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

我们利用可穿戴传感器和明斯基的情感机器模型开发了几个意图和情境模型。我们已经开发了几个多模态传感系统，通过信号处理、符号处理和知识处理获得的数据来理解人类的情况、意图和情感。通过整合获取的信息、视频、声音、传感器数据、知识和专有技术，可以创建多模式知识。我们构建了多个多模态的知识内容，这些知识内容来自于各种可穿戴和无处不在的传感器，应用范围包括团队自行车、空手道、登山和面对面会议。利用加速速度传感器等运动传感器采集运动员的动作和观众的点头动作。通过动作和点头的类型和时间数据，可以评估空手道比赛和会面的情况，以及选手和观众的意图和情绪。因此，我们构建了几个基于情感机器的理解模型。我们提出了一个骑行者社区激活支持系统，为骑行者提供多模式的知识内容，使骑行者享受骑行。它还提供了一种新的语音通信方式，利用自组织无线局域网技术实现自发语音通信。我们的理解模型可以应用于各种体育、艺术、文化、爱好等。

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.