According to the World Health Organization (WHO), health is a state of being in which one feels physical, mental, and social well-being, rather than simply the absence of sickness. Despite the fact that diseases such as cardiovascular disease (CVDs), neurodegenerative disorders, diabetes, and cancer are among the top causes of death and morbidity, the beginning and origin of these diseases is frequently disputed. Such diseases have very minor or no symptoms in their early stages. As a result, it's critical to recognize early signs of stress, such as changes in physiological parameters, and to encourage people to live a healthier lifestyle. Such longitudinal physical, physiological and biochemical data, in their daily living conditions, can be best captured using wearable sensors in a non-intrusive way.
For example, high-risk groups could be screened and/or followed for particular biomarkers on a regular basis, possibly 24 hours a day, utilizing unobtrusive and non-invasive wearable sensors. The goal of this monitoring effort would be to find early biomarkers in physical (e.g., activity monitoring by accelerometry or inertial measurement unit), physiological (e.g., heart rate(HR), HR Variability, breathing rate, oxygen saturation) and biochemical profile that can be used for (i) nudging so-called healthy people to change their lifestyle and improve their wellness and (ii) assisting clinicians by providing objective measures of patients' condition in their daily living scenario. The challenges of this approach include design of non-invasive sensors for user-friendly and unobtrusive wearables, handling the noisy sensor data obtained in uncontrolled environment, performing multi-sensor fusion for reliable inferences and AI based analytics on longitudinal sensor data.
As a whole, this longitudinal monitoring could lead to the creation of a digital human (e.g., virtual coach or companion) who can recognize physical, mental, and social well-being, and provide support as a caregiver or provide patient vitals to clinicians for early decision making and timely therapeutics. Aiming at accelerating the research on wearable sensors, this Research Topic welcomes review papers and original research on the following themes but is not limited to them:
- Wearables in neurorehabilitation (e.g. virtual companion for neurological diseases)
- Wearables monitoring for memory loss, mild cognitive impairments, mental stress
- Wearable for monitoring daily activity, ambient assisted leaving (AAL), wellness and improving lifestyle
- Wearable in infection diseases (e.g. COVID19)
- Wearable as biomarkers for monitoring physical, physiological and biochemical subject profiles (near body, on body, in body)
- Algorithms (AI, non-AI) used in wearable for personalized and non-personalized physical, physiological and biochemical measurements
- Wearables in fitness and sports (near body, on body, in body)
- Wearables for entertainment and gamification
Topic Editor Aniruddha Sinha is employed by TCS Research and Innovation and holds multiple patents. The other Topic Editors declare no competing interests with regard to the Research Topic subject.We would like to acknowledge Dr Avik Ghose who has acted as coordinator and has contributed to the preparation of the proposal for this Research Topic.