Statistical method of modeling and optimization for wireless sensor nodes with different interconnect technologies and substrates

A comparison study was carried out between a wireless sensor node with a bare die flip-chip mounted and its reference board with a BGA packaged transceiver chip. The main focus is the return loss (S parameter S11) at the antenna connector, which was highly depended on the impedance mismatch. Modeling including the different interconnect technologies, substrate properties and passive components, was performed to simulate the system in Ansoft Designer software. Statistical methods, such as the use of standard derivation and regression, were applied to the RF performance analysis, to see the impacts of the different parameters on the return loss. Extreme value search, following on the previous analysis, can provide the parameters' values for the minimum return loss. Measurements fit the analysis and simulation well and showed a great improvement of the return loss from -5dB to -25dB for the target wireless sensor node.

A simulation-based design method to transfer surface mount RF system to flip-chip die implementation

The flip-chip technology is a high chip density solution to meet the demand for very large scale integration design. For wireless sensor node or some similar RF applications, due to the growing requirements for the wearable and implantable implementations, flip-chip appears to be a leading technology to realize the integration and miniaturization. In this paper, flip-chip is considered as part of the whole system to affect the RF performance. A simulation based design is presented to transfer the surface mount PCB board to the flip-chip die package for the RF applications. Models are built by Q3D Extractor to extract the equivalent circuit based on the parasitic parameters of the interconnections, for both bare die and wire-bonding technologies. All the parameters and the PCB layout and stack-up are then modeled in the essential parts' design of the flip-chip RF circuit. By implementing simulation and optimization, a flip-chip package is re-designed by the parameters given by simulation sweep. Experimental results fit the simulation well for the comparison between pre-optimization and post-optimization of the bare die package's return loss performance. This design method could generally be used to transfer any surface mount PCB to flip-chip package for the RF systems or to predict the RF specifications of a RF system using the flip-chip technology.

Energy harvesting system design and optimization for wireless sensor networks

Wireless sensor networks (WSN) are becoming widely adopted for many applications including complicated tasks like building energy management. However, one major concern for WSN technologies is the short lifetime and high maintenance cost due to the limited battery energy. One of the solutions is to scavenge ambient energy, which is then rectified to power the WSN. The objective of this thesis was to investigate the feasibility of an ultra-low energy consumption power management system suitable for harvesting sub-mW photovoltaic and thermoelectric energy to power WSNs. To achieve this goal, energy harvesting system architectures have been analyzed. Detailed analysis of energy storage units (ESU) have led to an innovative ESU solution for the target applications. Battery-less, long-lifetime ESU and its associated power management circuitry, including fast-charge circuit, self-start circuit, output voltage regulation circuit and hybrid ESU, using a combination of super-capacitor and thin film battery, were developed to achieve continuous operation of energy harvester. Low start-up voltage DC/DC converters have been developed for 1mW level thermoelectric energy harvesting. The novel method of altering thermoelectric generator (TEG) configuration in order to match impedance has been verified in this work. Novel maximum power point tracking (MPPT) circuits, exploring the fractional open circuit voltage method, were particularly developed to suit the sub-1mW photovoltaic energy harvesting applications. The MPPT energy model has been developed and verified against both SPICE simulation and implemented prototypes. Both indoor light and thermoelectric energy harvesting methods proposed in this thesis have been implemented into prototype devices. The improved indoor light energy harvester prototype demonstrates 81% MPPT conversion efficiency with 0.5mW input power. This important improvement makes light energy harvesting from small energy sources (i.e. credit card size solar panel in 500lux indoor lighting conditions) a feasible approach. The 50mm × 54mm thermoelectric energy harvester prototype generates 0.95mW when placed on a 60oC heat source with 28% conversion efficiency. Both prototypes can be used to continuously power WSN for building energy management applications in typical office building environment. In addition to the hardware development, a comprehensive system energy model has been developed. This system energy model not only can be used to predict the available and consumed energy based on real-world ambient conditions, but also can be employed to optimize the system design and configuration. This energy model has been verified by indoor photovoltaic energy harvesting system prototypes in long-term deployed experiments.

Pharmacotherapy optimization in older patients by a structured clinical pharmacist assessment and intervention

Introduction: Older individuals are particularly vulnerable to potentially inappropriate prescribing (PIP), drug related problems (DRPs) and adverse drug reactions (ADRs). A number of different interventions have been proposed to address these issues. However to-date there is a paucity of well-designed trials examining the impact of such interventions. Therefore the aims of this work were to: (i) establish a baseline PIP prevalence both nationally and internationally using the STOPP, Beers and PRISCUS criteria, (ii) identify the most comprehensive method of assessing PIP in older individuals, (iii) develop a structured pharmacist intervention supported by a computer decisions support system (CDSS) and (iv) examine the impact of this intervention on prescribing and incidence of ADRs. Results: This work identified high rates of PIP across all three healthcare settings in Ireland, 84.7% in the long term care, 70.7% in secondary care and 43.3% in primary care being reported. This work identified that for a comprehensive assessment of prescribing to be undertaken, an amalgamation of all three criteria should be deployed simultaneously. High prevalences of DRPs and PIP in older hospitalised individuals were identified. With 82.0% and 76.3% of patients reported to have at least one DRP or PIP instance respectively. The structured pharmacist intervention demonstrated a positive impact on prescribing, with a significant reduction MAI scores being reported. It also resulted in the intervention patients’ having a reduced risk of experiencing an ADR when compared to the control patients (absolute risk reduction of 6.8 (95% CI 1.5% - 12.3%)) and the number needed to treat = 15 (95% CI 8 - 68). However the intervention was found to have no significant effect on length of stay or mortality rate. Conclusion: This work shows that PIP is highly prevalent in older individuals across three healthcare settings in Ireland. This work also demonstrates that a structured pharmacist intervention support by a dedicated CDSS can significantly improve the appropriateness of prescribing and reduce the incidence of ADRs in older acutely ill hospitalised individuals.