技术领域Technical Field
本发明属于神经科学和医疗康复领域，特别涉及一种基于虚拟现实的社交模拟数字化干预系统。The present invention belongs to the field of neuroscience and medical rehabilitation, and in particular relates to a social simulation digital intervention system based on virtual reality.
背景技术Background Art
现实生活中，存在一些社交障碍或社交焦虑障碍的患者，由于无法正确理解社交情境和他人的意图，缺乏有效的社交技能，因而常常在人际交往中感到困难，严重影响了其生活质量。对于这类患者，需要进行有针对性的社交技能训练，以增强其社交认知能力、情绪管理能力和社交互动技巧；随着虚拟现实(VR)技术的发展，基于VR的社交模拟训练逐渐被应用于此类领域。通过构建逼真的虚拟社交场景，不同的社交情境可以被模拟和重复体验，患者可以在安全且可控的虚拟环境中进行社交训练，提高其社交技能。然而，现有的VR社交模拟训练系统存在一些不足。由于缺乏对患者生理和心理状态的实时监测，难以全面评估患者的认知和情绪变化，无法根据个体差异动态调整训练内容和难度，因此训练效果有限。此外，现有系统主要依赖视听模拟，缺乏对感知通道的多模态融合，体验沉浸感不足。In real life, some patients with social disorders or social anxiety disorders often find it difficult to interact with others because they cannot correctly understand social situations and the intentions of others and lack effective social skills, which seriously affects their quality of life. For such patients, targeted social skills training is needed to enhance their social cognitive ability, emotional management ability and social interaction skills. With the development of virtual reality (VR) technology, VR-based social simulation training has gradually been applied to such fields. By constructing realistic virtual social scenes, different social situations can be simulated and repeatedly experienced, and patients can conduct social training in a safe and controllable virtual environment to improve their social skills. However, the existing VR social simulation training system has some shortcomings. Due to the lack of real-time monitoring of the patient's physiological and psychological state, it is difficult to fully evaluate the patient's cognitive and emotional changes, and it is impossible to dynamically adjust the training content and difficulty according to individual differences, so the training effect is limited. In addition, the existing system mainly relies on audio-visual simulation, lacks multimodal fusion of perceptual channels, and lacks immersive experience.
发明内容Summary of the invention
有鉴于此，本发明提供了一种基于虚拟现实的社交模拟数字化干预系统，该系统包括：In view of this, the present invention provides a social simulation digital intervention system based on virtual reality, the system comprising:
数据采集模块，用于采集生理数据、心理及行为数据作为原始数据；Data collection module, used to collect physiological data, psychological and behavioral data as raw data;
数据预处理模块，用于对采集到的所述原始数据进行清洗和标准化，消除噪声和无效数据；A data preprocessing module is used to clean and standardize the collected raw data to eliminate noise and invalid data;
数据处理与分析模块，用于通过多模态数据融合技术处理和分析用户的生理数据、心理及行为数据，以评估用户的社交行为和情感状态，并提供反馈；Data processing and analysis module, used to process and analyze the user's physiological data, psychological and behavioral data through multimodal data fusion technology to evaluate the user's social behavior and emotional state and provide feedback;
电刺激干预模块，用于在社交模拟训练过程中对用户进行无创的经皮迷走神经干涉电刺激，以调节用户的神经活动状态；An electrical stimulation intervention module, used to perform non-invasive transcutaneous vagus nerve intervention electrical stimulation on the user during social simulation training to regulate the user's neural activity state;
动态训练调整模块根据所述电刺激干预模块的刺激效果、用户的行为数据与理想数据的差异，以及训练场景，动态调整训练内容的难度和侧重点；The dynamic training adjustment module dynamically adjusts the difficulty and emphasis of the training content according to the stimulation effect of the electrical stimulation intervention module, the difference between the user's behavior data and the ideal data, and the training scenario;
优化模块，用于通过优化损失函数，调整权重向量，以最小化误差。The optimization module is used to adjust the weight vector to minimize the error by optimizing the loss function.
特别地，所述数据采集模块包括眼动追踪设备、面部表情分析器、手部动作捕捉器、体感检测设备、语音识别系统和神经活动监测设备。In particular, the data acquisition module includes an eye tracking device, a facial expression analyzer, a hand motion capture device, a somatosensory detection device, a speech recognition system and a neural activity monitoring device.
