Deep learning algorithms for human activity recognition using mobile and wearable sensor networks: State of the art and research challenges

• Published in: Expert systems with applications Vol. 105; pp. 233 - 261
• Main Authors: Nweke, Henry Friday, Teh, Ying Wah, Al-garadi, Mohammed Ali, Alo, Uzoma Rita
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.09.2018; Elsevier BV
• Subjects: Algorithms; Artificial intelligence; Biosensors; Complexity; Computation; Deep learning; Feature extraction; Feature representation; Human activity recognition; Human behavior; Human-computer interaction; Image classification; Interactive computer systems; Mobile and wearable sensors; Older people; Rehabilitation; Review; Sensors; Wearable computers; Wearable technology; Wireless networks; Deep learning; Review; Mobile and wearable sensors; Human activity recognition; Feature representation

•Review of deep learning methods for sensor based human activity recognition.•Categorize the studies into generative, discriminative and hybrid methods.•Present training, evaluation procedures and Common datasets.•Outline open research issues presented as future directions. Human activity recognitio...