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Published by the IEEE Computer Society
Guest Editors' Introduction Pervasive Computing in Healthcare
Pervasive computing is often mentioned in the context of improving healthcare. Usually, these examples involve consumer monitoring devices such as blood pressure cuffs and glucose meters that can upload data to a personal computer for collection and dissemination to professional caregivers. By collecting patient data in settings more varied than doctors' offices, healthcare providers hope to better understand the many facets of patients' daily lives and then modify therapies to the individual.
Another important context is emergency care to accelerate access to medical records at the emergency site or to bring experts to the scene virtually. By giving medical professionals appropriate, complete information, we expect to deliver better care that's tuned not only to the situation but also to the patient's history.
The surgical field also receives much attention, as surgeons and nurses must monitor and control various vital functions under intensely stressful conditions. Technologists are developing systems to collect and process an ever-increasing range of telemetry from instruments used in an operating room and to augment human ability to detect patterns of concern that could require immediate action.
Many of these applications have appeared in the popular press and are actually starting to be deployed. At one end of the spectrum, consumer devices easily network with home PCs to let users gather data from sensors in the home that their physicians can access online. At the other end, telesurgery is becoming a practical reality, with remote physicians able to consult on a patient's condition as well as take part in a surgical procedure.
This special issue seeks to go beyond these "expected" applications and bring the reader an even wider range of applicability for pervasive computing technologies in the highly varied healthcare domain.
Proponents tout pervasive computing as benefiting healthcare in at least three ways:
• lowering costs by getting appropriate care to the people who need it much faster than previously possible;
• making expert care accessible to more people, thereby increasing the scale at which first-rate healthcare is applied; and
• making healthcare more personalized, prompting individuals to take more responsibility for maintaining their health.
In realizing this promise, we'll have to radically improve the many technologies that constitute pervasive computing: from how we collect data to sensing devices to how we present information. As we explore new applications, we're finding important challenges that we, as technologists, must address to eventually make systems that help the great majority of the world's population. That means looking beyond acute care to the full range of afflictions that make life challenging for many people.
The five articles in this special issue will give you a sense of the expanding application of pervasive computing technologies in healthcare. They span a range of ages—from childhood to old age—and locations—from hospitals to homes and everything in between.
"Ubiquitous Psychotherapy," by Marco de Sá, Luís Carriço, and Pedro Antunes, is a case in point. Mobile technology supports cognitive behavioral therapy via a PDA that helps a therapist customize coaching help for a particular patient. It also lets that patient provide input to the therapist throughout the day. Together, they can then analyze the interactions, which helps the patient recall his or her difficulties and gives the therapist a better, more detailed view of what actually happened in a particular situation. This application builds on the experience-sampling method popularized in user-centered design.
In "Pervasive Computing and Autism: Assisting Caregivers of Children with Special Needs," Julie A. Kientz, Gillian R. Hayes, Tracy L. Westeyn, Thad Starner, and Gregory D. Abowd apply a suite of data-gathering technologies to help educators of children with autism. They describe how these technologies capture important aspects of the sessions between caregivers and the children. Besides facilitating assessment, this easily searchable record can help caregivers collectively tune methods and inform each other of a particular child's needs.
"Distributed Healthcare: Simultaneous Assessment of Multiple Individuals," by Tamara L. Hayes, Misha Pavel, Andre Gustavo Adami, Nicole Larimer, Ishan A. Tsay, and John Nutt, tackles the practical problems of evaluating elderly patients in their own homes. They examine gait analysis and the system necessary to measure gait in a real home occupied by multiple people. The authors present a complete system, from sensors to visualization software, that accomplishes this demanding task such that it could be useful for large-scale deployment.
We then turn to supporting caregivers more directly. In "Pervasive Computing Support for Hospitals: An Overview of the Activity-Based Computing Project," Jakob E. Bardram and Henrik B. Christensen demonstrate an approach that directly supports the larger-scale activities of medical professionals in a hospital setting. Rather than supporting a fine-grained task such as performing a specific procedure on a patient, the system seeks to support longer-range activities that will likely involve a team of clinicians and span a patient's entire hospital stay.
The last article, a special technology feature, discusses a new enabling technology for physiological monitoring. "Conductive-Fabric Garment for a Cable-Free Body Area Network," by Eric Wade and Harry Asada, describes a promising approach to making a wearable garment that can interconnect a wide range of sensors around a person's body. Such technologies will enrich the toolset that physicians and patients can count on for continuous telemetry.
Of course, the papers here are only the start of what has the promise to be a very important application space for pervasive computing technology—an area that will affect, and improve, all of our lives. We look forward to future work by these authors and the many others embarking in this exciting direction.
is a professor of computer science and engineering at the University of Washington, where he has been on the faculty since received his PhD from UC Berkeley. In 2001, he founded Intel Research Seattle, where he launched the lab on applications of ubiquitous computing technology to health care and elder care, in particular. His research interests include location-based systems, sensor-based inferencing, and tagging objects with passive and active tags. He serves on the IEEE Pervasive Computing
editorial board. Contact him at email@example.com; www.cs.washington.edu/homes/gaetano.
manages the Smart Space project for the National Institute of Standards and Technology's Information Technology Laboratory in its Information Access Division. His research interests include distributed sensor networks, sensor fusion, speech recognition, speaker identification, speech quality measurement, array based auto-directive speech signal acquisition, and video person tracking. He received his BA in Mathematics from Indiana University. He lead development of the NIST Smart Data Flow System middleware for sensor data acquisition and transport as well as the NIST Mk-III microphone array. These open software and hardware platforms are used by government, commercial, and academic R&D labs worldwide to capture multimodal sensor data bases and to integrate technologies for beamforming, bearing estimation, source localization, speaker, face, and speech recognition, using audio, video, and sensor fusion techniques. He's a principal investigator on the NIST Single Molecule Measurement and Manipulation Program developing statistical methods for state identification and decoding in single molecule systems using unsupervised Hidden Markov Modeling. He was previously the lead engineer for the IBM Spoken Language Systems Group and developed award winning IBM continuous speech recognition products. He obtained several patents on speech recognition techniques including word spotting, signal processing, and spoken interface. He's a member of the IEEE. Contact him at firstname.lastname@example.org.
manages a group on technologies for client computing at IBM Research. He led the IBM Research effort on developing the WatchPad, a high function wristwatch computer. He also helped develop novel concepts such as the SoulPad and the Personal Mobile Hub and worked on high-performance graphics systems. He received his PhD in computer and systems engineering from Rensselaer Polytechnic Institute. He has received 24 Invention Achievement Awards and an Outstanding Technical Achievement from IBM, and he holds 45 US patents. He was the general chair for the 7th IEEE Symposium on Wearable Computers in 2003 and has also served on program committees for several ACM/IEEE conferences on pervasive computing, media, and low power systems. He serves on the editorial boards for IEEE Pervasive Computing
and IEEE Transactions on Mobile Computing
. He's a senior member of the IEEE. Contact him at email@example.com.
is the Vice Chairman for Information Services at Mayo Clinic. He shares responsibility for leadership of the Information Services organization, which provides application development and support for Mayo Clinic's integrated clinical systems initiative; clinical support systems; laboratory, pathology and extramural applications; and administrative applications. The Information Services organization also provides technical and infrastructure support for Mayo's Rochester-based data centers and support services for Mayo's group practices in Jacksonville, Florida and Scottsdale, Arizona through an internal shared services organization. He's a fellow and past chairman of the Board of Directors of the Healthcare Information and Management Systems Society (HIMSS). He's a frequent speaker on topics addressing the effective use of healthcare information technology. Contact him at firstname.lastname@example.org.