特别地，其中多模态数据融合处理通过以下公式计算用户的社交行为和情感状态响应：In particular, the multimodal data fusion process calculates the user's social behavior and emotional state response through the following formula:
其中，为在时间t处的社交行为和情感状态响应值；in, is the social behavior and emotional state response value at timet ;
n为生理数据的模态数量，为第i种生理数据在时间处的响应函数，为第i种生理数据对应的权重因子；n is the number of modalities of physiological data, is theith physiological data at time The response function at is the weight factor corresponding to thei- th physiological data;
m为心理及行为数据的模态数量，为第j种心理及行为数据在时间处的响应函数，为第j种心理及行为数据对应的权重因子。m is the number of modes of psychological and behavioral data, is thejth psychological and behavioral data at time The response function at is the weight factor corresponding to thej -th psychological and behavioral data.
特别地，所述生理数据包括：眼动数据、面部表情数据、体感数据和神经活动数据；In particular, the physiological data includes: eye movement data, facial expression data, somatosensory data and neural activity data;
所述心理及行为数据包括：手部动作、手势数据和语音数据。The psychological and behavioral data include: hand movements, gesture data and voice data.
特别地，所述动态训练调整模块通过以下公式进行动态调整：In particular, the dynamic training adjustment module is dynamically adjusted by the following formula:
其中，为当前训练场景的调整结果，为当前第m+1个场景下的用户的生理数据、心理及行为数据的向量；为历史上第个场景下设定的理想的生理数据、心理及行为数据的指标，为核函数，衡量当前场景和历史场景的相似性；表示当前训练场景的特征向量，其中：表示之前的训练场景数量，表示考虑历史和当前场景的总数；表示历史第个场景特征向量；为用户在时间t处的社交行为和情感状态响应值，为训练场景的权重因子，为电刺激干预效果的响应函数；为电刺激干预效果的权重因子；为偏移量，用于调整训练难度；为用户的生理数据、心理及行为数据的权重因子，n为可参考的历史场景数。in, is the adjustment result of the current training scene, is the vector of the user's physiological data, psychological and behavioral data in the current m+1th scenario; For the first time in history The ideal physiological data, psychological and behavioral data indicators set in each scenario, is the kernel function, which measures the similarity between the current scene and the historical scene; Represents the feature vector of the current training scene, where: represents the number of previous training scenes, Indicates the total number of historical and current scenarios considered; Indicates the history scene feature vector; is the social behavior and emotional state response value of the user at timet , is the weight factor of the training scenario, is the response function of the electrical stimulation intervention effect; is the weight factor of the electrical stimulation intervention effect; is the offset, used to adjust the training difficulty; is the weight factor of the user's physiological data, psychological and behavioral data,and n is the number of historical scenarios that can be referenced.
特别地，所述优化模块通过以下优化损失函数，调整权重向量：In particular, the optimization module adjusts the weight vector by optimizing the loss function as follows:
其中为损失函数，ω为权重向量，为第i个数据点的误差向量，γ为正则化参数，N为数据点数量；通过优化损失函数，调整权重ω，使得误差和权重的平方和最小；根据优化后的权重ω和误差e，动态调整训练内容和难度。in is the loss function, ω is the weight vector, is the error vector of the i-th data point, γ is the regularization parameter, and N is the number of data points; by optimizing the loss function , adjust the weight ω so that the sum of the square of the error and the weight is minimized; according to the optimized weight ω and error e, dynamically adjust the training content and difficulty.
特别地，所述系统在虚拟现实环境中进行多种社交技能训练，包括社交发起技能训练、社交回应技能训练、情绪表达与管理训练及社交冲突处理训练。In particular, the system performs various social skills training in a virtual reality environment, including social initiation skills training, social response skills training, emotion expression and management training, and social conflict handling training.
