Understanding user's intention and situation using wearable sensors and emotion machine model

我们使用可穿戴传感器和Minsky的情感机器模型开发了几种意图和情景模型。我们已经开发了几个多模式传感系统，从信号处理、符号处理和知识处理获得的数据中理解人类的情况、意图和情感。多通道知识可以通过整合获取的信息、视频、声音、传感器数据、知识和诀窍来创建，我们已经构建了从各种可穿戴和无处不在的传感器获得的多通道知识内容，这些应用包括团队自行车、空手道、爬山和面对面会议。通过使用加速速度传感器等运动传感器来采集运动员的动作和观众的点头动作。空手道比赛和会议的情况，运动员和观众的意图和情绪，可以从动作和点头的类型和时间数据来评估。在此基础上，构建了多个基于情感机制的理解模型，提出了为骑行者提供多通道知识内容，让骑行者享受骑行乐趣的骑行者社区激活支持系统。它还提供了一种新的语音通信方式，使用自组织无线局域网技术来实现自发的语音通信。我们的理解模型可以应用于各种体育、艺术、文化、爱好等领域。

We have developed several intention and situations models by using wearable sensors and Minsky's emotion machine model. We have developed several multimodal sensing systems to comprehend human situations, intentions and emotions from data acquired by signal processing, symbol processing and knowledge processing. The multimodal knowledge can be created by integrating acquired information, videos, sounds, sensor data, knowledge and know-how.We have built several multimodal knowledge contents obtained from various wearable and ubiquitous sensors in several applications, including team cycling, Karate, mountain climbing and face-to-face meeting. The motions of the players and the nod motions of the audience are collected by using motion sensors such as accelerated velocity sensors. The situations of the karate match and the meeting, the intentions and emotions of the players and the audience can be evaluated from type and timing data of movements and nods. Thus, we have constructed several understanding models based on the emotion machine.We propose a cyclist community activation support system which provides multimodal knowledge contents for cyclists and makes them enjoy their riding. It also provides a new way of speech communication using an ad-hoc wireless LAN technology to achieve spontaneous speech communication. Our understanding models can be applied to various sports, arts, cultures, hobbies and so on.