Human activity recognition using machine learning methods in a smart healthcare environment

A Subasi, K Khateeb, T Brahimi, A Sarirete - Innovation in health informatics, 2020 - Elsevier
The rapid developments in information and communication technologies and wireless
communication networks have led to the utilization of the smart sensors. In modern …

Exploring user expectations of proactive AI systems

C Meurisch, CA Mihale-Wilson, A Hawlitschek… - Proceedings of the …, 2020 - dl.acm.org
Recent advances in artificial intelligence (AI) enabled digital assistants to evolve towards
proactive user support. However, expectations as to when and to what extent assistants …

Deep Learning‐Based Skin Diseases Classification using Smartphones

I Oztel, G Yolcu Oztel, VH Sahin - Advanced Intelligent Systems, 2023 - Wiley Online Library
Skin disease recognition is one of the essential topics in the medical industry. Detecting skin
disease from appearance can be difficult due to the similar appearance of skin lesions. In …

Internet of things for ambient assisted living: challenges and future opportunities

J Wan, X Gu, L Chen, J Wang - 2017 International conference …, 2017 - ieeexplore.ieee.org
As the age profile of many societies continues to increase, supporting health, both mental
and physical, is of increasing importance if independent living is to be maintained. Sensing …

Polaris: Probabilistic and ontological activity recognition in smart-homes

G Civitarese, T Sztyler, D Riboni… - … on Knowledge and …, 2019 - ieeexplore.ieee.org
Recognition of activities of daily living (ADLs) is an enabling technology for several
ubiquitous computing applications. Most activity recognition systems rely on supervised …

Evaluating the interplay between trajectory segmentation and mode inference error

G Kosmacher, K Shankari - Transportation research record, 2024 - journals.sagepub.com
Travel behavior changes are essential to transportation decarbonization. Travel diaries,
consisting of sequences of trips between places, are typically used to instrument human …

WOODY: a post-process method for smartphone-based activity recognition

C Wang, Y Xu, H Liang, W Huang, L Zhang - IEEE Access, 2018 - ieeexplore.ieee.org
In the past decade, the rapid popularization of smartphone has provided a promising
direction for human activity recognition. Despite identifying a variety of movements without …

HANDY: A benchmark dataset for context-awareness via wrist-worn motion sensors

K Açıcı, ÇB Erdaş, T Aşuroğlu, H Oğul - Data, 2018 - mdpi.com
Being aware of a personal context is a promising task for various applications, such as
biometry, human-computer interactions, telemonitoring, remote care, mobile marketing and …

Unsupervised classification of smartphone activities signals using wavelet packet transform and half-cosine fuzzy clustering

H He, Y Tan, J Huang - 2017 IEEE International Conference on …, 2017 - ieeexplore.ieee.org
Activity recognition using smartphone provides a ubiquitous and unobtrusive way for people
to realize health monitor and ambient assisted living. Since human activities has …

W-trans: A weighted transition matrix learning algorithm for the sensor-based human activity recognition

C Wang, B Wang, H Liang, J Zhang, W Huang… - IEEE …, 2020 - ieeexplore.ieee.org
The sensor-based human activity recognition has been wildly applied in behavior tracking,
health monitoring, indoor localization etc. Using activity continuity to assist activity …