特别地，其中，所述电刺激干预模块包括：刺激电极，用于将微弱电流施加到用户的耳甲区域；In particular, the electrical stimulation intervention module includes: stimulation electrodes for applying weak current to the concha area of the user;
电流发生器，用于产生微弱的交流或脉冲电流信号；Current generator, used to generate weak AC or pulse current signal;
刺激参数调节模块，用于根据用户的社交行为和情感状态响应值、当前场景下的用户的生理数据、心理及行为数据与历史上各个场景下设定的理想的生理数据、心理及行为数据的指标差异、当前训练内容的难度水平和用户的电刺激响应历史记录，当前场景和历史场景的相似度调节刺激的参数；A stimulation parameter adjustment module is used to adjust the stimulation parameters according to the user's social behavior and emotional state response value, the difference between the user's physiological data, psychological and behavioral data in the current scene and the ideal physiological data, psychological and behavioral data set in various scenes in history, the difficulty level of the current training content and the user's electrical stimulation response history record, and the similarity between the current scene and the historical scene;
同步控制模块，用于将无创的经皮迷走神经干涉电刺激与虚拟现实社交场景同步，在特定社交情境下施加刺激。The synchronization control module is used to synchronize non-invasive transcutaneous vagus nerve intervention electrical stimulation with the virtual reality social scene and apply stimulation in a specific social situation.
有益效果：Beneficial effects:
1.通过本发明的技术方案，实现了一种基于虚拟现实的社交模拟数字化干预系统，能够构建逼真的虚拟社交场景，为社交障碍患者提供安全、可控的社交训练环境，提高了训练的真实感和沉浸感。1. Through the technical solution of the present invention, a social simulation digital intervention system based on virtual reality is realized, which can construct realistic virtual social scenes, provide a safe and controllable social training environment for patients with social disorders, and improve the realism and immersion of training.
2.通过本发明的技术方案，将生理传感器、计算机视觉和语音识别等技术与虚拟现实相结合，实现了对患者行为、生理和神经活动状态的多模态感知和融合，全面评估了患者的社交认知和情绪变化，为个性化干预提供了关键信息支持。2. Through the technical solution of the present invention, physiological sensors, computer vision, speech recognition and other technologies are combined with virtual reality to achieve multimodal perception and fusion of patients' behavior, physiology and neural activity status, comprehensively evaluate patients' social cognition and emotional changes, and provide key information support for personalized intervention.
3.通过本发明的技术方案，引入了无创的经皮迷走神经电刺激(tVNS)干预技术，能够根据患者的神经活动响应实时调节无创的经皮迷走神经电刺激刺激参数，对患者的大脑活动进行调控，优化其认知状态和情绪管理能力，提高了社交训练的针对性和效率。3. Through the technical solution of the present invention, a non-invasive transcutaneous vagus nerve stimulation (tVNS) intervention technology is introduced, which can adjust the non-invasive transcutaneous vagus nerve stimulation stimulation parameters in real time according to the patient's neural activity response, regulate the patient's brain activity, optimize their cognitive state and emotional management ability, and improve the pertinence and efficiency of social training.
4.通过本发明的技术方案，建立了行为指标分析模型和动态训练调整算法，能够根据患者的行为表现与理想指标的差异、神经活动响应以及tVNS刺激效果，动态调整虚拟现实训练内容的难度和侧重点，形成了一个闭环自适应的训练系统。4. Through the technical solution of the present invention, a behavioral indicator analysis model and a dynamic training adjustment algorithm are established, which can dynamically adjust the difficulty and focus of the virtual reality training content according to the difference between the patient's behavioral performance and the ideal indicators, the neural activity response and the tVNS stimulation effect, forming a closed-loop adaptive training system.
5.通过本发明的技术方案，综合利用了虚拟现实技术、多模态交互技术、神经科学和人工智能算法等多学科知识，将先进的虚拟仿真、感知融合和神经调控技术应用于社交认知训练领域，拓展了相关技术的应用范围。5. Through the technical solution of the present invention, multidisciplinary knowledge such as virtual reality technology, multimodal interaction technology, neuroscience and artificial intelligence algorithms are comprehensively utilized, and advanced virtual simulation, perception fusion and neural regulation technology are applied to the field of social cognitive training, expanding the application scope of related technologies.
