Disorders of the heart and blood vessels are the leading cause of health problems and death. Early detection of them is extremely valuable as it can prevent serious incidents (e.g. heart attack, stroke) and associated complications. This requires extending the typical mobile monitoring methods (e.g. Holter ECG, tele-ECG) by introduction of integrated, multiparametric solutions for continuous monitoring of the cardiovascular system.
In this paper we propose the wearable system that integrates measurements of cardiac data with actual estimation of the cardiovascular risk level. It consists of two wirelessly connected devices, one designed in the form of a necklace, the another one in the form of a bracelet (wrist watch). These devices enable continuous measurement of electrocardiographic, plethysmographic (impedance-based and optical-based) and accelerometric signals. Collected signals and calculated parameters indicate the electrical and mechanical state of the heart and are processed to estimate a risk level. Depending on the risk level an appropriate alert is triggered and transmitted to predefined users (e.g. emergency departments, the family doctor, etc.).
This article presents a wearable system that localizes people in the indoor environment, using data from inertial sensors. The sensors measure the parameters of human motion, tracking the movements of the torso and foot. For this purpose, they were integrated with shirt and the shoe insole. The values of acceleration measured by the sensors are sent via Bluetooth to a smartphone. The localization algorithm implemented on the smartphone, presented here, merges data from the shirt and the shoe to track the steps made by the user and filter out the localization errors caused by movements the shirt and torso. The experimental verification of the algorithm is also presented.
In this paper, an autonomous wearable sensor node is developed for long-term continuous healthcare monitoring. This node is used to monitor the body temperature and heart rate of a human through a mobile application. Thus, it includes a temperature sensor, a heart pulse sensor, a low-power microcontroller, and a Bluetooth low energy (BLE) module. The power supply of the node is a lithium-ion rechargeable battery, but this battery has a limited lifetime. Therefore, a photovoltaic (PV) energy harvesting system is proposed to prolong the battery lifetime of the sensor node. The PV energy harvesting system consists of a flexible photovoltaic panel, and a charging controller. This PV energy harvesting system is practically tested outdoor under lighting intensity of 1000 W/m2. Experimentally, the overall power consumption of the node is 4.97 mW and its lifetime about 246 hours in active-sleep mode. Finally, the experimental results demonstrate long-term and sustainable operation for the wearable sensor node.