Celso P. Figueiredo

Low power wireless acquisition module for wearable health monitoring systems

This paper presents a low power wireless acquisition module for use within wearable health monitoring systems and Ambient Assisted Living applications. The acquisition module provides continuous monitoring of the users electrocardiogram (ECG) and activity, as well as the local temperature at the module. The module is placed on the chest of the user, and its wearability is achieved due to its fabrication based on a flexible PCB, and by the complete absence of connecting wires, as a result of the integration of flexible and dry ECG monitoring electrodes on the acquisition module, which do not require preparation with electrolyte gel. The design of the acquisition module also aimed for the minimization of power consumption to enable long-term continuous monitoring, namely concerning the wireless link, for which a proprietary low power solution was adopted. A low power analog frontend was custom designed for single-lead ECG monitoring, achieving a current consumption of 220 εA. The wireless acquisition module has a current consumption down to 1.3 mA while processing the acquisition of sensor data, and 4 mA when the wireless transceiver is active.

Design and realization of a wireless sensor gateway for health monitoring

This paper describes the design and realization of a wireless sensor gateway (WSG) within a wireless sensor network (WSN) for health monitoring. The WSN allows recording and wireless transmission of biosignals, namely the electrocardiogram, pulse wave and body weight, which are important parameters for cardiovascular monitoring. These can be displayed, analysed, and saved on the WSG through a user interface based on a touch screen. The proposed WSG has the distinctive feature of using two different radio transceivers, exploiting the advantages of each device. Currently, most personal computers and handhelds have standardized Bluetooth interfaces (IEEE 802.15.1) but not ZigBee interfaces (IEEE 802.15.4). Hence, the proposed gateway is designed to receive data from wireless sensors through its ZigBee interface and to forward them to a personal computer via its Bluetooth interface. This feature, combined with simple touch screen menu navigation will reach increased patient compliance and consequently increased benefit for patient in terms of healthcare and safety.

Autonomy Suitability of Wireless Modules for Ambient Assisted Living Applications: WiFi, Zigbee, and Proprietary Devices

Ambient Assisted Living is pushing the development of innovative wireless monitoring solutions. Most of the available solutions are based on well known wireless communication standards, such as Wi-Fi, Bluetooth or ZigBee. Moreover, there are also a few proprietary solutions, including those designed specifically for biomedical monitoring applications. The success of those solutions depends on many factors, and power autonomy is one key issue, since system recharging requires the user to temporarily remove the device. In this paper, we evaluate the autonomy of three different wireless modules, proposed for use on Ambient Assisted Living applications. We present the measured and expected autonomy for modules built from off-the-shelf components to assess its suitability for real scenario applications. From the results, it is evident that may be worthless to design extremely low power acquisition electronics, sacrificing the acquisition performance, when the main power consumption comes from the wireless subsystem that, which is one order of magnitude higher.

Towards a Reconfigurable Wireless Sensor Network for Biomedical Applications

This work presents a study on the reconfiguration requirements of wireless sensor network for biomedical applications. It is presented a wireless platform operating in a smart suit, the required monitored parameters and possible monitoring scenarios. The smart suit is currently used only for one scenario, which consists of monitoring handicapped people, with all physiological data being collected and routed to a base station. We propose using the smart suit for different scenarios, such as a patient requiring emergency medical care. The goal is to use the sensorial network in the suit to monitor his health condition, so that the cardio-respiratory rhythm, body temperature, and arterial pressure data can be used to help the diagnostic. We state that this network can be used if reconfigured correctly. This paper also shows that sensors here in use should control external high resolution ADCs using hardware interruptions instead of software interruptions.

A Wireless System for Biopotential Acquisition: an Approach for non-Invasive Brain-Computer Interface

Brain-computer interfaces (BCI) promise to be a very important tool for the handicapped people in the near future. A wireless biopotential acquisition system is proposed as a solution for true mobility during non-invasive BCI operation. Special care about noise must be taken in a signal acquisition system for biopotentials. The EEG signal amplitude ranges from a few to dozens of micro-volts and it is very low compared with the interference from mains power. Thus, a good quality signal requires an efficient interference removal. The wireless system is operating at 2.4 GHz, the maximum data throughput is 120 Kbps, the system resolution is about 4 muV, the power consumption is 0.015 W and accommodates 5 single-ended channels. The dimensions of the wireless acquisition system are approximately 5.7times4.8times2.0 cm3.

3D electrode localization on wireless sensor networks for wearable BCI

This paper presents a solution for electrode localization on wearable BCI radio-enabled electrodes. Electrode positioning is a common issue in any electrical physiological recording. Although wireless node localization is a very active research topic, a precise method with few centimeters of range and a resolution in the order of millimeters is still to be found, since far-field measurements are very prone to error. The calculation of 3D coordinates for each electrode is based on anchorless range-based localization algorithms such as Multidimensional Scaling and Self-Positioning Algorithm. The implemented solution relies on the association of a small antenna to measure the magnetic field and a microcontroller to each electrode, which will be part of the wireless sensor network module. The implemented solution is suitable for EEG applications, namely the wearable BCI, with expected range of 20 cm and resolution of 5 mm.

Multifunction antenna for compact wireless electrophysiological monitoring devices

This paper shows an antenna solution for use on electrophysiological monitoring devices with three different purposes. It may be used for wireless communications, wireless charging, and as an electrode or on top of it.

Electrode Localization in a Self-organizing Network for Electrophysiological Diagnostics

This paper presents a solution to provide electrode localization in electrophysiological diagnostics. A system concept was developed based on a network of active and intelligent electrodes which can cooperate to achieve self-localization. The position of the electrodes is determined with the use of radio localization techniques based on near-field Received Signal Strength Indication (RSSI) and also through the mapping of electrode placement models. The electrode placement models contain the patient’s body geometry and allow the comparison and verification of the predicted positions from the placement model with the calculated positions from the localization algorithms. Two different anchorless localization algorithms were simulated and tested in both computer and laboratory environment.

Electronics in Medicine

Electronics has long made an undeniable and valuable contribution in the field of medicine. New medical electronic devices are based on available medical knowledge combined with technologies available in the electronics field. Electronics in medicine has a wide range of applications, from diagnostics to therapy, always aiming to provide new tools to improve the well-being of the population.