6.通过本发明的技术方案，为社交障碍患者提供了一种全新的数字化干预方式，克服了传统训练方法的局限性，能够根据患者的个体差异提供定制化、高效的社交技能训练，从而有效提高患者的生活质量，具有良好的社会效益和应用前景。6. Through the technical solution of the present invention, a new digital intervention method is provided for patients with social disorders, which overcomes the limitations of traditional training methods and can provide customized and efficient social skills training according to the individual differences of patients, thereby effectively improving the quality of life of patients, and has good social benefits and application prospects.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
图1为本发明中提供的一种基于虚拟现实的社交模拟数字化干预系统。FIG1 is a social simulation digital intervention system based on virtual reality provided in the present invention.
具体实施方式DETAILED DESCRIPTION
下面结合附图并举实施例，对本发明进行详细描述。本发明提供了一种基于虚拟现实的社交模拟数字化干预系统，如图1所示，该系统包括：The present invention is described in detail below with reference to the accompanying drawings and examples. The present invention provides a social simulation digital intervention system based on virtual reality, as shown in FIG1 , the system comprises:
数据采集模块，用于采集生理数据、心理及行为数据；所述数据采集模块包括眼动追踪设备、面部表情分析器、手部动作捕捉器、体感检测设备、语音识别系统和神经活动监测设备。The data acquisition module is used to collect physiological data, psychological and behavioral data; the data acquisition module includes an eye tracking device, a facial expression analyzer, a hand motion capture device, a body sensing detection device, a speech recognition system and a neural activity monitoring device.
数据预处理模块，用于对采集到的原始数据进行清洗和标准化，消除噪声和无效数据；数据预处理模块对采集到的原始数据进行以下处理：The data preprocessing module is used to clean and standardize the collected raw data and eliminate noise and invalid data. The data preprocessing module performs the following processing on the collected raw data:
数据清洗用于去除明显异常值和离群点，填补数据缺失或丢失的部分剔除重复数据；标准化处理用于对不同量纲的数据进行无量纲化处理，将数据映射到同一数值范围；对分类数据进行One-Hot编码或有序编码等处理。噪声消除用于对眼动、面部表情等图像视频数据进行滤波、平滑等降噪处理；对语音、神经活动等时序数据进行频谱分析、小波去噪等处理。Data cleaning is used to remove obvious abnormal values and outliers, fill in missing or lost data, and remove duplicate data; standardization is used to non-dimensionalize data of different dimensions and map the data to the same numerical range; One-Hot encoding or ordered encoding is performed on classified data. Noise elimination is used to filter, smooth, and perform other noise reduction processing on image and video data such as eye movements and facial expressions; and spectrum analysis and wavelet denoising are performed on time series data such as speech and neural activity.
随后通过数据切分将预处理后的数据切分为训练集、验证集和测试集；Then, the preprocessed data is divided into training set, validation set and test set through data segmentation;
数据处理与分析模块，用于通过多模态数据融合技术处理和分析用户的生理数据、心理及行为数据，以评估用户的社交行为和情感状态，并提供反馈。The data processing and analysis module is used to process and analyze the user's physiological data, psychological and behavioral data through multimodal data fusion technology to evaluate the user's social behavior and emotional state and provide feedback.
所述数据处理与分析模块通过多模态数据融合技术处理和分析用户的生理数据、心理及行为数据，以评估用户的社交行为和情感状态，其中多模态数据融合技术通过以下公式计算用户的社交行为和情感状态响应：The data processing and analysis module processes and analyzes the user's physiological data, psychological and behavioral data through multimodal data fusion technology to evaluate the user's social behavior and emotional state, wherein the multimodal data fusion technology calculates the user's social behavior and emotional state response through the following formula:
其中，为在时间t处的社交行为和情感状态响应值；in, is the social behavior and emotional state response value at timet ;
n为生理数据的模态数量，为第i种生理数据在时间处的响应函数，为第i种生理数据对应的权重因子；n is the number of modalities of physiological data, is theith physiological data at time The response function at is the weight factor corresponding to thei- th physiological data;
m为心理及行为数据的模态数量，为第j种心理及行为数据在时间处的响应函数，为第j种心理及行为数据对应的权重因子。m is the number of modes of psychological and behavioral data, is thejth psychological and behavioral data at time The response function at is the weight factor corresponding to thej -th psychological and behavioral data.
其中，所述生理数据包括：眼动数据、面部表情数据、体感数据和神经活动数据；神经活动数据包括：脑电图EEG和/或近红外fNIRS数据。The physiological data include: eye movement data, facial expression data, body sensation data and neural activity data; the neural activity data include: electroencephalogram (EEG) and/or near-infrared fNIRS data.
