Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper firstly introduces common wearable sensors, smart wearable devices and the key
application areas. Since multi-sensor is defined by the presence of more than one model or …
application areas. Since multi-sensor is defined by the presence of more than one model or …
Artificial intelligence and machine learning for improving glycemic control in diabetes: Best practices, pitfalls, and opportunities
Objective: Artificial intelligence and machine learning are transforming many fields including
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …
medicine. In diabetes, robust biosensing technologies and automated insulin delivery …
Enhancing self-management in type 1 diabetes with wearables and deep learning
People living with type 1 diabetes (T1D) require lifelong self-management to maintain
glucose levels in a safe range. Failure to do so can lead to adverse glycemic events with …
glucose levels in a safe range. Failure to do so can lead to adverse glycemic events with …
[HTML][HTML] Deep learning in mHealth for cardiovascular disease, diabetes, and cancer: systematic review
Background: Major chronic diseases such as cardiovascular disease (CVD), diabetes, and
cancer impose a significant burden on people and health care systems around the globe …
cancer impose a significant burden on people and health care systems around the globe …
[HTML][HTML] Overview of artificial intelligence–driven wearable devices for diabetes: sco** review
Background Prevalence of diabetes has steadily increased over the last few decades with
1.5 million deaths reported in 2012 alone. Traditionally, analyzing patients with diabetes has …
1.5 million deaths reported in 2012 alone. Traditionally, analyzing patients with diabetes has …
Physical activity and psychological stress detection and assessment of their effects on glucose concentration predictions in diabetes management
Objective: Continuous glucose monitoring (CGM) enables prediction of the future glucose
concentration (GC) trajectory for making informed diabetes management decisions. The …
concentration (GC) trajectory for making informed diabetes management decisions. The …
[HTML][HTML] Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data
Abstract Introduction Diabetes Mellitus (DM) is characterized by impaired ability to
metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia) …
metabolize glucose for use in cells for energy, resulting in high blood sugar (hyperglycemia) …
The role of wearable devices in chronic disease monitoring and patient care: a comprehensive review
EA Jafleh, FA Alnaqbi, HA Almaeeni, S Faqeeh… - Cureus, 2024 - pmc.ncbi.nlm.nih.gov
Wearable health devices are becoming vital in chronic disease management because they
offer real-time monitoring and personalized care. This review explores their effectiveness …
offer real-time monitoring and personalized care. This review explores their effectiveness …
Detection and classification of unannounced physical activities and acute psychological stress events for interventions in diabetes treatment
Detection and classification of acute psychological stress (APS) and physical activity (PA) in
daily lives of people with chronic diseases can provide precision medicine for the treatment …
daily lives of people with chronic diseases can provide precision medicine for the treatment …
[HTML][HTML] Data analytics in physical activity studies with accelerometers: sco** review
YT Liang, C Wang, CK Hsiao - Journal of medical Internet research, 2024 - jmir.org
Background Monitoring free-living physical activity (PA) through wearable devices enables
the real-time assessment of activity features associated with health outcomes and provision …
the real-time assessment of activity features associated with health outcomes and provision …