Emerging wearable cortisol sensors represent a significant innovation in personalized health monitoring, allowing for detection of cortisol, a key biomarker for stress, chronic diseases, and overall well-being. Since cortisol regulates stress and met...
Traditional track and field education relies heavily on subjective assessment and manual feedback systems, creating critical barriers to personalized instruction in large-scale educational settings. This study presents a novel machine learning framew...
Flexible sensors with a porous hydrogel structure have attracted enormous attention for their extensive potential prospects in the fields of wearable electronics and human-machine interaction (HMI). Nevertheless, these sensors encounter significant c...
Laser-induced graphene (LIG) has emerged as a versatile and sustainable nanomaterial for biomedical applications, offering a unique combination of tunable surface chemistry, high electrical conductivity, mechanical flexibility, and biocompatibility. ...
Advancements in artificial intelligence have broadened the capabilities of robots, particularly in caregiving applications that are essential for aging societies facing a growing shortage of human caregivers. Humanoid caregiving robots require sophis...
BACKGROUND: Panic attack prediction remains a critical challenge in mental health care due to the high interindividual variability of physiological responses and the limitations of subjective psychological assessments.
Wearable electronic devices have brought many opportunities and hold great promise for applications in foot health monitoring. However, effective foot monitoring often requires more objective and cost-effective solutions. Here, we present a wearable ...
The challenge of providing independent living for elderly and disabled individuals is a critical societal concern. Accurate human activity recognition (HAR) is core to allow the development of context-aware applications that involve the identificatio...
BACKGROUND: Head and neck cancer (HNC) survivors face profound functional and quality-of-life deficits due to disease- and treatment-related sequelae, ranging from mild fatigue to debilitating dysphagia. Wearable technology, by monitoring biometric d...
The accurate identification of locomotion states from wearable sensor data using machine learning relies heavily on carefully selecting algorithm parameters, which remains a challenging task. This study systematically optimised key parameters-includi...
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