Using wearable sensors and data analytics for disease monitoring
Using wearable sensors and data analytics for disease monitoring lead image
COVID-19 patients exhibit disease symptoms in different levels of severity. Because symptoms are inconsistent, wearable sensors become powerful tools for monitoring disease progression—especially for individuals with underlying health conditions.
Li et al. reviewed recent advances in wearable, non/minimally invasive biophysical and biochemical sensors. They also investigated the future of using data analytics and machine learning methods for preventive healthcare.
“Wearable sensors enable continuous monitoring of vital signs such as respiration rate, body temperature, blood oxygen levels, and even biochemical markers,” said author Yi Zhang. “This provides more accurate physiological information for early disease detection and ongoing infection monitoring, empowering patients to make informed decisions about seeking hospital care.”
Integrating wearable sensors into our daily lives opens a new possibility for remote healthcare, equivalent to bringing the hospital to a patient’s home. Biophysical sensors provide useful information for predicting symptoms and disease outcomes.
If the effort to make biochemical sensors non-invasive and easy to use is successful, these sensors may be combined with biophysical sensors to improve data diversity and understand disease progression at the molecular level.
In the future, the team will concentrate on creating such hybrid platforms, which would benefit from data analytics and machine learning methods. The challenge will be exploring detection techniques for biomarkers in interstitial fluids and sweat and expanding the dataset utilized by machine learning.
“These sensors have the potential to provide convenient, real-time, and precise cloud-based diagnosis, monitoring, and therapy, paving the way for an innovative approach to healthcare and helping to relieve the strain on global medical resources during pandemics,” said Zhang.
Source: “Recent advances in wearable sensors and data analytics for continuous monitoring and analysis of biomarkers and symptoms related to COVID-19,” by Huijie Li, Jianhe Yuan, Gavin Fennell, Vagif Abdulla, Ravi Nistala, Dima Dandachi, Dominic K. C. Ho, and Yi Zhang, Biophysics Reviews (2023). The article can be accessed at https://doi.org/10.1063/5.0140900 .
