Dejan Raskovic

Stress monitoring using a distributed wireless intelligent sensor system

We are developing personal health monitors based on a wireless body area network (BAN) of intelligent sensors. Individual monitors will be integrated into a distributed wireless system for synchronized monitoring of a group of subjects. This system could be used during the selection process and as part of a psychophysiological evaluation of military members undergoing intense training. We use measures of heart-rate variability to quantify stress level prior to and during training as well as to predict stress resistance. This task requires reliable, high-precision instrumentation and synchronized measurements from a group of individuals over prolonged periods (days of training).

Issues in wearable computing for medical monitoring applications: a case study of a wearable ECG monitoring device

In this paper we discuss issues surrounding wearable computers used as intelligent health monitors. Unlike existing health monitors (for example, ECG and EEG holters), that are used mainly for data acquisition, the devices we discuss provide real-time feedback to the patient, either as a warning of impending medical emergency or as a monitoring aid during exercise. These medical applications are to be distinguished from applications of wearable computing for medical personnel, e.g. doctors, nurses, and emergency medical technicians. Medical monitoring applications differ from other wearable applications in their I/O requirements, sensors, reliability, privacy issues, and user interface. The paper describes a prototype wearable ECG monitor based upon a high-performance, low-power digital signal processor and the development environment for its design.

Medical Monitoring Applications for Wearable Computing

Medical monitors have benefited from technological advances in the field of wireless communication, processing and power sources. These advances have made possible miniaturization and prolonged operating times of medical monitors, as well as their global integration into telemedical systems. This allows patients to have real-time feedback about medical conditions while going about their normal daily activities. System designers are facing specific issues related to monitor acceptability, application requirements, power consumption and system connectivity. In this paper we discuss system design issues, present a survey of existing systems and sensors, and introduce two taxonomies of medical monitoring applications for wearable computing.

Wireless personal area networks in telemedical environment

Presents a new design of a wireless personal area network with physiological sensors for medical applications in a telemedical environment. Intelligent wireless sensors perform data acquisition and limited processing. Individual sensors monitor specific physiological signals (such as EEG, EGG, GSR, etc.) and communicate with each other and the personal server. The personal server integrates information from different sensors and communicates with the rest of the telemedical system as a standard mobile unit. The authors present their prototype implementation of the wireless intelligent sensor (WISE) based on a very low power consumption microcontroller and a DSP-based personal server. In future the authors expect all components of WISE to be integrated in a single chip for use in a variety of new medical applications and sophisticated human computer interfaces.

An accelerometer-based physical rehabilitation system

This paper presents a portable physical rehabilitation monitoring system based on a personal network of intelligent sensors. Rehabilitation is traditionally carried out in hospitals under supervision of qualified personnel. However, significantly better results could be achieved using out-of-hospital portable monitoring to allow patients computer-assisted rehabilitation in their homes. The new generation of personal digital assistants (PDA), such as Compaq iPAQ, offers large processing power, decent graphical user interface, and compact flash based secondary memory. Therefore, they are perfectly suited for portable monitoring units. Individual sensors are positioned on limbs to analyze movements using 2-axis MEMS accelerometers. The system monitors periods and forces of individual sensors, visualizing relevant physiological data in real-time on PDA, and archiving progress data on compact flash. A specialist supervises current advance and sets new optimum rehabilitation modes, thresholds for forces, step periods, etc. The system generates real-time warnings when predefined thresholds have been exceeded. We are developing a system for hip and knee replacement rehabilitation, as well as general physical rehabilitation. Other possible applications of our system include rehabilitation of stroke and heart attack patients.

An environment for runtime power monitoring of wireless sensor network platforms

Wireless sensor networks emerged as a key technology for prolonged, unsupervised monitoring in a wide spectrum of applications, from biological and environmental to civil and military. The sensor networks should operate autonomously for a long period of time under stringent resource and energy constraints. Energy conservation and power-awareness have become a focus of a number of research efforts, as sensor network nodes must operate on batteries or use energy extracted from the environment, such as solar energy or vibrations. Runtime power measurements and characterization of real existing systems are crucial for studies that target power optimizations, including techniques for dynamic adaptation based on the current energy status. This paper introduces an environment for unobtrusive real-time power monitoring that could be used for a number of wireless sensor platforms. We describe our methodology for calibration and validation of the environment and give empirical data for the Telos wireless sensor platform when it runs a subset of representative applications.

