Assessing the Functionality and Biocompatibility of a Wireless Contact Lens Sensor for 24 hour-intraocular Pressure Monitoring in Volunteers: Preliminary Results

Purpose: In vitro studies in porcine eyes have demonstrated a good correlation between induced intraocular pressure variations and corneal curvature changes, using a contact lens with an embedded microfabricated strain gauge. Continuous 24 hour-intraocular pressure (IOP) monitoring to detect large diurnal fluctuation is currently an unmet clinical need. The aims of this study is to evaluate precision of signal transmission and biocompatibility of 24 hour contact lens sensor wear (SENSIMED Triggerfish®) in humans. Methods: After full eye examination in 10 healthy volunteers, a 8.7 mm radius contact lens sensor and an orbital bandage containing a loop antenna were applied and connected to a portable recorder. Best corrected visual acuity and position, lubrication status and mobility of the sensor were assessed after 5 and 30 minutes, 4, 7 and 24 hours. Subjective comfort was scored and activities documented in a logbook. After sensor removal full eye examination was repeated, and the registration signal studied. Results: The comfort score was high and did not fluctuate significantly, except at the 7 hour-visit. The mobility of the contact lens was minimal but its lubrication remained good. Best corrected visual acuity was significantly reduced during the sensor wear and immediately after its removal. Three patients developed mild corneal staining. In all but one participant we obtained a registration IOP curve with visible ocular pulse amplitude. Conclusions: This 24 hour-trial confirmed the functionality and biocompatibility of SENSIMED Triggerfish® wireless contact lens sensor for IOP-fluctuation monitoring in volunteers. Further studies with a range of different contact lens sensor radii are indicated.

Audit report on the Chariton Valley Planning & Development Council of Governments in Centerville, Iowa for the year ended June 30, 2012

Audit report on the Chariton Valley Planning & Development Council of Governments in Centerville, Iowa for the year ended June 30, 2012

Commissioner’s Planning Guidance, 2013

As technology evolves, vital resources shift, and the state’s population diversifies, Public Safety will have a unique opportunity to show our integrity, values, and worth to the citizens of Iowa. To take advantage of this unique moment in history, and will remain committed to, proactive and on-going strategic mapping. This strategic work will always be guided by Public Safety’s mission and core values, as well as by our responsibility to support local Police Departments and Sheriff’s Offices.

Integration of Bridge Damage Detection Concepts and Components (3 volumes), TR-636, 2013

This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.

Iowa Public Television’s Planning Targets 2011-2014

Agency Performance Plan, Iowa Public Television