A survey on wearable sensor modality centred human activity recognition in health care

Y Wang, S Cang, H Yu - Expert Systems with Applications, 2019 - Elsevier
Increased life expectancy coupled with declining birth rates is leading to an aging
population structure. Aging-caused changes, such as physical or cognitive decline, could …

Complex human activity recognition using smartphone and wrist-worn motion sensors

M Shoaib, S Bosch, OD Incel, H Scholten… - Sensors, 2016 - mdpi.com
The position of on-body motion sensors plays an important role in human activity
recognition. Most often, mobile phone sensors at the trouser pocket or an equivalent position …

[HTML][HTML] Development and clinical evaluation of a web-based upper limb home rehabilitation system using a smartwatch and machine learning model for chronic …

SH Chae, Y Kim, KS Lee, HS Park - JMIR mHealth and uHealth, 2020 - mhealth.jmir.org
Background: Recent advancements in wearable sensor technology have shown the
feasibility of remote physical therapy at home. In particular, the current COVID-19 pandemic …

Towards a diffraction-based sensing approach on human activity recognition

F Zhang, K Niu, J **ong, B **, T Gu, Y Jiang… - Proceedings of the …, 2019 - dl.acm.org
In recent years, wireless sensing has been exploited as a promising research direction for
contactless human activity recognition. However, one major issue hindering the real …

A review of sensor selection, sensor devices and sensor deployment for wearable sensor-based human activity recognition systems

H Yu, S Cang, Y Wang - 2016 10th international conference on …, 2016 - ieeexplore.ieee.org
Data preprocessing, feature selection and classification algorithms usually occupy the bulk
of surveys on human activity recognition (HAR). This paper instead gives a brief review on …

Towards detection of bad habits by fusing smartphone and smartwatch sensors

M Shoaib, S Bosch, H Scholten… - 2015 IEEE …, 2015 - ieeexplore.ieee.org
Recently, there has been a growing interest in the research community about using wrist-
worn devices, such as smartwatches for human activity recognition, since these devices are …

Mm-fit: Multimodal deep learning for automatic exercise logging across sensing devices

D Strömbäck, S Huang, V Radu - Proceedings of the ACM on Interactive …, 2020 - dl.acm.org
Fitness tracking devices have risen in popularity in recent years, but limitations in terms of
their accuracy and failure to track many common exercises presents a need for improved …

Milift: Efficient smartwatch-based workout tracking using automatic segmentation

C Shen, BJ Ho, M Srivastava - IEEE Transactions on Mobile …, 2017 - ieeexplore.ieee.org
The use of smartphones and wearables as sensing devices has created innumerable
context inference apps including a class of workout tracking apps. Workout data generated …

Recognition of nutrition intake using time-frequency decomposition in a wearable necklace using a piezoelectric sensor

N Alshurafa, H Kalantarian… - IEEE sensors …, 2015 - ieeexplore.ieee.org
Food intake levels, hydration, ingestion rate, and dietary choices are all factors known to
impact the risk of obesity. This paper presents a novel wearable system in the form of a …

Quantifying sources and types of smartwatch usage sessions

A Visuri, Z Sarsenbayeva, N Van Berkel… - Proceedings of the …, 2017 - dl.acm.org
We seek to quantify smartwatch use, and establish differences and similarities to
smartphone use. Our analysis considers use traces from 307 users that include over 2.8 …