Week11

Week 11 Progress: Building the App Interface and State Management

Objective:

To design and implement the primary interface for the smart sock Android application using Jetpack Compose. This included setting up the BLE device list screen, live data display components, and the infrastructure for real-time state management.

Implementation:

During this week, focus was placed on two major components: the connection logic in MainActivity.kt and the UI construction within ConnectedDeviceScreen.kt. The goal was to build a responsive, functional layout that could reflect live BLE data and display relevant health status indicators.

  1. Connection Flow and UI Switching:

A reactive architecture was adopted using mutableStateOf variables such as isConnected, connectedDeviceData, and alarmStatusState. These were used to dynamically swap between the scanning screen and the connected device screen:

setContent {

    if (isConnected) {

        ConnectedDeviceScreen(...)

    } else {

        BleDeviceListScreen(...)

    }

}

  1. BLE Callbacks and Data Parsing:

In onCharacteristicChanged, composite BLE data (e.g., "MOVING,NORMAL,6380") was split into parts and stored in state variables:

val parts = compositeValue.split(",")

deviceStatusState = parts[0]

alarmStatusState = parts[1]

connectedDeviceData = (parts[2].toInt() / 100.0).toString()

This mechanism ensured that state variables instantly reflected new incoming data, triggering automatic UI updates due to Compose’s recomposition model.

  1. Chart Integration and Dynamic Plotting:

The application incorporates MPAndroidChart through the custom LineChartComponent, which reads from the reactive dataList. As connectedDeviceData changes, its value is appended to dataList, which the chart component observes to redraw the line in real-time:

LineChartComponent(dataList = dataList)

  1. Interface Composition:

The app’s screen was built using vertical Column structures, embedding Text views for status indicators and buttons for user interaction. Components were spaced with padding and aligned to maximize clarity and accessibility on small screens.



Results:

  • A fully functional and clean Compose interface was completed.

  • BLE data parsing and live status tracking were tested successfully.

  • Charts displayed historical ADC values with accurate rendering.

  • A robust architecture is now in place for integrating BLE controls and user interactions in the next phase.



Comments

Post a Comment

Popular posts from this blog

Week13

Image
Week 13 Progress: Testing Strategy Design and Simulation Objective: This week’s objective was to investigate the physiological significance of ankle swelling as a symptom of heart failure and to design a testing methodology that simulates this condition using available tools. The aim was to assess whether the current smart sock prototype could reliably detect early signs of edema through the flex sensor readings and trend detection algorithm implemented in previous weeks. Implementation: To begin with, a thorough background study was conducted on the clinical causes and relevance of ankle swelling, or  peripheral edema , especially in heart failure patients: According to the UK’s NHS website,  oedema  occurs when excess fluid builds up in body tissues, often affecting the ankles and feet. It’s particularly common among elderly or sedentary individuals and can be a sign of more serious conditions like  heart failure  or kidney problems【NHS†source】. HeartFailureMa...
Read more

Week9

Image
Week 9 Progress: State Machine Design and System Modularity Objective To modularize the ankle monitoring code by implementing a two-state state machine (MOVING / STATIONARY) to detect whether the user is currently in motion or in a stable position for trend detection. The goal is to trigger alarm conditions only when reliable stationary measurements are available. Implementation: State Machine Architecture The firmware now uses a simple finite state machine (FSM) with two primary states: MOVING : The user is moving, sensor data fluctuates significantly, and trend evaluation is temporarily disabled. STATIONARY : The user is still. Trend data is collected to determine if ankle swelling is occurring. 📌 Transition Logic: Transition from MOVING → STATIONARY happens when sensor variation over a defined window is small (low deviation). Transition from STATIONARY → MOVING happens when at least 3 significantly different readings appear within the window (indicating movement or p...
Read more

Week1

Image
Week 1 Progress: System Testing and Redesign Planning During the first two weeks of the project, my main task was to test the previous prototype and develop improvement plans based on its performance. The system consists of two main parts: a wristband and an anklet module. As shown in the figure, the wristband worked relatively well. Once worn, it was able to accurately display heart rate and blood oxygen levels, although the SpO₂ readings occasionally showed inconsistencies. In contrast, the anklet system had several issues. It frequently produced errors during testing and often triggered false alarms when tested with a 3D-printed cone-shaped object. Additionally, the circuit design was overly complex and bulky, making it uncomfortable to wear.
Read more