EnsemConvNet: a deep learning approach for human activity recognition using smartphone sensors for healthcare applications

• Published in: Multimedia tools and applications Vol. 79; no. 41-42; pp. 31663 - 31690
• Main Authors: Mukherjee, Debadyuti, Mondal, Riktim, Singh, Pawan Kumar, Sarkar, Ram, Bhattacharjee, Debotosh
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.11.2020
• Subjects: Computer Communication Networks; Computer Science; Data Structures and Information Theory; Multimedia Information Systems; Special Purpose and Application-Based Systems; Classifier ensemble; EnsemConvNet; Human activity recognition; Sensor data; Time-series data

Human Activity Recognition (HAR) can be defined as the automatic prediction of the regular human activities performed in our day-to-day life, such as walking, running, cooking, performing office work, etc. It is truly beneficial in the field of medical care services, for example, personal health car...