Sensors (Basel, Switzerland), 2022-02, Vol.22 (4), p.1476
2022
Details
- Autor(en) / Beteiligte
- Titel
- Deep Learning in Human Activity Recognition with Wearable Sensors: A Review on Advances
- Ist Teil von
- Sensors (Basel, Switzerland), 2022-02, Vol.22 (4), p.1476
- Ort / Verlag
- Switzerland: MDPI AG
- Erscheinungsjahr
- 2022
- Link zum Volltext
- Quelle
- Free E-Journal (出版社公開部分のみ）
- Beschreibungen/Notizen
- Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human-computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the rich collection of low-power sensors found in many mobile and wearable devices to perform human activity recognition (HAR). Recently, deep learning has greatly pushed the boundaries of HAR on mobile and wearable devices. This paper systematically categorizes and summarizes existing work that introduces deep learning methods for wearables-based HAR and provides a comprehensive analysis of the current advancements, developing trends, and major challenges. We also present cutting-edge frontiers and future directions for deep learning-based HAR.
- Sprache
- Englisch
- Identifikatoren
- ISSN: 1424-8220eISSN: 1424-8220DOI: 10.3390/s22041476Titel-ID: cdi_doaj_primary_oai_doaj_org_article_d840901d624a4fde972fc3373097c100
- Format
- –
- Schlagworte
- Activities of daily living, Algorithms, Automobile industry, Computational linguistics, Computer network equipment industry, Datasets, Deep Learning, Health aspects, Human Activities, Human activity recognition, Human-computer interaction, Humans, Keywords, Language processing, Moving object recognition, Natural language interfaces, Neural networks, pervasive computing, Physiology, Review, Sensors, Smartwatches, Systematic review, ubiquitous computing, Wearable computers, Wearable Electronic Devices, wearable sensors, Wearable technology