Health care continues to be one of the biggest challenges facing our society. Factors such as lifestyle choices, genetics, aging, stress and environmental exposures play a critical role in determining health outcomes. Wearable technologies that can enable continuous/long-term personal health monitoring and personal environmental monitoring can empower users to make better lifestyle decisions and improve health outcomes. While wearable devices promise a compelling future of achieving wellness, current wearable products are not addressing the needs of the health space. To achieve this future, key challenges in wearable systems such as battery life, form factor, sensor functionality, configurability and data analysis will have to be carefully addressed to ensure user adoption and effectively manage health.

This article provides the latest advances from the NSF Advanced Self-powered Systems of Integrated sensors and Technologies (ASSIST) center. The work in the center addresses the key challenges in wearable health and environmental systems by exploring technologies that enable ultra-long battery lifetime, user comfort and wearability, robust medically validated sensor data with value added from multimodal sensing, and access to open architecture data streams. The vison of the ASSIST center is to use nanotechnology to build miniature, self-powered, wearable, and wireless sensing devices that can enable monitoring of personal health and personal environmental exposure and enable correlation of multimodal sensors. These devices can empower patients and doctors to transition from managing illness to managing wellness and create a paradigm shift in improving healthcare outcomes. This article presents the latest advances in high-efficiency nanostructured energy harvesters and storage capacitors, new sensing modalities that consume less power, low power computation, and communication strategies, and novel flexible materials that provide form, function, and comfort. These technologies span a spatial scale ranging from underlying materials at the nanoscale to body worn structures, and the challenge is to integrate them into a unified device designed to revolutionize wearable health applications.

MOTIVATION: Availability of the sequences of entire genomes shifts the scientific curiosity towards the identification of function of the genomes in large scale as in genome studies. In the near future, data produced about cellular processes at molecular level will accumulate with an accelerating rate as a result of proteomics studies. In this regard, it is essential to develop tools for storing, integrating, accessing, and analyzing this data effectively. RESULTS: We define an ontology for a comprehensive representation of cellular events. The ontology presented here enables integration of fragmented or incomplete pathway information and supports manipulation and incorporation of the stored data, as well as multiple levels of abstraction. Based on this ontology, we present the architecture of an integrated environment named Patika (Pathway Analysis Tool for Integration and Knowledge Acquisition). Patika is composed of a server-side, scalable, object-oriented database and client-side editors to provide an integrated, multi-user environment for visualizing and manipulating network of cellular events. This tool features automated pathway layout, functional computation support, advanced querying and a user-friendly graphical interface. We expect that Patika will be a valuable tool for rapid knowledge acquisition, microarray generated large-scale data interpretation, disease gene identification, and drug development. AVAILABILITY: A prototype of Patika is available upon request from the authors.