Leo Selavo

The Advanced Health and Disaster Aid Network: A Light-Weight Wireless Medical System for Triage

Advances in semiconductor technology have resulted in the creation of miniature medical embedded systems that can wirelessly monitor the vital signs of patients. These lightweight medical systems can aid providers in large disasters who become overwhelmed with the large number of patients, limited resources, and insufficient information. In a mass casualty incident, small embedded medical systems facilitate patient care, resource allocation, and real-time communication in the advanced health and disaster aid network (AID-N). We present the design of electronic triage tags on lightweight, embedded systems with limited memory and computational power. These electronic triage tags use noninvasive, biomedical sensors (pulse oximeter, electrocardiogram, and blood pressure cuff) to continuously monitor the vital signs of a patient and deliver pertinent information to first responders. This electronic triage system facilitates the seamless collection and dissemination of data from the incident site to key members of the distributed emergency response community. The real-time collection of data through a mesh network in a mass casualty drill was shown to approximately triple the number of times patients that were triaged compared with the traditional paper triage system.

Wireless Medical Sensor Networks in Emergency Response: Implementation and Pilot Results

This project demonstrates the feasibility of using cost- effective, flexible, and scalable sensor networks to address critical bottlenecks of the emergency response process. For years, emergency medical service providers conducted patient care by manually measuring vital signs, documenting assessments on paper, and communicating over handheld radios. When disasters occurred, the large numbers of casualties quickly and easily overwhelmed the responders. Collaboration with EMS and hospitals in the Baltimore Washington Metropolitan region prompted us to develop miTag (medical information tag), a cost- effective wireless sensor platform that automatically track patients throughout each step of the disaster response process, from disaster scenes, to ambulances, to hospitals. The miTag is a highly extensible platform that supports a variety of sensor add-ons - GPS, pulse oximetry, blood pressure, temperature, ECG - and relays data over a self-organizing wireless mesh network Scalability is the distinguishing characteristic of miTag: its wireless network scales across a wide range of network densities, from sparse hospital network deployments to very densely populated mass casualty sites. The miTag system is out-of-the-box operational and includes the following key technologies: 1) cost-effective sensor hardware, 2) self-organizing wireless network and 3) scalable server software that analyzes sensor data and delivers real-time updates to handheld devices and web portals. The system has evolved through multiple iterations of development and pilot deployments to become an effective patient monitoring solution. A pilot conducted with the Department of Homeland Security indicates miTags can increase the patient care capacity of responders in the field A pilot at Washington Hospital showed miTags are capable of reliably transmitting data inside radio-interference-rich critical care settings.

Clairvoyant: a comprehensive source-level debugger for wireless sensor networks

Wireless sensor network (WSN) applications are notoriously difficult to develop and debug. This paper describes Clairvoyant which is a comprehensive source-level debugger for wireless, embedded networks. With Clairvoyant, a developer can wirelessly connect to a sensor network and execute standard debugging commands including break, step, watch, and backtrace, as well as new commands that are specially designed for debugging WSNs. Clairvoyant attempts to minimize its effect on the program being debugged in terms of network load, memory footprint, execution speed, clock consistency, and flash lifetime.

Real time pothole detection using Android smartphones with accelerometers

The importance of the road infrastructure for the society could be compared with importance of blood vessels for humans. To ensure road surface quality it should be monitored continuously and repaired as necessary. The optimal distribution of resources for road repairs is possible providing the availability of comprehensive and objective real time data about the state of the roads. Participatory sensing is a promising approach for such data collection. The paper is describing a mobile sensing system for road irregularity detection using Android OS based smart-phones. Selected data processing algorithms are discussed and their evaluation presented with true positive rate as high as 90% using real world data. The optimal parameters for the algorithms are determined as well as recommendations for their application.

An Assisted Living Oriented Information System Based on a Residential Wireless Sensor Network

This paper deals with a new medical information system called Alarm Net designed for smart healthcare. Based on an advanced Wireless Sensor Network (WSN), it specifically targets assisted-living residents and others who may benefit from continuous and remote health monitoring. We present the advantages, objectives, and status of the system built at the Department of Computer Science at UVA. Early results of the prototype suggest a strong potential for WSNs to open new research perspectives for ad hoc deployment of multi-modal sensors and improved quality of medical care

Participatory user centered design techniques for a large scale ad-hoc health information system

During mass casualty incidents, an enormous amount of data, including the vital signs of the patients, the location of the patients, and the location of the first responders must be gathered and communicated efficiently. The Advanced Health and Disaster Aid Network (AID-N) used participatory design methods to develop an electronic triage system that changed how emergency personnel interacted, collected, and processed data at mass casualty incidents. Through a collaboration between computer scientists, biomedical engineers, usability analysts, paramedics, and medical doctors, AID-N constructed scalable algorithms to monitor a large numbers of patients, an intuitive interface to support overwhelmed responders, and an ad-hoc mesh network that maintained connectivity to patients in ad-hoc, chaotic settings. This paper describes an iterative approach to user-centered design that allows for the collection of a massive amount of data and presents this data in a clear and understandable format to the user.

