Master of Science / Department of Electrical and Computer Engineering / Steven Warren / A reference design for a wearable, wireless biomedical sensor set has been a long-term need for researchers at Kansas State University, driven by the idea that a basic set of sensor components could address the demands of multiple types of human and animal health monitoring scenarios if these components offered even basic reconfigurability. Such a reference design would also be a starting point to assess sensor performance and signal quality in the context of various biomedical research applications. This thesis describes the development of a set of wireless health monitoring sensors that can be used collectively as a data acquisition platform to provide biomedical research data and to serve as a baseline reference design for new sensor and system development. The host computer, an Intel Edison unit, offers plug-and-play usability and supports both Wi-Fi and Bluetooth wireless connectivity. The reference sensor set that accompanies the Intel Edison single-board computer includes an electrocardiograph, a pulse oximeter, and an accelerometer/gyrometer. All sensors are based on the same physical footprint and connector placement so that the sensors can be stacked to create a collection with a minimal volume and footprint. The latest hardware version is 3.1. Version 1.0 supported only a pulse oximeter, whereas version 2.0 included an electrocardiograph, pulse oximeter, and respiration belt. In version 3.0, the respiration belt was removed, and accelerometers and gyroscopes were added to the sensor set. Version 3.1 is a refined version of the latter design, where known hardware bugs were remedied. Future work includes the development of new sensors and casing designs that can hold these sensor stacks.

Doctor of Philosophy / Department of Electrical & Computer Engineering / Steve Warren / The U.S. health care system is one of the most advanced and costly systems in the world. The health services supply/demand gap is being enlarged by the aging population coupled with shortages in the traditional health care workforce and new information technology workers. This will not change if the current medical system adheres to the traditional hospital-centered model. One promising solution is to incorporate patient-centered, point-of-care test systems that promote proactive and preventive care by utilizing technology advancements in sensors, devices, communication standards, engineering systems, and information infrastructures. Biomedical devices optimized for home and mobile health care environments will drive this transition. This dissertation documents research and development focused on biomedical device design for this purpose (including a wearable wireless pulse oximeter, motion sensor, and two-thumb electrocardiograph) and, more importantly, their interactions with other medical components, their supporting information infrastructures, and processing tools that illustrate the effectiveness of their data. The GumPack concept and prototype introduced in Chapter 2 addresses these aspects, as it is a sensor-laden device, a host for a local body area network (BAN), a portal to external integration frameworks, and a data processing platform. GumPack sensor-component design (Chapters 3 and 4) is oriented toward surface applications (e.g., touch and measure), an everyday-carry form factor, and reconfigurability. Onboard tagging technology (Chapters 5 and 6) enhances sensor functionality by providing, e.g., a signal quality index and confidence coefficient for itself and/or next-tier medical components (e.g., a hub). Sensor interaction and integration work includes applications based on the GumPack design (Chapters 7 through 9) and the Medical Device Coordination Framework (Chapters 10 through 12). A high-resolution, wireless BAN is presented in Chapter 8, followed by a new physiological use case for pulse wave velocity estimation in Chapter 9. The collaborative MDCF work is transitioned to a web-based Hospital Information Integration System (Chapter 11) by employing database, AJAX, and Java Servlet technology. Given the preceding sensor designs and the availability of information infrastructures like the MDCF, medical platform-oriented devices (Chapter 12) could be an innovative and efficient way to design medical devices for hospital and home health care applications.