所述心理及行为数据包括：手部动作、手势数据和语音数据。The psychological and behavioral data include: hand movements, gesture data and voice data.
电刺激干预模块，用于在社交模拟训练过程中对用户进行无创的经皮迷走神经电刺激（tVNS）干涉，以调节用户的神经活动状态；An electrical stimulation intervention module, used to perform non-invasive transcutaneous vagus nerve stimulation (tVNS) intervention on the user during social simulation training to regulate the user's neural activity state;
动态训练调整模块根据所述电刺激干预模块的刺激效果、用户的行为数据与理想数据的差异，以及训练场景，动态调整训练内容的难度和侧重点；所述动态训练调整模块通过以下公式进行动态调整：The dynamic training adjustment module dynamically adjusts the difficulty and emphasis of the training content according to the stimulation effect of the electrical stimulation intervention module, the difference between the user's behavior data and the ideal data, and the training scenario; the dynamic training adjustment module performs dynamic adjustment through the following formula:
其中，为当前训练场景的调整结果，为当前第m+1个场景下的用户的生理数据、心理及行为数据的向量；为历史上第个场景下设定的理想的生理数据、心理及行为数据的指标，为核函数，衡量当前场景和历史场景的相似性；表示当前训练场景的特征向量，其中：表示之前的训练场景数量，表示考虑历史和当前场景的总数；表示历史第个场景特征向量；为用户在时间t处的社交行为和情感状态响应值，为训练场景的权重因子，为电刺激干预效果的响应函数；为电刺激干预效果的权重因子；为偏移量，用于调整训练难度；为用户的生理数据、心理及行为数据的权重因子，n为可参考的历史场景数。in, is the adjustment result of the current training scene, is the vector of the user's physiological data, psychological and behavioral data in the current m+1th scenario; For the first time in history The ideal physiological data, psychological and behavioral data indicators set in each scenario, is the kernel function, which measures the similarity between the current scene and the historical scene; Represents the feature vector of the current training scene, where: represents the number of previous training scenes, Indicates the total number of historical and current scenarios considered; Indicates the history scene feature vector; is the social behavior and emotional state response value of the user at timet , is the weight factor of the training scenario, is the response function of the electrical stimulation intervention effect; is the weight factor of the electrical stimulation intervention effect; is the offset, used to adjust the training difficulty; is the weight factor of the user's physiological data, psychological and behavioral data,and n is the number of historical scenarios that can be referenced.
所述电刺激干预模块包括：刺激电极，用于将微弱电流施加到用户的耳甲区域；The electrical stimulation intervention module includes: stimulation electrodes for applying weak current to the user's concha area;
电流发生器，用于产生微弱的交流或脉冲电流信号；Current generator, used to generate weak AC or pulse current signal;
刺激参数调节模块，用于根据用户的社交行为和情感状态响应值、当前场景下的用户的生理数据、心理及行为数据与历史上各个场景下设定的理想的生理数据、心理及行为数据的指标差异、当前训练内容的难度水平和用户的电刺激响应历史记录，当前场景和历史场景的相似度调节刺激的参数；A stimulation parameter adjustment module is used to adjust the stimulation parameters according to the user's social behavior and emotional state response value, the difference between the user's physiological data, psychological and behavioral data in the current scene and the ideal physiological data, psychological and behavioral data set in various scenes in history, the difficulty level of the current training content and the user's electrical stimulation response history record, and the similarity between the current scene and the historical scene;
同步控制模块，用于将无创的经皮迷走神经干涉电刺激与虚拟现实社交场景同步，在特定社交情境下施加刺激。The synchronization control module is used to synchronize non-invasive transcutaneous vagus nerve intervention electrical stimulation with the virtual reality social scene and apply stimulation in a specific social situation.
当用户的社交行为和情感状态响应值R(t)低于正常水平时，增加刺激强度和频率，以提高用户的注意力和兴奋度；When the user's social behavior and emotional state response valueR(t) is lower than normal, increase the stimulation intensity and frequency to improve the user's attention and excitement;
当训练内容难度较高时，适当增加刺激强度，提高用户的集中力和应对能力；根据用户的电刺激响应历史记录，调整刺激参数以达到个性化的最佳刺激效果。When the training content is more difficult, the stimulation intensity is appropriately increased to improve the user's concentration and coping ability; according to the user's electrical stimulation response history, the stimulation parameters are adjusted to achieve the personalized best stimulation effect.
