Stig Støa

An ultra wideband communication channel model for capsule endoscopy

Capsule endoscopy is an increasingly popular alternative to a tube-based endoscope used in diagnosing gastrointestinal diseases. It enables the inspection of areas that are not easily accessible using traditional endoscopy and reduces patient discomfort. In addition to transferring high-capacity demanding image data, the capsules wireless interface must provide a wireless link that enables real-time positioning and tracking of the capsule. Ultra wideband (UWB) interfaces have great potential for the communication links of this application due to their inherent low power consumption, high transmission rates, accurate localization properties and simple electronics. However, accurate knowledge of the propagation channel is essential for efficient design of such UWB wireless communication systems. This paper presents a channel model for the propagation of a UWB pulse in the digestive tract in the 3.4–4.8 GHz frequency band. For the development of this model, numerical electromagnetic (EM) simulations were conducted using a voxel anatomical model that includes the dielectric properties of human tissues; using this EM simulator the channel responses of many in-body probes were computed. Based on the analysis of the obtained data we provide the mathematical expressions to calculate the average path loss and its distribution at several receiver locations surrounding the abdomen. Our proposed model gives designers an important tool that approximates well the digestive tracts in-body channel properties, thereby eliminating the need for time consuming and complex numerical simulations.

A decentralized MAC layer protocol with periodic channel access for biomedical sensor networks

The use of biomedical sensor networks in complex clinical diagnostics and treatment may provide greater flexibility for both patient and the medical staff as some of the same sensors could follow the patient throughout the cycle of treatment. Biomedical sensors usually transmit periodically with known intervals and may require medium to higher data rates and lower packet drop rate than most traditional sensor networks. We propose a new method built on the IEEE 802.15.4 standard to enable higher throughput while keeping the packet drop rate at a minimum by utilizing the periodic behavior observed in such sensor networks. The simulation results show that, for certain scenarios, the average throughput compared to the IEEE 802.15.4 standard configuration can be doubled, while keeping the packet drop ratio at a minimum. Furthermore, by utilizing the property of periodic behavior, the channel efficiency has been improved from 30% to 50% compared to the standard IEEE 802.15.4 configuration. We show that the proposed method generates less protocol overhead and significantly reduces the chance of transmission errors due to colliding packets. Thus, it attains operational performance closer to saturation for a given packet discard ratio. Energy consumption due to retransmissions is reduced as the proposed algorithm greatly reduces collisions and requires few retransmissions. The proposed method requires minimum computational complexity and can be used on sensor nodes in a decentralized manner.

Data Throughput Optimization in the IEEE 802.15.4 Medical Sensor Networks

Use of wireless biomedical sensor networks in complex clinical diagnostics and treatments may provide greater flexibility for both patient and medical staff as some of the same sensors could follow the patient throughout the cycle of treatment. A typical scenario from an intensive care unit, with data from three vital sign sensors, is used as an example for both hardware and software simulations. Results show that data throughput in such biomedical networks is greatly depended on packet size while competing for channel access. A new scheduling algorithm has been proposed for multi-hop networks. Some of the hardware limitations are identified, where the trade off between hardware and software systems is demonstrated

On localisation accuracy inside the human abdomen region

In this work, localisation of a source within an absorbing medium is considered. By an absorbing medium, the authors mean an environment where the signal power decays exponentially with distance. The authors assume that the source is heard by nearby sensors when transmitting and its position shall be estimated based on the received signal strength (RSS) by these sensors. Under these assumptions, the focus is to determine the Cramer–Rao lower bound (CRLB). Thus, the goal is to derive the theoretical performance limit for an optimal estimator, and to study the feasibility of RSS-based localisation in an absorbing environment and specifically in human abdominal region. The authors demonstrate that the CRLB greatly depends on the shadowing conditions, and also on the relative positions of the sensors and the source. Although the obtained results are quite general, the motivating application is localisation of capsule endoscope in human abdominal region. The authors find that the RSS-based method can reach the needed accuracy for localising a capsule endoscope.

