Wearable Sensor for Activity Analysis and Context Recognition
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (31 May 2021) | Viewed by 47307
Special Issue Editors
Interests: wearable robotics; physical human robot interaction; robotics
Interests: robot control; rehabilitation robbots; wearable robots; underactuted robotics; mobile robots; robotic manipulation
Interests: biomechatronics; wearable systems; instrumentation; assistive technology; signal fusion; biorobotics
Special Issue Information
Dear Colleagues,
Active participation of the dependent population in society has become an important challenge from both societal and economic viewpoints as this population is constantly increasing. Assisting with the daily activities would enhance personal safety, well-being, and autonomy while reducing health care costs. The dependent population requires continuous monitoring to detect abnormal situations or prevent unpredictable events such as falls. Thus, the problem of human activity recognition is central for understanding and predicting human behavior, in particular to provide assistive services to humans, such as health monitoring, well-being, security, etc. The last decade has shown an increasing interest in the development of wearable technologies for physical and cognitive assistance and rehabilitation purposes. For instance, the rapid development of microsystems technology has contributed to the development of small, lightweight, and inexpensive wearable sensors. This has provided users with a means to improve early stage detection of pathologies while reducing the overall costs compared with more intrusive standard diagnostic methods. Recent advances in the fields of machine learning and deep learning technologies have opened new and exciting research paradigms to construct end-to-end learning models from complex data in the health care domain. These new learning techniques can be also used for translating wearable biomedical data into improved human health.
Despite this vast potential, the majority of the wearables today remain limited to simple metrics (e.g., step counts, heart rate, calories, etc.); detailed health and/or physiological instrumentation for machine interface have yet been implemented. A staggering one-third of users are reported to abandon commercial devices in regular use, which indicates transience and sustainability. Sensor development, embedded systems, and cloud connectivity enable an evolution from a device to a systems perspective, which demands recognition that sensors, learning algorithms, and devices linking wearables to humans (e.g. robotic assist) are fundamentally coupled, and hence should be treated as an integrated whole.
The Special Issue seeks to publish original investigations aimed at closing this gap. We invite papers presenting significant advances with respect to the state-of-the-art development in the following topics, which include, but are not limited to:
- Daily living activity recognition using wearable sensors;
- Learning techniques for health care application using wearable devices;
- Human assistance using smart spaces;
- Design and control of wearable robot for health care applications;
- Human-in-the-loop-optimization algorithms for assistive purposes using wearable devices;
- Neuro-robotics paradigm for wearable assistive technologies;
- Recent development and trends in wearable clinical rehabilitation techniques;
- Motion control and fall detection using wearable devices;
- Ethical, legal, and social issues of wearable devices.
Prof. Dr. Samer MohammedProf. Dr. Jian Huang
Prof. Dr. Ravi Vaidyanathan
Guest Editors
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