优化模块，用于通过优化损失函数，调整权重向量，以最小化误差。所述优化模块通过以下优化损失函数，调整权重向量：The optimization module is used to adjust the weight vector by optimizing the loss function to minimize the error. The optimization module adjusts the weight vector by optimizing the loss function as follows:
其中为损失函数，ω为权重向量，为第i个数据点的误差向量，γ为正则化参数，N为数据点数量；通过优化损失函数，调整权重ω，使得误差和权重的平方和最小；根据优化后的权重ω和误差e，动态调整训练内容和难度。in is the loss function, ω is the weight vector, is the error vector of the i-th data point, γ is the regularization parameter, and N is the number of data points; by optimizing the loss function , adjust the weight ω so that the sum of the square of the error and the weight is minimized; according to the optimized weight ω and error e, dynamically adjust the training content and difficulty.
所述系统能够在虚拟现实环境中进行多种社交技能训练，包括社交发起技能训练、社交回应技能训练、情绪表达与管理训练及社交冲突处理训练。The system can perform various social skills training in a virtual reality environment, including social initiation skills training, social response skills training, emotion expression and management training, and social conflict handling training.
所述社交发起技能训练包括如何主动与他人打招呼、开启对话；所述社交回应技能训练包括如何适当地回应他人的问候或询问；所述情绪表达与管理训练包括如何识别并表达自己的情绪，以及如何管理负面情绪。The social initiation skills training includes how to proactively greet others and start a conversation; the social response skills training includes how to appropriately respond to others' greetings or inquiries; the emotional expression and management training includes how to identify and express one's own emotions, and how to manage negative emotions.
本发明提出了一种基于虚拟现实的社交模拟数字化干预系统，将虚拟现实技术、多模态交互技术、神经调控技术和人工智能算法等多学科知识有机结合，形成了一套完整的数字化干预解决方案，用于对社交障碍患者进行高效、个性化的社交技能训练。The present invention proposes a social simulation digital intervention system based on virtual reality, which organically combines multidisciplinary knowledge such as virtual reality technology, multimodal interaction technology, neural regulation technology and artificial intelligence algorithm to form a complete digital intervention solution for efficient and personalized social skills training for patients with social disorders.
该系统以虚拟现实为核心，能够构建逼真、沉浸式的虚拟社交场景，为患者提供安全、可控的社交训练环境，模拟不同的社交情境并支持重复练习，极大提高了训练的真实感和体验感。The system is centered on virtual reality and can build realistic and immersive virtual social scenes, providing patients with a safe and controllable social training environment. It simulates different social situations and supports repeated practice, greatly improving the realism and experience of training.
同时，该系统集成了生理传感器、计算机视觉和语音识别等技术，实现了对患者行为、生理和神经活动状态的多模态感知与融合，全面评估患者在社交过程中的认知、情绪和行为表现，为个性化干预提供数据支持。At the same time, the system integrates technologies such as physiological sensors, computer vision and speech recognition, realizing multimodal perception and fusion of patients' behavior, physiology and neural activity status, comprehensively evaluating patients' cognitive, emotional and behavioral performance in the social process, and providing data support for personalized intervention.
此外，该系统还引入了无创的经皮迷走神经电刺激(tVNS)干预技术，通过实时调节tVNS刺激参数，对患者的大脑活动进行调控，优化其注意力、情绪管理和社交认知等能力，提高社交训练的针对性和效率。In addition, the system also introduces non-invasive transcutaneous vagus nerve stimulation (tVNS) intervention technology, which regulates the patient's brain activity by adjusting tVNS stimulation parameters in real time, optimizes their attention, emotion management, social cognition and other abilities, and improves the targetedness and efficiency of social training.
该系统建立了行为指标分析模型和动态训练调整算法，能够根据患者的行为表现、神经活动响应以及tVNS刺激效果，动态调整虚拟现实训练内容的难度和侧重点，形成一个闭环自适应的训练系统，持续优化干预方案。The system has established a behavioral indicator analysis model and a dynamic training adjustment algorithm, which can dynamically adjust the difficulty and focus of virtual reality training content according to the patient's behavioral performance, neural activity response, and tVNS stimulation effect, forming a closed-loop adaptive training system to continuously optimize the intervention plan.
