Wearable microfluidic-based e-skin sweat sensors. Issue 14 (18th March 2022) - Tabasum, Humairah; Gill, Nikita; Mishra, Rahul; Lone, Saifullah
Abstract : Electronic skins are soft wearable devices that emulate attributes of human skin and act as a human–machine interface for early prediction and real-time monitoring of disease. Abstract : Electronic skins (e-skins) are soft (deformable and stretchable) state-of-the-art wearable devices that emulate the attributes of human skin and act as a Human–Machine Interface (HMI). Recent advances in e-skin for real-time detection of medical signals such as pulse, temperature, electromyogram (EMG), electroencephalogram (EEG), electrooculogram (EOG), electrocardiogram (ECG), and other bioelectric signals laid down an intelligent foundation for early prediction and diagnosis of diseases with a motive of reducing the risk of the ailment reaching to the end stage. In particular, sweat testing has been employed in diverse applications ranging from medical diagnosis of diabetes, cystic fibrosis, tuberculosis, blood pressure, and autonomic neuropathy to evaluating fluid and electrolyte balance in athletes. Typically, sweat testing techniques are done by trained experts and require off-body measurements, which prevent individuals from de-coding health issues quickly and independently. With the onset of soft electronics, wearable sweat sensors overcome this disadvantage via in situ sweat measurements with real-time feedback, timely diagnosis, creating the potential for preventive care and treatment. Over the past few decades, wearable microfluidic-based e-skin sweat sensors have paved a new way, promising sensing interfaces that are highly compatible with arranging medical and electronic applications. The present review highlights the recent research carried out in the microfluidic-based wearable sweat sensors with a critical focus on real-time sensing of lactate, chloride, and glucose concentration; sweat rate, simultaneously with pH, and total sweat loss for preventive care, timely diagnosis, and point-of-care health and fitness monitoring.