Feature Extraction and Wearable Sensors Based Patient Monitoring System
A survey on human activity recognition using wearable sensors used wired communication device. For a survey on human activity recognition using wearable sensors used wireless communication device. The recognition of human activities has been approached in two different ways, namely using external and wearable sensors. In the former, the devices are fixed in predetermined points of interest, so the inference of activities entirely depends on the voluntary interaction of the users with the sensors. In the latter, the devices are attached to the user. In the feature extraction technique, the image from the camera is feed into the system, where we use the classifiers to extract the features of the images. We use two techniques in this project, namely (i) Feed forward neural network (ii) General regression neural network. The feature extraction uses two techniques. Testing and training. In the training phase, couple of the user images are processed and updated in the system. So during the testing phase, when images are feed into the system, the system compares with the existing training data and validates the images.
Dr. A. Sahaya Anselin Nisha, S. Dhatchayini