Erkennung von Mehrfingergesten mit einem Fingerring: Ubiquitäre Interaktion für das Internet of Things

物联网（IoT）是指各种各样的连接设备，内置传感器，收集和交换信息。这些对象中的大多数没有配备专用的用户界面技术。因此，与物联网的交互需要新的交互模式，即无处不在的交互设备，这些设备无缝地存在于用户的日常生活中，不受任何特定事物的约束。它们还代表了与物联网交互的一种有前途的模式，因为它们可以传达涉及物联网物理方面的空间关系。配备传感器的指环是无处不在的手势检测的有前途的基础。然而，大多数现有的传感器环只能跟踪一个手指的运动，或者在它们可以识别的手势方面受到严重限制。此外，手势识别算法，如果连续应用，可以很容易地超过电池的功率容量，该电池足够小以集成在指环中。这些缺点限制了电流传感器环的适用性和实用性。该项目的目的是探索和评估电容式接近传感的能力和限制，使多个手指手势识别与一个手指戒指在一整天。为此，我们遵循三重研究议程，回答以下问题：（1）电容式接近传感器和其他传感器的哪种配置最适合检测手势，这项技术的限制是什么？(2)如何将生成的数据流映射到骨骼手模型以实现手指跟踪？(3)预过滤算法可以优化功率使用到什么程度？为了回答这些问题，我们开发了多代戒指原型，并结合基于记录手势的手指跟踪和预过滤算法对其进行优化。

The `Internet of Things' (IoT) refers to a wide variety of connected devices with build-in sensors, which collect and exchange information. Most of these objects are not equipped with dedicated user interface technology. Interaction with the IoT thus requires new interaction paradigms with ubiquitous interaction devices, devices that are seamlessly present throughout the users' daily live and not bound to any specific things.Gestures are naturally used in inter-human communication. They also represent a promising modality for interaction with the IoT as they can communicate spatial relations referring to the physical side of the IoT. Finger rings equipped with sensors are a promising basis for ubiquitous gesture detection. However, most existing sensor rings can only track the motion of one finger or are severely limited in the gestures they can recognize. Additionally, gesture recognition algorithms, if applied continuously, can easily exceed the power capacity of a battery that is small enough to be integrated in a finger ring. These disadvantages limit the applicability and utility of current sensor rings. The objective of this project is to explore and evaluate the capabilities and limits of capacitive proximity sensing for enabling multiple finger gesture recognition with a single finger ring over the whole day. For this purpose we follow a 3-fold research agenda by answering the following questions: (1) Which configuration of capacitive proximity sensing and other sensors is best suited to detect gestures and what are the limits of this technology? (2) How can the produced data streams be mapped to a skeleton hand model to enable finger tracking? (3) How far can the power usage be optimized by a prefiltering algorithm? To answer these questions we develop multiple generations of ring prototypes and optimize them in combination with the finger tracking and prefiltering algorithms based on recorded gestures.