Posture Monitoring System
Current Problem
Nowadays, many people spend their time sitting at desks, in front of computers, as a result of the tasks specific to the digital era we live in. Most people do not adopt a healthy posture during this time, which leads to many spinal disorders. These include back pain, spinal deformities such as scoliosis, kyphosis, and even muscle disorders, becoming common conditions among teenagers and young adults. Additionally, a sedentary lifestyle has become one of the main causes of reduced quality of life, which is why the implementation of monitoring and posture correction systems has become necessary to offer users solutions to improve spinal health and prevent or resolve these problems.
Project Goal
The development of an IoT system for monitoring spinal posture is proposed. The main goal is to provide a solution for maintaining correct posture over long periods and proper sitting on a chair using pressure and tilt sensors. The sensors will detect incorrect positions in real time and alert the user to adjust. Additionally, with the help of an accelerometer, the device will combat sedentarism by identifying moments when the user remains in a fixed position or does not get up from the chair for a prolonged period. In such cases, the system will send notifications recommending physical activity. This system can contribute to preventing disorders and improving existing solutions.
Integrated Components and Sensors
- FSR Sensors: measure pressure applied on the seat and detect weight distribution.
- Tilt Sensor: identifies trunk tilt (hunched position).
- MPU9250 Inertial Sensor: detects lack of movement over longer periods.
Main Features
Incorrect posture detection: identifies wrong positions (tilted trunk or uneven weight distribution).
Inactivity monitoring: alerts after prolonged time without movement.
Visual notifications: messages such as "Sit up straight!" or "Move!" displayed on the interface.
Real-time graphs: acceleration and tilt visually displayed for personal analysis.
Pressure analysis on FSR sensors: visualization of weight distribution on the seat to identify unbalanced positions.
Position classification: automatic recognition of positions using an integrated machine learning algorithm.
Data Transmission and Display
All collected data are sent via Wi-Fi to a server that processes and saves them in a database. The information is displayed in real time on the web interface but can also be reviewed retrospectively for analysis or research.
Benefits
The posture monitoring system offers numerous educational and preventive benefits. By integrating multiple types of sensors, the system allows more precise detection of postural deviations, including those that might not be detected by a single sensor. Real-time visual feedback helps the user immediately correct their posture, assisting in developing healthy sitting habits. It can be easily used in various environments such as home, office, or educational institutions. It is an effective tool for preventing musculoskeletal disorders as well as for optimizing posture and supporting research processes.