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Active Sense Wordmark Active Sense Wordmark

ActiveSense

ActiveSense is a wearable application for activity tracking and recognition developed at RheinMain University of Applied Sciences. Designed to streamline caregiving workflows and provide detailed insights into patient activities, ActiveSense leverages modern sensor data and machine learning models to monitor and classify physical activity in real-time.

How ActiveSense Works

ActiveSense is built with the goal of enhancing the quality of care for patients while improving efficiency for caregivers. By wearing the ActiveSense smartwatch, patients' movements and activities are continuously tracked. This real-time monitoring offers caregivers a clear and detailed view of daily activities, which can inform personalized care plans and improve patient outcomes.

System Context Diagram

Here’s a high-level overview of how the system functions:

  1. Pairing and Initialization: After the initial setup and pairing process, the smartwatch begins capturing data from a predefined set of sensors.
  2. Data Transmission: The sensor data is sent to the backend services where it is initially stored in a database.
  3. Data Processing: The stored sensor values are processed into feature vectors, which are the input for machine learning models.
  4. Activity Classification: One or more ML models classify the activity the wearer is currently performing, providing actionable insights for caregivers.

This system not only helps monitor physical activities but also lays the groundwork for future functionalities, such as detecting anomalies or potential health risks based on activity patterns.

Documentation Overview

The documentation for ActiveSense is structured into two main sections, each catering to a specific audience:

  1. MKDocs Documentation: This is the documentation you’re currently viewing. It provides high-level insights into key concepts, such as how the communication between the smartwatch and the server works, system architecture, and the overall functionality of the app.

  2. Dokka Documentation: Found under the “Reference” tab, this section is automatically generated from the source code and serves as the API specification. It’s intended for developers and provides more granular information about specific components and functions within ActiveSense.

Getting Started with Development

If you’re interested in contributing to the development of ActiveSense, that’s great! Here’s a quick guide to getting started.

Prerequisites

Before diving into development, ensure you have the following tools installed:

  1. IntelliJ IDEA with the Android Plugin or Android Studio to build, run, and test the app.
  2. Familiarity with Android development, Kotlin, and WearOS is recommended.
  3. Basic understanding of WebSocket communication, as it's used extensively within the app for real-time data transfer.

Installation

Follow these steps to set up the development environment:

  1. Clone the ActiveSense repository: 

    git clone https://gitlab.cs.hs-rm.de/some-org/ActiveSense.git

  2. Open the project in IntelliJ or Android Studio.

  3. Sync Gradle to ensure all dependencies are installed.

  4. Connect your WearOS device or emulator to begin testing.

Reporting Issues

Found a bug or have a feature request? Please open an issue on the GitLab repository with detailed information so we can address it promptly.

ActiveSense is an ongoing project with a mission to improve patient care and caregiver efficiency. Your contributions and feedback are crucial to its success.

Feel free to reach out if you have any questions or suggestions. Happy coding!