In recent years, the development of a large variety of mobile computing devices has led to wide scale deployment and use of wireless ad hoc and sensor networks. Wireless Sensor Networks consist of battery powered, tiny and cheap "motes", having sensing and wireless communication capabilities. Although wireless motes have limited battery power, communication and computation capabilities, the range of their application is vast. In the first part of the dissertation, we have addressed the specific application of Biomedical Sensor Networks. To solve the problem of data routing in these networks, we have proposed the Adaptive Least Temperature Routing (ALTR) algorithm that reduces the average temperature rise of the nodes in the in-vivo network while routing data efficiently. For delay sensitive biomedical applications, we proposed the Hotspot Preventing Routing (HPR) algorithm which avoids the formation of hotspots (regions having very high temperature) in the network. HPR forwards the packets using the shortest path, bypassing the regions of high temperature and thus significantly reduces the average packet delivery delay, making it suitable for real-time applications of in-vivo networks. We also proposed another routing algorithm suitable for being used in a network of id-less biomedical sensor nodes, namely Routing Algorithm for networks of homogeneous and Id-less biomedical sensor Nodes (RAIN). Finally we developed Biocomm, a cross-layer MAC and Routing protocol co-design for Biomedical Sensor Networks, which optimizes the overall performance of an in-vivo network through cross-layer interactions. We performed extensive simulations to show that the proposed Biocomm protocol performs much better than the other existing MAC and Routing protocols in terms of preventing the formation of hotspots, reducing energy consumption of nodes and preventing network congestion when used in an in-vivo network. In the second part of the dissertation, we have addressed the problems of habitat-monitoring sensor networks, broadcast algorithms for sensor networks and the congestion problem in sensor networks as well as one non-sensor network application, namely, on-chip communication networks. Specifically, we have proposed a variation of HPR algorithm, called Hotspot Preventing Adaptive Routing (HPAR) algorithm, for efficient data routing in Networks On-Chip catering to their specific hotspot prevention issues. A protocol similar to ALTR has been shown to perform well in a sensor network deployed for habitat monitoring. We developed a reliable, low overhead broadcast algorithm for sensor networks namely Topology Adaptive Gossip (TAG) algorithm. To reduce the congestion problem in Wireless Sensor Networks, we proposed a tunable cross-layer Congestion Reducing Medium Access Control (CRMAC) protocol that utilizes buffer status information from the Network layer to give prioritized medium access to congested nodes in the MAC layer and thus preventing congestion and packet drops. CRMAC can also be easily tuned to satisfy different application-specific performance requirements. With the help of extensive simulation results we have shown how CRMAC can be adapted to perform well in different applications of Sensor Network like Emergency Situation that requires a high network throughput and low packet delivery latency or Long-term Monitoring application requiring energy conservation.

This doctoral thesis investigates the application of laser-induced breakdown spectroscopy (LIBS) for detection of labeled biomolecules on nitrocellulose paper. Nitrocellulose paper is a material often used for assays involving the concentration and labeling of a target analyte, followed by label detection. Among paper-based diagnostics are lateral-flow immuno-assays (LFIAs). Research efforts have made LFIAs into accessible, portable,and low-cost tools for detecting targets such as allergens, toxins,and microbes in food and water.Gold (Au) nanoparticles are standard biomolecular labels among LFIAs, typically detected via colorimetric means.Other labels, such as quantum dots, are also often metallic, and research is ongoing to expand the number of portable instrumentations applied to their detection. A wide diversity of lanthanide-complexed polymers (LCPs) are used as immunoassay labels but have been inapt for portable paper-based assays owing to lab-bound detection instrumentation, until now. LIBS is a multi-element characterization technique which has recently developed from a bench-top to a portable/hand-held analytical tool. This is among the first studies to show that LCPs can be considered as options for biomolecule labels in paper-based assays using bench-based and hand-held LIBS as label detection modalities.<div>Chapter one reviews the importance of rapid, multiplexed detection of chemical and biological contaminants, the application of current biosensors, and the role of LIBS as an emerging biosensor. Paper-based bioassays were identified as a promising approach for contaminant detection whose capabilities could be enhanced by LIBS. The next chapter dives into LIBS system designs to address which LIBS parameters were appropriate for label detection on paper assay material. A balance of LIBS parameters was found to be important for successful analyte detection. Chaptert hree optimizes a LIBS design for sensitive detection of 17 metals and establishes limit of detection values for 7 metals. Optimal detection parameters depended on the metal being detected and were applied to the objective of the final chapter: LIBS detection of labeled antigen immobilized on a paper-based assay. Both antibody and bacteria detection assays were successfully performed and analyzed using bench top and portable LIBS,suggesting an exciting future for the use of LIBS as a biosensor.The prospect of using LIBS for multiplexed, rapid and sensitive detection of biomolecules in assays is explored, laying grounds for future work in the ever-relevant field of biological and chemical hazard detection.<br></div>