Review on the wearable health-care monitoring system with robust motion artifacts reduction techniques

Purpose 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. Design/methodology/approach 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. Findings According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems. Originality/value 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.

Smart Healthcare Monitoring System for War-End Soldiers Using CNN

Health monitoring plays a vital role to overcome the health issues of the patients. According to research, approximately 2000 people die due to carelessness of monitoring their health. Wearable monitoring systems record the activities of daily life. A 24-hour wearable monitoring system was developed and changes were identified. This project is designed for helping the soldiers to maintain their health conditions and to identify their health issues at war's end. Different health parameters are monitored using sensors, and the data are transmitted through GSM to the receiver, and the received data are analyzed using convolutional neural networks, which is performed in cloud IoT. If any abnormalities are found during the analyzing process, the message is sent to military personnel and the doctor at the camp so that they could take necessary actions to recover the ill soldier from the war field and provide emergency assistance on time. The location of the soldier is also shared using the input from GPS modem in the smart jacket.

Smart Healthcare Monitoring System for War-End Soldiers Using CNN

Health monitoring plays a vital role to overcome the health issues of the patients. According to research, approximately 2000 people die due to carelessness of monitoring their health. Wearable monitoring systems record the activities of daily life. A 24-hour wearable monitoring system was developed and changes were identified. This project is designed for helping the soldiers to maintain their health conditions and to identify their health issues at war's end. Different health parameters are monitored using sensors, and the data are transmitted through GSM to the receiver, and the received data are analyzed using convolutional neural networks, which is performed in cloud IoT. If any abnormalities are found during the analyzing process, the message is sent to military personnel and the doctor at the camp so that they could take necessary actions to recover the ill soldier from the war field and provide emergency assistance on time. The location of the soldier is also shared using the input from GPS modem in the smart jacket.

The Role of Wearable Monitor for Healthcare

Wearable monitor for healthcare was proposed in the late 1990s. Physiological monitoring in daily life has considerable potential for preventing and predicting diseases, without significant discomfort or inconvenience to the user. Over the past 25 years, wearable monitoring systems have been developed for health monitoring in daily life. In this presentation we will 1) review the devices used in wearable monitoring, including home use and clinical practice; 2) consider the evidence for their benefit in terms of healthcare outcomes; and 3) discuss long-term data collection and analysis using Big Data techniques. Furthermore, issues relating to the popularization of these devices are discussed, including regulation and business models. There are many promising devices available for wearable healthcare monitoring, and we propose ideas to popularize these devices.