UC Irvine

This thesis presents a new open-source framework for plotting and managing streams of sensor data on iOS devices. The framework, called the Sensor Plot Kit (SPK), aims to help developers build apps for viewing sensor data that can be streamed in real-time or pre-recorded. It can handle multiple streams at relatively high data rates with short latencies, making it suitable for advanced medical applications such as electrocardiograms (ECG). This framework also supports filtering, post processing, and saving the data in non-volatile storage. A novel feature of our design is that we adopt the Model View View-Model (MVVM) design pattern that reduces complexity and maximizes code reusability compared to the standard Model View Controller (MVC) pattern in iOS while remaining compatible. Experimental results using a real-world ECG, on-board sensors, and pre-recorded results over actual and simulated iOS devices confirm that SPK enables developers to build feature-rich, robust apps that embed real-time, responsive plotting capability while significantly shortening development time. This work has the potential to make a crosscutting impact on science, engineering, medicine, the financial market, and many other fields that increasingly rely on smart phones and tablets as the primary device for viewing and interacting live and historical streams of data.