensors that capture the user's visual, auditory, haptic, olfactory, and gustatory impressions. The multimodal data is then aggregated in a central AI module and analyzed using deep learning algorithms. Applications • Medicine: Assessment of pain, depression, cognitive states • Workplace: Optimizing workload / concentration • Gaming & AR / VR: immersive environments with emotional feedback • Accessibility: Assistive devices for people with communication difficulties

[0010] The system can be used by a single person or by multiple users simultaneously. When used by multiple users, individual signals are synchronized in a central analysis module and combined into group profiles. This allows for the recording of collective moods, stress levels, and motivational states, which can then be used for teamwork, decision-making, and conflict prevention.

[0011] Another key element of the invention lies in the storage and use of positive patterns. Emotional states associated with optimism, motivation, and success are stored in a database and can be used as a basis for training in negative states. This creates a system that promotes learning processes, supports therapy, and enables people to participate in education or work with optimism and performance.

[0012] The system also includes a language and translation module that translates voice input into other languages ​​in real time, thus facilitating communication between users from different backgrounds. Additionally, work orders can be automatically generated and flexibly assigned based on the user's current emotional and cognitive state as well as their abilities.

[0013] To protect against manipulation, the system includes a security module that detects unusual data patterns, an audit trail that transparently records all interactions, and a level system. Each user starts with limited tasks and functions. Only through proven behavior, successful use, and tamper-free participation can they advance to higher levels, which allow for greater responsibility and more complex tasks. Misuse leads to automatic demotion.

[0014] The invention is modular and scalable to different technical platforms such as servers, cloud environments, edge devices, or, in the future, quantum computers. It represents a novel human-machine interface that combines technical, social, and economic innovations.

Claims

[1] System for multimodal recording of human emotions, comprising an EEG-like cap, at least one sensor for sensory impressions and an integrated AI unit for human evaluation. [2] System according to claim 1. characterized by that the EEG cap records brainwaves in real time and synchronizes them with sensory impressions. [3] System according to claim 1 or 2, characterized by that the AI ​​unit processes multimodal data streams and interprets emotional states. [4] System according to one of claims 1-3, characterized by that external devices such as smartphones, tablets, AR glasses or keyboards are integrated as additional sensors. [5] System according to any one of claims 1-4, characterized by that the results are used in real time to control assistance systems or immersive applications. [6] System according to any one of claims 1-5, characterized bythat multiple users are connected simultaneously and their data is merged in a central analysis module. [7] System according to claim 6, characterized by , that collective group profiles are created that reflect the emotional states of multiple users. [8] System according to claim 6 or 7. characterized by that the group profiles are used for teamwork, decision-making processes and conflict prevention. [9] System according to any one of claims 1-8, characterized by , that positive emotional patterns are stored and made available as a basis for training. [10] System according to claim 9, characterized by that negative emotions automatically activate positive patterns to promote optimism and motivation. [11] System according to any one of claims 1-10, characterized by that a language and translation module is integrated, which transmits language input in real time. [12] System according to any one of claims 1-11, characterized by , that work orders are automatically created based on the analyzed emotional and cognitive states and flexibly assigned to users. [13] System according to any one of claims 1-12, characterized by that it is used to integrate users into education and work. [14] System according to any one of claims 1-13, characterized by , that a security module detects and prevents attempts to manipulate input data. [15] System according to any one of claims 1-14, characterized by , that every interaction is recorded in an audit trail. [16] System according to any one of claims 1-15, characterized by , that a level system is planned which releases functions and tasks in stages. [17] System according to claim 16, characterized by that users can only reach higher levels through proven behavior and successful usage. [18] System according to one of claims 16-17, characterized by, that in case of misuse or incorrect use the level will be automatically downgraded.

Images