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Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

In recent years, oil spill pollution has become one of the main problems of environmental pollution. Recovering oil by means of sorbent materials is a very promising approach and has acquired more attention due to its high cleanup efficiency. Compared to synthetic fibrous sorbents, the use of natural fibers in oil spill cleanups offers several advantages including environmental friendliness, degradable features and cost-effectiveness. Therefore, studies on developing sorbents using natural fibers for oil spill cleanup applications have become a research hotspot.

This paper reviews the work conducted by several researchers in developing oil sorbents from fibers such as cattail, nettle, cotton, milkweed, kapok, populous seed fiber and Metaplexis japonica fiber. Some featured critical parameters influencing the oil sorption capacity of fibrous substrates are discussed. Oil sorption capacity and reusability performance of various fibers are also discussed. Recent developments in oil spill cleanups and test methods for oil sorbents are briefly covered.

The main parameters influencing the oil sorption capacity of sorbents are fiber morphological structure, fiber density (g/cc), wax (%), hollowness (%) and water contact angle. An extensive literature review showed that oil sorption capacity is highest for Metaplexis japonica fiber followed by populous seed fiber, kapok, milkweed, cotton, nettle and cattail fiber. After use, the sorbents can be buried under soil or they can also be burned so that they can be vanished from the surface without causing environmental-related issues.

This review paper aims to summarize research studies conducted related to various natural fibers for oil spill cleanups, fiber structural characteristics influencing oil sorption and recent developments in oil spill cleanups. This work will inspire future researchers with various knowledge backgrounds, particularly, from a sustainability perspective.