Human Activity Recognition (HAR) in Healthcare
Source abstract
Abstract
Developments in the medical and technological fields have led to a longer life expectancy [...]
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: Context-Aware Activity Recognition Systems · Healthcare Technology and Patient Monitoring · Anomaly Detection Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
BioRobotics Lab, Department of Industrial Engineering, University of Florence, 50134 Florence, Italy
Department of Electrical Engineering, Pontifical Catholic University of Rio de Janeiro, Rio de Janeiro 22451-000, Brazil
References (18)
Show source-provided references
1. (2021, July 08). Un’indagine Sugli Anziani non Autosufficienti: Le Scelte delle Famiglie tra Assistenza Domiciliare e RSA. I Luoghi della Cura Rivista Online Network Non Autosufficienza (NNA). Available online: https://www.luoghicura.it/dati-e-tendenze/2022/11.
2. Bibbo, L., Carotenuto, R., Corte, F.D., Merenda, M., and Messina, G. (2022, January 19). Home care system for the elderly and pathological conditions. Proceedings of the 7th International Conference on Smart and Sustainable Technologies (SpliTech), Split/Bol, Croatia.10.23919/SpliTech55088.2022.9854252 ↗
3. Artificial intelligence and ambient intelligence10.3233/AIS-180508 ↗
4. Cicirelli, G., Marani, R., Petitti, A., Milella, A., and D’Orazio, T. (2021). Ambient Assisted Living: A Review of Technologies, Methodologies and Future Perspectives for Healthy Aging of Population. Sensors, 21.10.3390/s21103549 ↗
5. Robust Human Activity Recognition using smartwatches and smartphones
6. Şahin, E., Yavuz Veizi, B.G., and Naharci, M.I. (2021). Telemedicine interventions for older adults: A systematic review. J. Telemed. Telecare.10.1177/1357633X211058340 ↗
7. Design recommendations for socially assistive robots for health and social care based on a large-scale analysis of stakeholder positions: Social robot design recommendations10.1016/j.hlpt.2021.100544 ↗
8. Human activity recognition using wearable sensors, discriminant analysis, and long short-term memory-based neural structured learning10.1038/s41598-021-95947-y ↗
9. A systematic review of smartphone-based human activity recognition methods for health research10.1038/s41746-021-00514-4 ↗
10. A Review of Deep Learning-based Human Activity Recognition on Benchmark Video Datasets10.1080/08839514.2022.2093705 ↗
11. Human Activity Recognition using Inertial, Physiological and Environmental Sensors: A Comprehensive Survey10.1109/ACCESS.2020.3037715 ↗
12. MLP-Mixer: An all-MLP architecture for vision
13. Brachman, R.J., and Arnad, T. (August, January 31). The Process of Knowledge Discovery in Databases: A First Sketch. Proceedings of the 1994 {AAAI} Workshop, Seattle, WA, USA. Technical Report {WS-94-03}.
14. Weiss, G.M. (2021, July 08). UCI Machine Learning Repository: WISDM Smartphone and Smartwatch Activity and Biometrics Dataset. Available online: https://archive.ics.uci.edu/ml/machine-learning-databases/00507/WISDM-dataset-description.pdf.
15. Ohashi, H., Al-Nasser, M., Ahmed, S., Akiyama, T., Sato, T., Nguyen, P., Nakamura, K., and Dengel, A. (2017, January 6–11). Augmenting wearable sensor data with physical constraint for DNN-based human-action recognition. Proceedings of the ICML 2017 Times Series Workshop, Sydney, NSW, Australia.
16. Fridriksdottir, E., and Bonomi, A.G. (2020). Accelerometer-based human activity recognition for patient monitoring using a deep neural network. Sensors, 20.10.3390/s20226424 ↗
17. Ball, M. (2022). The Metaverse: And How it Will Revolutionize Everything, W.W. Norton & CO.
18. Artificial Intelligence (AI) Ethics: Ethics of AI and Ethical AI10.4018/JDM.2020040105 ↗