Wearable Devices Projects for M.E, M.Tech, Masters, MS abroad, and PhD students. These Wearable Devices ieee projects are implemented with future work and extension for final year project submission with research paper publishing. These research projects guide final year students to learn, practice, and complete their academic submissions successfully. Each project includes complete source code, project report, PPT, a tutorial, documentation, and a research paper.
Latest Wearable Devices Projects
-
A Deep Learning Approach for Fear Recognition on the Edge Based on Two-Dimensional Feature Maps
This project uses wearable sensors to detect fear in real time. It analyzes body signals using artificial intelligence to identify emotions. The system can work on small devices and could help keep people safe in dangerous situations. -
A Wavelet-Based Approach for Motion Artifact Reduction in Ambulatory Seismocardiography
This project focuses on improving heart monitoring using a wearable device that measures chest vibrations. Walking and movement often create noise that makes the signals unclear. The researchers developed a new method to remove this noise and get accurate heart rate readings. This makes wearable heart monitoring more reliable for everyday use and clinical care. -
Pathological Gait Analysis With an Open-Source Cloud-Enabled Platform Empowered by Semi-Supervised Learning-PathoOpenGait
PathoOpenGait is a cloud platform that studies how people walk. It helps track walking patterns, especially for patients with Parkinson’s disease and similar disorders. The system uses 3D cameras and smart algorithms to measure walking details accurately. It is easy to use, affordable, and can be used by doctors and patients for ongoing care. -
Pulse2AI An Adaptive Framework to Standardize and Process Pulsatile Wearable Sensor Data for Clinical Applications
This project created Pulse2AI, a system that cleans and prepares wearable health signals for machine learning. It takes raw data from devices like heart rate or blood pressure monitors and makes it ready for analysis. Using Pulse2AI improved accuracy in estimating blood pressure and breathing rate. The framework works with different types of signals and can help in many remote health monitoring tasks. -
Treatment of Nocturnal Enuresis Using Miniaturised Smart Mechatronics With Artificial Intelligence
This project developed a small, wearable device called MyPAD that can track how full the bladder is and alert the user before accidents happen. It uses ultrasound sensors and smart algorithms to learn and improve over time. Tests on volunteers and models show it works with very high accuracy. The device aims to help children manage bedwetting more effectively than current methods. -
Empowering Collaborative Application Development: A Robust Framework for Ad-Hoc Distributed Systems
This project focuses on improving how devices send computing tasks to nearby servers or the cloud in real time. It uses a smart learning method called deep reinforcement learning to decide where to send tasks efficiently. The approach saves energy, reduces delays, and makes the system work more reliably. Experiments show it performs better than existing methods in most areas. -
Design of a Dual-Branch Resonator End-Launcher for Low-Loss WBAN Communications Using Wearable Waveguide Surfaces
This project develops a small, flexible device that can be built into clothing to help wearable electronics communicate wirelessly. It uses a specially designed surface in the fabric to send signals efficiently at 2.4 GHz. The device works well on the human body and leaves space for other electronics. It can operate on its own without wires or batteries. -
Human Activity Recognition Based on Wireless Electrocardiogram and Inertial Sensors
This project uses wearable sensors to monitor a person’s heart activity and body movements. It applies deep learning to identify what activity a person is doing, such as running, sitting, or climbing stairs. The system achieved very high accuracy, showing that combining heart signals and motion data gives better results. It helps in tracking health and daily activity remotely with precision.
Did you like this research project?
To get this research project Guidelines, Training and Code…