通过将虚拟现实仿真、多模态交互、神经调控和人工智能算法等多种先进技术集成应用，本发明系统实现了社交训练的高度个性化、智能化和高效化，为社交障碍患者提供了一种全新的数字化干预方式，克服了传统训练方法的局限，能够根据患者的个体差异提供量身定制的社交技能训练，从而有效提高患者的生活质量，具有广阔的应用前景。By integrating and applying multiple advanced technologies such as virtual reality simulation, multimodal interaction, neural regulation and artificial intelligence algorithms, the system of the present invention achieves highly personalized, intelligent and efficient social training, providing a new digital intervention method for patients with social disorders, overcoming the limitations of traditional training methods, and being able to provide customized social skills training based on individual differences of patients, thereby effectively improving the quality of life of patients. It has broad application prospects.
本设计方案通过优化方法实现动态训练调整，将用户的神经活动响应与行为数据结合，实时调整训练内容和难度，为高功能自闭症患者提供个性化、实时的反馈和优化。通过优化损失函数来进一步精确调整训练策略，以提升训练效果。通过该动态训练调整设计，系统能够根据用户在虚拟现实环境中的实时表现和神经活动响应，利用优化方法生成个性化反馈，并动态调整训练内容和难度。这样可以帮助高功能自闭症患者逐步提升社交技能，并为治疗师提供有效的监控和指导工具。This design achieves dynamic training adjustment through optimization methods, combines the user's neural activity response with behavioral data, adjusts the training content and difficulty in real time, and provides personalized, real-time feedback and optimization for high-functioning autistic patients. The training strategy is further precisely adjusted by optimizing the loss function to improve the training effect. Through this dynamic training adjustment design, the system can generate personalized feedback based on the user's real-time performance and neural activity response in the virtual reality environment, and dynamically adjust the training content and difficulty using optimization methods. This can help high-functioning autistic patients gradually improve their social skills and provide therapists with effective monitoring and guidance tools.
综上所述，以上仅为本发明的较佳实施例而已，并非用于限定本发明的保护范围。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。In summary, the above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
对于本领域技术人员而言，显然本发明实施例不限于上述示范性实施例的细节，而且在不背离本发明实施例的精神或基本特征的情况下，能够以其他的具体形式实现本发明实施例。因此，无论从哪一点来看，均应将实施例看作是示范性的，而且是非限制性的，本发明实施例的范围由所附权利要求而不是上述说明限定，因此旨在将落在权利要求的等同要件的含义和范围内的所有变化涵括在本发明实施例内。不应将权利要求中的任何附图标记视为限制所涉及的权利要求。此外，显然“包括”一词不排除其他单元或步骤，单数不排除复数。系统、装置或终端权利要求中陈述的多个单元、模块或装置也可以由同一个单元、模块或装置通过软件或者硬件来实现。第一，第二等词语用来表示名称，而并不表示任何特定的顺序。It is obvious to those skilled in the art that the embodiments of the present invention are not limited to the details of the above exemplary embodiments, and that the embodiments of the present invention can be implemented in other specific forms without departing from the spirit or basic features of the embodiments of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the embodiments of the present invention is limited by the attached claims rather than the above description, so it is intended to include all changes that fall within the meaning and scope of the equivalent elements of the claims in the embodiments of the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units, modules or devices stated in the system, device or terminal claims can also be implemented by the same unit, module or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.
最后应说明的是，以上实施方式仅用以说明本发明实施例的技术方案而非限制，尽管参照以上较佳实施方式对本发明实施例进行了详细说明，本领域的普通技术人员应当理解，可以对本发明实施例的技术方案进行修改或等同替换都不应脱离本发明实施例的技术方案的精神和范围。Finally, it should be noted that the above implementation modes are only used to illustrate the technical solutions of the embodiments of the present invention and are not intended to limit them. Although the embodiments of the present invention have been described in detail with reference to the above preferred implementation modes, those skilled in the art should understand that the technical solutions of the embodiments of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the embodiments of the present invention.
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