The recent advancements in wearables, "nearables", and machine learning have paved the way for unparalleled approaches to monitoring physiological parameters. These approaches show great potential in studying human physiology during daily life as well as in extreme conditions such as astronaut monitoring and human performance. In addition, wearables and recent advances in physio-logging can alleviate the impact of numerous diseases, and medical conditions globally and, therefore have the potential to reduce the cost of healthcare and increase patients' quality of life.
Noteworthy strides have already been accomplished, evoking enthusiasm among patients and researchers alike, but very few wearable solutions have reached their anticipated potential due to many limitations such as sensor interoperability, fit/comfort/adverse reaction to wearables, lack of design standards and validation guidelines By curating an article collection that brings together explored avenues to monitor physiological parameters that did or did not work, it is anticipated that further progress in the field can be accelerated.
We welcome submissions related to, but not limited to, the following topics:
· Advances in signal processing and machine learning-based methods applied to wearable and nearable devices.
· Advances in physiological data measurements from wearable and nearable devices.
· Advances in sensor arrays for wearable and nearable devices.
· Comparison of wearable/nearable with FDA-approved devices.
· Translational technology barriers of wearables.
· Wearable devices to monitor physiological parameters during spaceflight.
· Recent advances in wearable devices in human performance.
· Application of LLM, Vit, and Foundational model in Wearable devices.
Authors are encouraged to contribute their research and findings in these areas, as well as any other related sub-topics. This article collection aims to foster collaboration and knowledge exchange to advance the development of wearables, "nearables," and machine learning techniques in biomedical applications with a unique opportunity to publish unsuccessful results to provide the research community with great insights on paths that have already been explored.
Topic Editor Dr. Mohammad Yavarimanesh is a bio-algorithm data scientist at Philips and an Adjunct Professor at the University of San Diego in San Diego, CA, USA. However, his ongoing projects are related to hospital patient monitoring and are not linked to wearable/nearable technology. Topic Editor Dr. Céderick Landry has a patent on a Method and system for cueing a user of a tool using wearables. Topic Editor Prof. Colin Drummond declares no competing interests with regard to the Research Topic subject.
The recent advancements in wearables, "nearables", and machine learning have paved the way for unparalleled approaches to monitoring physiological parameters. These approaches show great potential in studying human physiology during daily life as well as in extreme conditions such as astronaut monitoring and human performance. In addition, wearables and recent advances in physio-logging can alleviate the impact of numerous diseases, and medical conditions globally and, therefore have the potential to reduce the cost of healthcare and increase patients' quality of life.
Noteworthy strides have already been accomplished, evoking enthusiasm among patients and researchers alike, but very few wearable solutions have reached their anticipated potential due to many limitations such as sensor interoperability, fit/comfort/adverse reaction to wearables, lack of design standards and validation guidelines By curating an article collection that brings together explored avenues to monitor physiological parameters that did or did not work, it is anticipated that further progress in the field can be accelerated.
We welcome submissions related to, but not limited to, the following topics:
· Advances in signal processing and machine learning-based methods applied to wearable and nearable devices.
· Advances in physiological data measurements from wearable and nearable devices.
· Advances in sensor arrays for wearable and nearable devices.
· Comparison of wearable/nearable with FDA-approved devices.
· Translational technology barriers of wearables.
· Wearable devices to monitor physiological parameters during spaceflight.
· Recent advances in wearable devices in human performance.
· Application of LLM, Vit, and Foundational model in Wearable devices.
Authors are encouraged to contribute their research and findings in these areas, as well as any other related sub-topics. This article collection aims to foster collaboration and knowledge exchange to advance the development of wearables, "nearables," and machine learning techniques in biomedical applications with a unique opportunity to publish unsuccessful results to provide the research community with great insights on paths that have already been explored.
Topic Editor Dr. Mohammad Yavarimanesh is a bio-algorithm data scientist at Philips and an Adjunct Professor at the University of San Diego in San Diego, CA, USA. However, his ongoing projects are related to hospital patient monitoring and are not linked to wearable/nearable technology. Topic Editor Dr. Céderick Landry has a patent on a Method and system for cueing a user of a tool using wearables. Topic Editor Prof. Colin Drummond declares no competing interests with regard to the Research Topic subject.