LynxNet: wild animal monitoring using sensor networks

Monitoring wild animals, especially those that are becoming endangered (for example, lynxes and wolves) is important for biology researchers. Solutions for the monitoring already exist; however, they all have drawbacks, such as limited range or lifetime, sensing modality, reporting delays, unreliability of operation. In this work we describe our experiences in designing an improved animal monitoring sensor system and low-level software for sensor node control and communication. The target animals for this particular research are wild lynxes or canines, however it can be extended to other animal species. The LynxNet system is based on tracking collars, built around TMote Mini sensor nodes, sensors, GPS and 433MHz radio, and stationary base stations, placed at the locations that are frequented by the animals. We present preliminary field results of our radio communication range tests.

SenQ: An Embedded Query System for Streaming Data in Heterogeneous Interactive Wireless Sensor Networks

Interactive wireless sensor networks (IWSNs) manifest diverse application architectures, hardware capabilities, and user interactions that challenge existing centralized [1], or VM-based [2] query system designs. To support in-network processing of streaming sensor data in such heterogeneous environments, we created SenQ, a multi-layer embedded query system. SenQ enables user-driven and peer-to-peer in-network query issue by wearable interfaces and other resource-constrained devices. Complex virtual sensors and user-created streams can be dynamically discovered and shared, and SenQ is extensible to new sensors and processing algorithms. We evaluated SenQs efficiency and performance in a testbed for assisted-living, and show that on-demand buffering, query caching, efficient restart and other optimizations reduce network overhead and minimize data latency.

SeeDTV : deployment-time validation for wireless sensor networks

Deployment of a wireless sensor network (WSN) system is a critical step because theoretical models and assumptions often differ from real environmental characteristics and performance at the deployment site. In addition, such systems are often located in areas that are difficult to reach or even in-accessible for certain periods of time. Therefore, it is imperative to verify the functionality of the system at the time of the deployment, thus lowering the risk of early failures. Coincidentally, the validation minimizes the expense of revisiting the site in the near future for re-deployment, maintenance, or repairs. In this paper we present a deployment time validation framework SeeDTV that consists of techniques and procedures for WSN status assesment and verification. SeeDTV is supported by a portable, lightweight, and low power in-situ user interface device SeeMote. SeeDTV has demonstrated the potential for early problem detection at three levels of WSN in-situ validation: sensor node devices, wireless network physical and logical integrity, and connectivity to the back-end such as a data server over the Internet. SeeDTV is presented in the context of LUSTER -- an environmental sensor network for ecological monitoring under a shrub thicket canopy on islands off the coast of Virginia.

SeeMote: In-Situ Visualization and Logging Device for Wireless Sensor Networks

In this paper we address three challenges that are present when building and analyzing wireless sensor networks (WSN) as part of ubiquitous computing environment: the need for an in-situ user interface, a data logger, and a power consumption meter. Solutions for the above have been presented using laptops, personal digital assistants (PDA), onboard flash memory chips of limited size (usually 1MB), and laboratory test equipment. All of them have a good utility for the right applications. However, considering a certain variety of WSNs, where size, battery life, and cost are crucial, none of the above solutions is satisfactory. In this paper we present a compact, lightweight, low power, and low cost multimodal sensor module SeeMote that meets the stated challenges, and is compatible with the popular MICAz mote. Our module has the following components: (1) a graphical user interface component that combines a color liquid crystal display (LCD) and 5-way buttons, (2) a power meter component that is reconfigurable for attaching various low-power devices, and (3) a data logger component that is interfaced to a removable secure digital (SD) or multimedia memory card (MMC). The module dimensions are 34times58times12 mm. This paper describes the hardware and software design and experiences while developing and using the device. The device is evaluated by comparing its parameters and functionality to laptop and PDA solutions. We conclude that SeeMote is preferred for certain WSNs, such as very large scale, difficult to reach, and wearable WSNs. We also present several applications that use the LCD module, such as the portable frequency spectrum analyzer and remote sensory data display device.