Synchronized physiological monitoring using a distributed wireless intelligent sensor system

Psychophysiological evaluation of a group of subjects requires synchronized monitoring of the individual subjects in the group during collective events. We present a concept of a wireless distributed data acquisition system for prolonged, synchronized health/stress monitoring of a selected group of subjects. The wireless distributed data acquisition system uses wireless intelligent sensors (WHRM) as individual heart rate variability (HRV) monitors, and a mobile wireless gateway (MOGUL). Each microcontroller sensor is equipped with a low power/low range (up to 100 ft) wireless transceiver, and communicates with the mobile gateway whenever the gateway comes into a range and identifies itself. The system is used for stress level evaluation using HRV monitoring during intense military training, and could be used to evaluate the stress level of individuals within the group in different settings, such as battlefield monitoring or day-trading on the stock market. In this paper we present the implemented distributed system architecture, system design issues, and lessons learned during implementation of the system.

Dynamic Voltage and Frequency Scaling For On-Demand Performance and Availability of Biomedical Embedded Systems

The goal of the study presented in this paper is to develop an embedded biomedical system capable of delivering maximum performance on demand, while maintaining the optimal energy efficiency whenever possible. Several hardware and software solutions are presented allowing the system to intelligently change the power supply voltage and frequency in runtime. The resulting system allows use of more energy-efficient components, operates most of the time in its most battery-efficient mode, and provides means to quickly change the operation mode while maintaining reliable performance. While all of these techniques extend battery life, the main benefit is on-demand availability of computational performance using a system that is not excessive. Biomedical applications, perhaps more than any other application, require battery operation, favor infrequent battery replacements, and can benefit from increased performance under certain conditions (e.g., when anomaly is detected) that makes them ideal candidates for this approach. In addition, if the system is a part of a body area network, it needs to be light, inexpensive, and adaptable enough to satisfy changing requirements of the other nodes in the network.

Embedded web server for wireless sensor networks

This paper presents an implementation of a platform-independent embedded web server and its integration into a network of wireless sensor nodes. The embedded web server is designed and built as an expansion module for one of the nodes in the wireless sensor network (WSN). It allows authorized Internet users to establish two-way communication with the sensor network. The server uses limited available hardware resources to implement an interface to the WSN node and to serve dynamic HTML pages to the remote user. This allows the user to monitor the operation of the WSN remotely, to periodically download the sensed data, and to change the operation mode of the network. In addition to providing monitoring and data collection services, the embedded web server can generate email alerts about critical issues in the WSN, provide secure access to modules that change the operation of the WSN, shut down sensor nodes, and log data from the network into an on-board flash memory.

Battery-Aware Embedded GPS Receiver Node

This paper discusses the design and implementation of an ultra low power embedded GPS receiver node for use in remote monitoring situations where battery life is of the utmost importance. The power consumed by a GPS radio is high when compared to other typical components of sensor networks. We offer several hardware and software solutions to prolong the battery life while preserving a required GPS tracking precision. A standard SiRF trickle mode, available on some of the latest chipsets switches between the full power and a single fixed duty cycle. If the fixed duty cycle is set too low, trickle mode causes too many signal drops; if set too high, consumes too much energy. Adding a low-power microcontroller allows us to dynamically change the operation mode by setting the duty cycle in relatively small steps, based on a set of less stringent and application dependant set of rules. In addition, an accelerometer is used as an energy efficient way of detecting that the object or person carrying the GPS is not moving. This allows the GPS-equipped node to switch to the lowest possible power consumption mode that still allows for fast restarts. Several hardware and software design aspects are explored and several measurements comparing system performance to commercially available products are shown to illustrate the effectiveness of the system.