A Review on Requirement of Wireless Sensor Network in Healthcare Applications

An assortment of uses depend on Wireless AdHoc and Sensor Networks (WASN) which has pulled in individuals from a wide number of regions demonstrating its utility extents from protection to farming, climate guaging to pre-fiasco discovery, geography to mineralogy, catastrophe alleviation frameworks to medicinal care, vehicle following to territory checking, and a considerable measure many. In the field of therapeutic sciences the uses of WASN are new however have left an incredible effect on the psyches of the two analysts and specialists. Medicinal determination and test examination like observing the patients, detecting exceptional and basic indications physically and rationally should be possible utilizing sensor systems for the therapeutic care. The potential restorative utilizations of WASN are 'Constant, nonstop patient observing', 'Home checking for interminable and elderly patients', 'Gathering of long haul databases of clinical information'. Alternate applications can be giving therapeutic supervision to individuals in remote zones and for detecting vast mischances, fires, fear based oppressor assaults and remote crucial sign checking facilitating the activity of specialists. In this paper we have attempted to make an overview of all the conceivable utilizations of WASN in the field of therapeutic Sciences

Reliable Patient Monitoring: A Clinical Study in a Step-down Hospital Unit

This paper presents the design, deployment, and empirical study of a wireless clinical monitoring system that collects pulse and oxygen saturation readings from patients. The primary contribution of this paper is an in-depth clinical trial that assesses the feasibility of wireless sensor networks for patient monitoring in general (non-ICU) hospital units. The trial involved 32 patients monitored in a step-down cardiology unit at Barnes-Jewish Hospital, St. Louis. During a total of 31 days of monitoring, the network achieved high reliability (median 99.92%, range 95.21% - 100%). The overall reliability of the system was dominated by sensing reliability (median 80.55%, range 0.38% - 97.69%) of the pulse oximeters. Sensing failures usually occurred in short bursts, although long bursts were also present and were caused by the sensor disconnections. We show that the sensing reliability could be significantly improved through oversampling and by implementing a disconnection alarm system that incurs minimal intervention cost. Our results also indicate that the system provided sufficient resolution to support the detection of clinical deterioration in two patients who were transferred to the ICU. The results show the feasibility of using wireless sensor networks for patient monitoring and may guide future research. We also report lessons learned from the deployment in the clinical environments with patient users

Towards Real-time Wireless Sensor Networks

Wireless sensor networks are poised to change the way computer systems interact with the physical world. We plan on entrusting sensor systems to collect medical data from patients, monitor the safety of our infrastructure, and control manufacturing processes in our factories. To date, the focus of the sensor network community has been on developing best-effort services. This approach is insufficient for many applications since it does not enable developers to determine if a system\u27s requirements in terms of communication latency, bandwidth utilization, reliability, or energy consumption are met. The focus of this thesis is to develop real-time network support for such critical applications. The first part of the thesis focuses on developing a power management solution for the radio subsystem which addresses both the problem of idle-listening and power control. In contrast to traditional power management solutions which focus solely on reducing energy consumption, the distinguishing feature of our approach is that it achieves both energy efficiency and real-time communication. A solution to the idle-listening problem is proposed in Energy Efficient Sleep Scheduling based on Application Semantics: ESSAT). The novelty of ESSAT lies in that it takes advantage of the common features of data collection applications to determine when to turn on and off a node\u27s radio without affecting real-time performance. A solution to the power control problem is proposed in Real-time Power Aware-Routing: RPAR). RPAR tunes the transmission power for each packet based on its deadline such that energy is saved without missing packet deadlines. The main theoretical contribution of this thesis is the development of novel transmission scheduling techniques optimized for data collection applications. This work bridges the gap between wireless sensor networks and real-time scheduling theory, which have traditionally been applied to processor scheduling. The proposed approach has significant advantages over existing design methodologies:: 1) it provides predictable performance allowing for the performance of a system to be estimated upon its deployment,: 2) it is possible to detect and handle overload conditions through simple rate control mechanisms, and: 3) it easily accommodates workload changes. I developed this framework under a realistic interference model by coordinating the activities at the MAC, link, and routing layers. The last component of this thesis focuses on the development of a real-time patient monitoring system for general hospital units. The system is designed to facilitate the detection of clinical deterioration, which is a key factor in saving lives and reducing healthcare costs. Since patients in general hospital wards are often ambulatory, a key challenge is to achieve high reliability even in the presence of mobility. To support patient mobility, I developed the Dynamic Relay Association Protocol -- a simple and effective mechanism for dynamically discovering the right relays for forwarding patient data -- and a Radio Mapping Tool -- a practical tool for ensuring network coverage in 802.15.4 networks. We show that it is feasible to use low-power and low-cost wireless sensor networks for clinical monitoring through an in-depth clinical study. The study was performed in a step-down cardiac care unit at Barnes-Jewish Hospital. This is the first long-term study of such a patient monitoring system