Short-range wireless sensor network for critical care monitoring

A Scandinavian research consortium collaborated to develop a wireless clinical monitoring platform. A collection of experimental wireless sensor prototypes were implemented in complex, process-control software modified for the project. The objective was to facilitate real-time and historical point-of-care sensor data for clinical decision support in critical care. The short-range wireless radio frequency platform used in the project was the IEEE 802.15.4 wireless personal area network standard. Invasive sensors included an arterial blood pressure sensor, an epicardial three-axis accelerometer and a digital pulmonary air leakage system. Non-invasive sensor signals came from an electrocardiogram sensor, a pulse oximeter, a medical radar prototype and a temperature sensor. Radio frequency signals from sensors to base stations and onwards in the wireless sensor network architecture were scrutinised during experimental surgery. Qualitative assessment of the sensor data presentation was made. Shadowing effects influencing the radio frequency channel performance was quantified. The shadowing effects were caused by the dynamic work pattern of the clinical team in combination with stationary equipment in the operating room during surgery. Shadowing effects did not compromise the quality of wireless sensor data severely. An evaluation of the communication links between individual sensors and two separate base stations are provided in this paper.

A biomedical wireless sensor network for hemodynamic monitoring

In the Biomedical Wireless Sensor Network (BWSN) project a consortium of Scandinavian research institutions, technology startup companies, sensor producers, software companies and a hospital based clinical test facility collaborated for 36 months. A portfolio of multiple, experimental wireless sensor prototypes were implemented in sophisticated process control software modified for the project. The project objective was to facilitate real time and historical point-of-care sensor data for clinical decision support and monitoring in hemodynamic treatment. The wireless communication platform and results from clinical tests are presented in this paper. The radio frequency platform used in the project was operating in the 2.4 GHz ISM band based on the IEEE 802.15.4 Wireless Personal Area Network standard. Invasive sensors included a non-disposable blood pressure sensor, an epicardial 3- axis accelerometer and a digital pulmonary air leakage system. Non-invasive sensor signals came from an ECG sensor, a pulse oximeter, a medical radar and a temperature sensor. Point-to-point transmission of radio frequency signals from sensors to base stations and onwards in the biomedical wireless sensor network (BWSN) architecture was scrutinized during experimental surgery. A qualitative assessment of the sensor data presentation was made. Occurrence of shadowing effects influencing the radio frequency channel performance was quantified. The shadowing effects were caused by the dynamic work pattern of the clinical team in combination with stationary equipment in the operating room during surgery. The shadowing effects were not found to compromise the quality of the wireless sensor data. Shadowing parameters to reconstruct our measurements and model the communication links between individual sensors and two separate base stations are provided.

Online analysis of myocardial ischemia from medical sensor data streams with Esper

Despite tremendous development in wireless sensor networks, the abilities are by far yet fully leveraged in the case of online analysis of medical sensor data. We investigate how a data stream management system can be used to query and analyze streaming data from different medical sensors in real-time. By using the open source data stream management system Esper, we have implemented queries, based upon earlier work by Elle et al., that can be used for real-time recognition of myocardial ischemia by combining a 3-axis accelerometer on the left ventricle of the heart, with an ECG sensor used for QRS detection. In the queries we use a new type of sliding window; a variable length triggered tumbling window. The window is used for aggregate operations that targets only sensor readings originating from single heartbeats. We show how algorithms that are used for medical analysis can be implemented as custom aggregation functions, thus incorporated into the declarative query language that is more suitable for medical personnel without programming experience. Results from experiments run on data recorded from surgical procedures on pig models show that the queries produce correct results, and can be run in real-time on fairly simple computers, e.g. laptops.

