The rapidly growing market for wireless technologies (Body LAN, cellular and Wireless LAN) in medical environments has led to a critical need for effective cable replacement solutions. This will enable widespread use of wireless body sensors, utilizing both an effective transmission protocol as well as providing proper infrastructure support. One of the emerging solutions for the body network is the ZigBee technology; primarily because it utilizes small format, low-power, long battery life radios. It is generally used for applications that can tolerate a low transmission rate, but demand long battery life. An essential requirement of Body LANs for patient care is to guarantee reliable service. In this respect, ZigBee faces severe interference problems in the presence of various 802.11 networks, and its viability in the medical environment is greatly diminished. This interference is caused by the fact that ZigBee shares channel spectrum with the 802.11 protocols. In this paper, we first confirm the claims that ZigBee is vulnerable to interference from 802.11. Then, we propose a solution for minimizing interference from 802.11 in ZigBee medical sensors.

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Abstract-AutoGait is a mobile platform that autonomously discovers a user's walking profile and accurately estimates the distance walked. The discovery is made by utilizing the GPS in the user's mobile device when the user is walking outdoors. This profile can then be used both indoors and outdoors to estimate the distance walked. To model the person's walking profile, we take advantage of the fact that a linear relationship exists between step frequency and stride length, which is unique to individuals and applies to everyone regardless of age. Autonomous calibration invisible to users allows the system to maintain a high level of accuracy under changing conditions. AutoGait can be integrated into any pedometer or indoor navigation software on handheld devices as long as they are equipped with GPS. The main contribution of this paper is two fold: (1) we propose an autocalibration method that trains a person's walking profile by effectively processing noisy GPS readings, and (2) we build a prototype system and validate its performance by performing extensive experiments. Our experimental results confirm that the proposed auto-calibration method can accurately estimate a person's walking profile and thus significantly reduce the error rate.

Abstract-Remote medical monitoring using body sensors and wireless communications has been gaining attention recently because of the potential savings in patient care and the equally impressive enhancements of quality of care for mobile individuals. What makes remote medical monitoring feasible are the advances in the body sensor technology (non-intrusive sensors embedded in actuators to monitor vital signs); and in wireless technology (Body LAN, cellular and Wireless LAN). Currently, most medical vests and body LANs connect to the Internet in a point-topoint fashion, via the cellular system (say SMS). With the growing popularity of ubiquitous computing and opportunistic P2P personal networks, it makes sense to explore beyond the point to point health care paradigm and study new models for remote patient care that exploit P2P networking among patients and care providers (nurses, doctors, emergency personnel). In this paper we identify several medical care applications based on P2P Health Networking. We then focus on two specific scenarios with nurses and patients both equipped with Bluetooth devices: a field hospital where nurses opportunistically collect, share and upload in P2P fashion patient medical records during bedside visits, and a field trip situation with patients supervised by nurses, where a patient emergency is promptly reported to the nearest nurse using enhanced inquiry response Bluetooth techniques. Simulation and testbed experiments show that Bluetooth P2P networking is both feasible and cost-effective in remote medical monitoring.