## 4 Concept of a DAid(r) Smart Socks-Based Biofeedback System
### System Requirements for the Concept of DAid\({}^{\otimes}\) Smart Socks-Based Biofedback System  
The smart socks are equipped with pressure sensors on both legs, each transmitting data via Bluetooth over two separate channels to a computer or other processing device. Each sensor package contains 3-4 data points, including metrics such as plantar pressure  
Figure 4: Component diagram for the biofeedback system application.  
Figure 5: System architecture of the biofeedback system.  
distribution and other key movement indicators. Sensor data are transferred over Bluetooth to the server.  
Once the sensor data are received by the application, they are processed in real time and then transmitted to the Meta Quest 3 HMD over a Wi-Fi connection. This allows the user to receive immersive feedback through MR, enabling them to adjust their movements based on the system's real-time analysis. The combination of Bluetooth for sensor data and Wi-Fi for MR streaming provides a balance between the need for low-latency, high-speed data transmission and power efficiency.  
Requirements for the First Prototype--Minimal Viable Product (MVP) of DAid\({}^{\text{\text{\textregistered}}}\) Smart Socks-Based Biofeedback System  
A Minimal Viable Product has been created that consists of three components: server, client, and DAid\({}^{\text{\textregistered}}\) smart socks. The MPV architecture is presented in Figure 6.  
There are six steps in the MVP system architecture:  
1. Command to Start Data Flow: The system sends an initial command to the sensor socks to activate data transmission, initiating the flow of sensor data.
2. Sending Data from the DAid\({}^{\text{\textregistered}}\) Smart Socks: Data received continuously from the DAid\({}^{\text{\textregistered}}\) smart socks, maintaining an ongoing communication loop.
3. Data Reception and Processing: The system receives raw data packets from the socks, converts them into numerical values, normalizes the data, writes sensor-specific information to a CSV file, and computes real-time center of pressure (COP) coordinates (x, y).
4. User Input Commands: The user interacts with the system commands via terminal sending such as \"connect\", \"calibrate\", and \"start\" enabling connection to the socks, calibration of the sensors, and initiation of data collection.
5. Command to Start Receiving Data: A specific command is issued to the server to begin receiving and processing sensor data from the socks.
6. Sending COP Data to Client: The processed COP data are transmitted to the client side, where they are displayed on the terminal in real time for monitoring and feedback.  
The system must support a data sampling rate of 200 Hz, ensuring that the sensor data are collected frequently enough to provide a smooth and accurate reflection of foot pressure and movement changes. Data transmission from the sensors occurs 10-15 times per second, and a 1 MB buffer is recommended for managing the incoming data streams efficiently. This buffer uses a circular data handling approach, preventing data loss or overflow during periods of intense data transmission.  
Figure 6: MVP system architecture of the biofeedback system.  
Regarding hardware requirements, the application requires a multi-core processor with at least four cores and 8 GB of RAM (with 16 GB being ideal) to handle the data analysis and multiple data streams. The system also needs to maintain a feedback latency of less than 100 ms to ensure that users receive actionable feedback promptly.