Application and Implications

This is one of the last weeks for FabAcademy and I'm using this assignment for structuring the final project.

Motivation

Motion sickness has long been recognized as an important factor affecting a person's car riding experience. In this project, I would like to develop a bio-signal data collection and analyzation tool kit that can be further developed for predict the occurrence of motion sickness based on human physiological signals. This device will be used in a car riding environment, anyone who is likely to encounter car-sickness will be a potential user.

Idea Sketch

The figure below has shown the original idea design of this tool set.

This detection tool consists of 5 parts:

• A set of sensors for collecting human physiological signals includes PPG, SKT etc.
• A data processor module based on Raspberry Pi with Wifi connection.
• An algorithm (possibly with AI powered) for data processing which can be deployed on Raspberry Pi.
• A screen to show motion sickness dose value.
• A control panel for function selection.

After weeks of learning I have adjusted my final project design and the idea is demonstrated as below. In this new design the Tool kit is divided into two parts: A Raspberry Pi 4B Data Processing Module and A Seeed Studio ESP32C3 Bio-signal Data Collection Module.

The purchase list involved in this project is shown as table below.

Overall Techniques Applied in this Project

• Computer Aided Design - the Bio-signal Detection Module Housing
• Computer Controlled Cutting - the LOGO Sticker
• Embedded Programming - the Bio-Signal Detection Module Program and the Data Processing Program
• 3D Printing - the Housing of Bio-signal Detection Module
• Input device - Multi-biosensors
• Output device - Screen
• Electronic Design - Design Biosensor Connections to MCU
• Electronic Production - Production of PDB
• Networking and Communications - Wifi Connection between Raspberry Pi and Bio-signal Detection Module
• Interface and application programming - Demonstration of the Detected and the Analyzed Bio-signal, Using it to predict the motion sickness possibility