Periodic-MAC: Improving MAC Protocols for Wireless Biomedical Sensor Networks through Implicit Synchronization

Wired biomedical sensors have facilitated increasingly advanced clinical decisions support systems in specialized medical settings over the last decades. Reliable hemodynamic monitoring of cardiac and pulmonary function is mandatory for individual tailoring of treatment of critically ill patients. Sensors provide the hemodynamic parameters that reveal impending clinical problems, and initiate caregiver intervention. Biomedical sensor technologies include invasive or non-invasive sensors for intermittent or continuous monitoring of vital physiological parameters used in hemodynamic treatment at point-of-care. A hemodynamic sensor portfolio thus involves multiple sensors either attached to the patient, or embedded in biomedical devices used for treatment. The criticality of such systems is evident, as they are used for direct life support in a setting where quality, stability and continuity of real-time data is vital (Oyri et al., 2010). For the last few decades, biomedical sensors and patient monitors used in hemodynamic monitoring have been based on wired solutions. However, a digital revolution is now taking place in healthcare. Medical profiles for wireless standards, such as Bluetooth or ZigBee standards, have currently been developed and adopted by the Continua Health Alliance (Caroll et al., 2007). In the standardization bodies IEEE, ISO and CEN TC 251, improvement of care by reuse of medical device data has been addressed for many years; In particular the IEEE 1073 Standard for Medical Device Connection. A consortium of Scandinavian research institutions, technology startup companies, sensor producers, and a hospital based test facility collaborated to develop a portfolio of multiple experimental wireless sensor prototypes for a platform compliant with the X73 PoC-MDC (ISO11073/IEEE1073)(Galarraga et al., 2006) medical device communication outline (Oyri et al., 2010). Other research groups have evaluated implementations of wireless clinical alerts from pager systems (Major et al., 2002 and Reddy et al., 2005). Yao and Warren investigated how to apply the ISO/IEEE 11073 Standards to wearable home health monitoring systems (Yao & Warren., 2005). There is a demand for a point of care clinical decision support systems providing real time processing of 26

Wireless vital signs from a life-supporting medical device exposed to electromagnetic disturbance

Abstract Objectives: To evaluate the level of agreement of simulated wired and Wi-Fi vital signs output from an intra-aortic balloon pump during exposure to electromagnetic interference from frequency overlapping ZigBee sensors. Material and methods: A series of experiments with interference from single and multiple ZigBee sensors were benchmarked with wired and Wi-Fi output. Tests included single ZigBee sensor adjacent and co-channel interference, and multiple ZigBee interferences towards the Wi-Fi receiver and transmitter. Results: Interference-free differences between wired and wireless aortic blood pressure and electrocardiogram were very small, verified by time domain and Bland – Altman plots. Bland – Altman plots comparing level of agreement in wired and wireless aortic blood pressure and ECG output during interference experiments showed a difference from 0.2 to 0.3 mmHg for blood pressure, and from 0.001 to 0.004 mV for electrocardiogram. Conclusions: Level of agreement in wired and wireless (Wi-Fi) arterial blood pressure and electrocardiogram during single or multiple sensor interference was high. No clinically relevant degradation of Wi-Fi transmission of aortic blood pressure or ECG signals was observed.

Evaluation of the reliability of blood pressure data transmission through an IEEE 802.11 link in the presence of IEEE 802.15.4 interference

Wireless sensors operating in unlicensed frequency bands have been proposed for monitoring physiological signals during surgical procedures in the operating room (OR). The IEEE 802.15.4/ZigBee wireless interface in the 2.4 GHz industrial-scientific-medical (ISM) band has been widely adopted for the implementation of radio transceivers (motes) suitable for medical wireless sensors. However, other medical devices in the OR transmit medical information in the same frequency band through IEEE 802.11/WiFi interfaces. Therefore, the introduction of wireless sensors in current medical practice is conditioned to the assurance of the electromagnetic compatibility (EMC) with the collocated medical devices already operating in the same frequency band. This is especially critical with life-supporting equipment, which cannot be interfered with during medical procedures. This paper presents the evaluation of the reliability of the transmission of blood pressure (BP) data from an intra-aortic balloon pump (IABP) console through an IEEE 802.11/WiFi interface when a collocated IEEE 802.15.4/ZigBee mote is transmitting. The Bland-Altman plotting method was used to assess the effects of cochannel and adjacent-channel interference. The results show that EMC is assured between both systems.